PAVAN ADURI, Assistant Professor of Computer Science

 

Ph.D. 2001, Computer Science, University at Buffalo, Buffalo

M. Tech. 1995, Computer Science, Indian Institute of Technology, Kanpur

B. Tech, 1993, Computer Science, JNT University, Hyderabad

 

Major Interests:

Computational Complexity: Average-case complexity, Connections between average-case complexity and worst-case complexity, Structural complexity of function classes.

 

Current Research:

Part of my work is motivated by the following questions:

1. What is a hard problem? What are the properties of hard problems?

2. What are the relationships among various notions of hardness?

3. For problems in NP, what is the relationship between search and decision ?

There are several ways to define a satisfactory notion of hardness such as worst-case hardness, average-case hardness, and almost-everywhere hardness. Part of the work concerns with a variation of average-case hardness known as distributional hardness. This involves understanding various properties of distributionally-hard languages and investigate the question of whether such languages exist in NP.

Some problems such as Permanent have the fascinating property that if they are easy on average, then they are easy in worst-case. Thus, the worst-case hardness of the problem is the same as the average-case hardness of the problem. Can we find such problems in NP? A slightly related question is given a problem in NP that is mildly hard can we construct a much harder problem in NP?

The last question deals with the complexity of function classes. Is computing a witness for a NP problem more difficult than decision? Can we compute some non trivial partial information about NP-complete problems? These questions lead to a study of concepts such as selectivity and membership comparable.

 

Representative Publications:

"Separation of NP-completeness notions", A. Pavan and A. Selman. 16^th Annual IEEE Conference on Computational Complexity, 1999, pp 78-89.

 

"Complete distributional problems, hard languages, and resource-bounded measure", A. Pavan and A. Selman. Theoretical Computer Science. 234:273-286 (2000).

 

"On the hardness of permanent", J. Cai, A. Pavan and D. Sivakumar. Proceedings of the 16th Annual Symposium on Theoretical Aspects of Computer Science LNCS 1563: 90-99, 1999.

 

 

SAMIK BASU, Assistant Professor of Computer Science

 

Ph.D. 2003, Computer Science, State University of New York at Stony Brook

M.S. 2000, Computer Science, State University of New York at Stony Brook

B.E. 1998, Computer Science & Engineering, Jadavpur University, Calcutta

 

Major Interests:

Model Checking, Software Safety & Security Analysis

 

Current Research:

The main thrust of my research is to develop techniques for verification of infinite-state systems and use them to ensure the reliability and security of software systems. Two major activities of my research include (a) developing efficient techniques to detect system flaws and (b) enhancing debugging capabilities by building effective justification of the cause of these flaws.

 

Representative Publications:

Model-Carrying Code: A Practical Approach for Secure Execution of Untrusted Applications. R. Sekar, V.N. Venkatakrishnan, Samik Basu, Sandeep Bhatkar and Daniel C. DuVarney. Nineteenth ACM Symposium on Operating Systems Principles (SOSP-2003)

 

Generation of All Counter-Examples for Push-Down Systems. Samik Basu, Diptikalyan Saha, Yow-Jian Lin and Scott A. Smolka. Application of Formal Description Techniques in Internet and Communication Domains (FORTE-2003)

 

Compositional Analysis for Verification of Parameterized Systems. Samik Basu and C.R. Ramakrishnan. Ninth International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS-2003).

 

Resource Constrained Model Checking for Push-down Systems. Samik Basu, K. Narayan Kumar, Robert L. Pokorny and C.R. Ramakrishan. Eighth International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS-2002).

 

Local and Symbolic Bisimulation using Tabled Constraint Logic Programming. Samik Basu, C.R. Ramakrishan, I.V. Ramakrishnan, M. Mukund and R.M. Verma. International Conference on Logic Programming (ICLP-2001).

 

Model Checking the Java Meta-locking Algorithm. Samik Basu, Scott A. Smolka and Orson R. Ward. Seventh IEEE Conference and Workshops on Engineering of Computer-Based Systems (ECBS-2000).

 

 

CARL K. CHANG, Professor and Chair of Computer Science

 

B.S. 1974, Mathematics, National Central University, Taiwan

M.S. 1978, Computer Science, Northern Illinois University

Ph.D. 1982, Computer Science, Northwestern University

 

Major Interests:

Software engineering, net-centric computing.

 

Current Research:

Professor Chang’s research in software engineering includes two major activities: software architecture based requirements engineering (SABRE) and project management with genetic algorithms (PROMGA). His research in net-centric computing currently focuses on rule-mitigated collaboration technology to support formal electronic meetings. He also studies distributed requirements engineering using mobile agents.

 

Representative Publications (1994-)

Refereed Journal Papers:

Carl K. Chang, Jane Cleland-Huang, Shiyan Hua and Annie Combelles, “On Function-Class Decomposition”, IEEE Computer, Dec. 2001, pp. 87-93.

 

Carl K. Chang, Tao Zhang and Mark Christensen, “Genetic Algorithms for Project Management”, Annals of Software Engineering, Kluwer Academic Publishers, 11:107-139, Nov. 2001.

 

Carl K. Chang, Yong Liu, Thribhuvana Murthy, James Kenevan and Pattanasak Mongkolwat, “Simulation of UICCELL II'', SIMULATION, The Society for Computer Simulation International, 75(3):128-140, Sept. 2000.

 

Carl K. Chang and Chiao-Chuan Shih, “A Circular Skip-Cluster Scheme to Support Video-on-Demand Services'', ACM Multimedia Systems, Springer-Verlag, 7(2):107-118, 1999.

 

Carl K. Chang, Gerald Engel, Willis King, Eric Roberts, Russ Shackelford, Robert H. Sloan, and Pradip K. Srimani, “Curricula 2001: Bringing the Future to the Classroom”, IEEE Computer, 32(9):85-88, September 1999.

 

Carl K. Chang and Mark Christensen, “Net Practice in Software Project Management”, IEEE Software, 16(6):80-88, Nov/Dec 1999.

 

Luqi, Carl K. Chang and Hong Zhu, “Specifications in Software Prototyping'', The Journal of Systems and Software, 42:125-140, 1998.

 

Yahya Al-Salqan and Carl K. Chang, “MediaWare: A Distributed Multimedia Environment with Interoperability.'' Computers in Industry, 29(1-2):71-78, July 1996, Elsevier Science B.V., Netherlands, 1995.

 

Yahya Al-Salqan and Carl K. Chang, “MediaWare : On Distributed Multimedia Temporal Relations and Synchronization Agents.'' IEEE Multimedia, June 1996, pp. 30-39.

 

Carl K. Chang and Chiao-Chuan Shih, “Challenges and Trends of Multimedia Services'', 1994-1995 Annual Review of Communications, National Engineering Consortium, 1995, pp. 683-686.

 

C. K. Chang and Yahya Al-Salqan, “Performance Study of CSMA/CD with Connected Direct Data Link--Simulation Study'', Int'l Journal in Computer Simulation, 4(3):343-371, 1994.

 

Refereed Conference Papers:

Carl K. Chang, Jia Zhang, and Tsang Ming Jiang, “Formalization of Computer Supported Cooperative Work Applications”, Prof. of 2001 IEEE Workshop on Future Trends of Distributed Computing Systems, Bologna, Italy, October 31-November 2, 2001, pp. 185-191.

 

 

Chia-Song Ma*, Carl K. Chang, Jane Cleland-Huang, “Measuring the Intensity of Object Coupling in C++ Programs”, to be published in Proc. of IEEE COMPSAC 2001, Lisle, Illinois, October 8-12, 2001.

 

Jane Cleland-Huang, Carl K. Chang, Hosung Kim and Arun Balakrishnan, “Requirements-Based Dynamic Metrics on Object-Oriented Systems”, to be published in Proc. ff IEEE International Symposium on Requirements Engineering, Toronto, Canada, August, 2001.

 

Carl K. Chang and Lie Cai, “Agent Based Requirements Evolution Over the Internet,” Proc. of IEEE Workshop on Software Engineering on the Internet, The IEEE-CS/IPSJ 2001 Symposium on Applications and the Internet (SAINT 2001), Jan. 8-12, 2001, pp. 83-88.

 

Jane L. Huang and Carl K. Chang, “Supporting the Partitioning of Distributed Systems with Function Class Decomposition”, Proc. of IEEE COMPSAC 2000, Taipei, Taiwan, Oct. 25-27, 2000, pp. 351-356

 

Carl K. Chang, Alexei Vorontsov, Jia Zhang and Francis Quek, “Rule-Mitigated Collaboration Technology”, Proc. of 1999 IEEE Workshop on Future Trends of Distributed Computing Systems, Dec. 20-22, Cape Town, South Africa, pp. 137-142.

 

Carl K. Chang and Seongwoon Kim, “I^3:A Petri-net based Specification Method for Architectural Component”, Proc. of IEEE COMPSAC’99, Oct. 27-29, Phoenix, Arizona, pp. 396-402.

 

Carl K. Chang, Lie Cai and Francis Quek, “On Formal Meetings for Net-centric Web-based Computing”, Proc. of The International Symposium on Internet Technology, Taipei, April 29-May 1, 1998, pp. 35-40.

 

Carl K. Chang, Francis Quek, Lie Cai, Seongwoon Kim and Annie Kunzmann-Combelles, "A Research on Collaboration Net", Proc. of 1997 IEEE Workshop on Future Trends of Distributed Computing Systems, Tunis, Tunisia, October 1997, pp. 228-233.

 

Carl K. Chang, Yi-Te Tseng, and Ugo Buy, "Compiling Process Algebraic Specifications Into Timed Automata", Proc. of IEEE COMPSAC'97, Washington, DC, August 1997, pp. 338-343.

 

Carl K. Chang, Chiao-Chuan Shih, Thinh T. Nguyen and Pattanasak Mongkolwat, “A Popularity-based Data Allocation Scheme for a Cluster-based VOD Server'', Proc. of IEEE COMPSAC'96, Seoul, Korea, August 1996, pp. 62-67.

 

Carl K. Chang and Chiao-Chuan Shih, "Reducing the System Response Time of a Large-scale VOD Server by Disk Grouping", Proc. of IEEE ICCASS '96 (International Conference on Circuits and Systems Symposium), Shanghai, China, June 1996.

 

Yahya Al-Salqan and Carl K. Chang, “MediaWare: On Distributed Multimedi a Synchronization'', Proc. of The second IEEE International Conference on Multimedia Computing and Systems, Washington, DC, May 1995, pp. 150-158.

 

Yahya Al-Salqan and Carl K. Chang, “MediaWare: A Distributed Multimedia Environment with Interoperability'', Proc. of The Fourth IEEE International Workshop on Enabling Technology: Infrastructure for Collaborative Environment, Berkely Springs, WV, April 1995, pp. 128-137.

 

Carl K. Chang, Jamsheed Bugwadia and Pattanasak Mongkolwat, “An Message-Oriented Discrete Event Simulation Model of the Cellular Telephone System", Proc. of 1995 Summer Computer Simulation Conference, Ottawa, Ontario, Canada, 1995, pp. 858-862.

 

Carl K. Chang, Pattanasak Mongkolwat and Bashir Haswarey, “Creating a Distributed Environment Using Object-Oriented Technology'', Proc. of IEEE COMPSAC' 95, Pheonix, Arizona, August 1995, pp. 262-267.

 

Carl K. Chang, Yong Liu and Thribhuvana Murthy, “Study of Performance Engineering with Emphasis on Simulation of UICCELL II", Proc. of IASTED International Conference: MODELLING AND SIMULATION, Pittsburgh, Pennsylvania. April 27-29, 1995, pp. 403-406.

 

 

SOMA CHAUDHURI, Associate Professor of Computer Science

 

B.S. 1984, Mathematics, Massachusetts Institute of Technology, Cambridge

B.S. 1984, Computer Science & Engineering, Massachusetts Institute of Technology, Cambridge

M.S. 1987, Computer Science & Engineering, University of Washington, Seattle

Ph.D. 1990, Computer Science & Engineering, University of Washington, Seattle

 

Major Interests:

Theory of Distributed Computing, Parallel Algorithms and Parallel Complexity.

 

Current Research:

Dr. Chaudhuri's research in distributed computing has focused on understanding the power of asynchronous distributed systems subject to various kinds of failures. A persistent question has been to determine the problems that are solvable in the presence of uncertainty due to processor asynchrony and failures. She used combinatorial techniques to prove that certain problems are impossible to solve in these systems. The current focus of her research has shifted to the study of systems that are semi-synchronous, i.e., that have partial but inexact information about timing. These systems are much more realistic and deserve further study.  Dr. Chaudhuri is using similar combinatorial techniques with the goal of obtaining time and space complexity characterizations for problems in semi-synchronous systems analogous to the fault-resiliency character-ization obtained for problems in asynchronous systems.  The ultimate objective would be to understand in a formal sense the advantage that can be gained by considering timing-based models for distributed computing over asynchronous models, and the disadvantage they represent in relation to fully synchronous models.

Dr. Chaudhuri has also been recently interested in the area of distributed ad hoc networks. In particular, it would be useful to develop algorithms that are specifically suited to solving problems in these networks. These networks are unpredictable due to frequent link failures when nodes drift apart and link formations when nodes drift closer to each other. Existing distributed algorithms that rely on static communication links cannot run in such networks. Instead, efficient algorithms would have to be designed that adjusts to the mobility of the network.

 

Representative Publications:

"Tight Bounds for "k"-Set Agreement." Chaudhuri, S., Herlihy, M., Lynch, N., & Tuttle, M. (2000). To appear in Journal of the ACM.

 

"One-Write Algorithms for Multi-Valued Regular and Atomic Registers," Chaudhuri, S., Kosa, M., & Welch, J.L. Acta Informatica, 37:161-192, 2000.

 

"Wait-Free Implementations in Message Passing Systems."  Chaudhuri, S., Herlihy, M., & Tuttle, M. Theoretical Computer Science  (2000).  Theoretical Computer Science, 220(1):211-245, June 1999.

 

"Shared Memory Consistency Conditions for Non-Sequential Execution: Definitions and Programming Strategies," Chaudhuri, S., Attiya, H., Friedman, R., & Welch, J.L.  SIAM Journal on Computing, 27(1):65-89, February 1998.

 

"Understanding the Set Consensus Partial order Using the Borowsky-Gafni Simulation," Chaudhuri, S., & Reiners, P.  Proceedings of the Tenth International Workshop on Distributed Algorithms, 1996.  Lecture notes in Computer Science 1151, Springer-Verlag, pp. 362-379.

 

"Using Adaptive Timeouts to Achieve At-Most-Once Message Delivery," Chaudhuri, S., Coan, B., & Welch, J. Distributed Computing, 9(3):109-117, September 1995.

 

"Bounds on the Costs of Multi-Valued Register Implementations," Chaudhuri, S., & Welch, J. SIAM Journal on Computing, 23(2):335-354, April 1994.

 

"Designing Algorithms for Distributed Systems with Partially Synchronized Clocks," Chaudhuri, S., Gawlick, R., & Lynch, N. Proceedings of the Twelfth Annual ACM Symposium on Principles of Distributed Computing, August 1993.

 

"More Choices Allow More Faults: Set Consensus Problems in Totally Asynchronous Systems," Chaudhuri, S. Information and Computation, 105(1):132-158, July 1993.

 

 

HUI-HSIEN CHOU, Assistant Professor of Computer Science & Zoology and Genetics

 

B.S, 1984, Chemical Engineering, Ming-Chih Institute of Technology, Taipei, Taiwan

B.S, 1989, Computer Science, National Taiwan University, Taipei, Taiwan

Ph.D., 1996, Computer Science, University of Maryland at College Park

 

203 Science II, Iowa State University, Ames, IA 50011;

Email: hhchou@iastate.edu

 

Major Interests:

Bioinformatics, computational biology, cellular automata, programming language design and compiling.

 

Current Research:

Dr. Chou's research centers around two complementary scientific front-ends: computational biology and artificial life. In computational biology, he studies how to best analyze the vast amount of biological data generated because of recent advances in high-throughput molecular biology research, such as genomics, transcriptomics and proteomics.  These advances allow us to gather explosively more biological data about species, but then only computers can efficiently analyze these huge quantity of data. Dr. Chou has designed an automatic DNA sequence quality assurance program (Lucy) that is in use by many research centers to turn raw DNA sequences into high quality data for subsequent genomic data processing. Dr. Chou is currently working on an integrated approach of biological data analysis that handles sequence, structure, microarray and pathway data altogether based on specialized coding methods developed by him.

One can view computational biology as an analytical approach to understanding life. An alternative, the synthetic approach taken in the artificial life research, aims at simulating life phenomena within computers. It is an attempt to grasp the principles of life in an information processing context without touching the difficult details of implementation such as DNA or proteins. Dr. Chou has been working on the cellular automata modeling of self-replication processes. Cellular automata are massively parallel computer-theoretical models which closely resemble the information restrictions in living cells. As in cells, where no single molecule is the commander-in-chief, in cellular automata, there is no centralized control. All global behaviors must be the collaborative results of each automaton making up the models. Yet, complex and very interesting behaviors such as information self-replication can be observed with such models, promoting one to computationally study the principles of life.

On more practical aspects, Dr. Chou is also involved in programming language design and compiling. He has developed the Trend cellular automata programming language to facilitate the cellular automata studies mentioned above. He is currently working on a visual programming tool that can automatically generate working Perl programs for biologists who may not know how to program in Perl directly.

 

Representative Publications:

Hui-Hsien Chou, Wei Huang and James A. Reggia. "The Trend Cellular Automata Programming Environment." To by published by SIMULATION: Transactions of The Society for Modeling and Simulation International.

 

Hui-Hsien Chou and Michael H. Holmes.  "DNA Sequences Quality Trimming and Vector Removal."  Bioinformatics, 17(12):1093-1104, Dec. 2001.

 

Eugene W. Myers, et al. "A Whole-Genome Assembly of Drosophila." Science, 287:2196-2204, March 24, 2000.

 

Hui-Hsien Chou and James A. Reggia. "Problem Solving During Artificial Selection of Self-Replicating Loops." Physica, D 115:293-312, 1998.

 

Hui-Hsien Chou and James A. Reggia. "Emergent of Self-Replicating Structures in a Cellular Automata Space."  Physica, D 100:252-276, 1997.

 

Hui-Hsien Chou, James A. Reggia, Rafael Navarro-Gonzalez, and Jayoung Wu. "An Extended Cellular Space Method for Simulating Autocatalytic Oligonucleotides." Computers and Chemistry, 18(1):33-43, 1994.

 

James A. Reggia, Steven L. Armentrout, Hui-Hsien Chou, and Yun Peng. "Simple Systems that Exhibit Self-Directed Replication." Science, 259:1282-1288, Feb. 26, 1993.

 

 

OLIVER EULENSTEIN, Assistant Professor of Computer Science

 

Dr.rer.nat. 1998, Computer Science, University of Bonn

Diplom-Informatiker 1991, Computer Science, University of Paderborn (the US-equivalent for Dr.rer.nat. is Ph.D. and for Diplom-Informatiker is M.S )

 

Web Page:  http://www.cs.iastate.edu/~oeulenst

 

Major Research Interests:

Computational Biology, Combinatorial Optimization in Science and Engineering, and Design and Analysis of Discrete Algorithms.

 

Current Research:

Introducing Computational Biology: In July 1995 the first organism, {\Haemo\-philius influenzae} was entirely sequenced and its 1 830 137 DNA base pairs were published. Soon after this other organisms were completely sequenced and, most likely, the human genome will be completely sequenced by the end of this decade.

Given an organism's sequence information, the biologists task is now to reveal  function and interference of these sequences. As a metaphor, the biologist wants  to understand the function of a complex spacecraft engine only by looking at its  parts.

Computational Biology offers algorithms to support biologists in their effort to retrieve information out of an organism's enormous set of sequence information. Design and analysis of these algorithms is based on models that reflect the biologists needs as best as possible. A model must also allow the design of an algorithm that actually solves the problem in practice in a reasonable time. Thus, a basic problem in Computational Biology is to develop good models. Most of the time biologists and computer scientists collaborate to set up an initial model and then refine it stepwise according to practical results. Thus, Computational Biology is an interdisciplinary science where Biology and Computer Science are intertwined.

Current Research in Computational Biology: Reconstructing the ancestral relations of biological sequences can give insights into the function of biological sequences, and thus helps to reveal unknown functions of genes. The ancestral relations of a set of biological sequences can be represented by a rooted tree, where any two sequences are related through their least common ancestor.

Most of my current research is in constructing phylogenetic trees, which is a sub-area of Computational Biology. For convenience I will describe one of my research topics, “phylogenetic super-trees” in more detail.

Computational Biology offers a huge set of different methods for phylogenetic tree construction that are available through program packages like PAUP, McClade and Component, which are widely used by systematic biologists. Already reconstructed phylogenetic trees can be found in phylogenetic tree databases like TreeBase. Some of these databases have grown enormously and now contain sets of trees that overlap in some of their sequences. My goal is to construct a “super-tree” from such a set of overlapping phylogenetic trees. A super-tree would give a much broader picture of how sequences evolve. Unfortunately, combining trees into a super-tree is not an easy task. For example one of the arising problems is that phylogenetic trees have for their shared sequences often different ancient relationships.\medskip

Together with the biologist Mike Sanderson from the University of California Davis, I developed a model to construct super-trees. In collaboration with David Fernandez-Baca and the help of the student Duhong Chen we are designing algorithms based on this model. In our new computational biology lab (CBL), we are implementing own ideas and analyze algorithms. We are also refining the underlying model. Recently Mike Sanderson, the biologist Olaf Biminda-Edmondson, and I received an NSF grand that will support our research on super-trees for the coming three years.

Other topics of my current research in Computational Biology are the prediction of gene-duplications and reconstructing phylogenetic trees from incomplete information. The above should not led to the impression that my interests are exclusively in phylogenetic tree construction. In fact I am interested in many algorithmic problems of biology and actively look for potential interdisciplinary collaborations.

 

Grants:
$  398,170,  funding period 2000-2003,  "Algorithms and Software for Phylogenetic Supertrees"  (NSF-1053164),
O. Eulenstein (co-PI), D. Gusfield (co-PI), M.J. Sanderson (PI).

 

Representative Publications:

D. Chen, L. Diao, O. Eulenstein, D. Fernández-Baca, M. J. Sanderson, Flipping: A Supertree Construction Method to appear in DIMACS Series in Discrete Mathematics and Theoretical Computer Sciences, AMS (2003).

 

D. Chen, O. Eulenstein, D. Fernández-Baca, and M.J. Sanderson; Supertrees by Flipping; Computing & Combinatorics Conference (COCOON) 2002.

D. Chen, L. Diao, O. Eulenstein, D. Fernández-Baca, and M.J. Sanderson; Flipping: A Supertree Construction Method; Ed. F.B.M. Morris et al., DIMACS Series in Discrete Mathematics and Theoretical Computer Sciences, AMS (2002).

J.  Schonfeld, O. Eulenstein, K. VanderVelden, and G.J.P. Naylor; Investigating Evolutionary Lines of Least Resistance Using the Inverse Protein-Folding Problem; Pacific Symposium on Biocomputing (PSB) 2002.

 

Oliver Eulenstein and Martin Vingron, "On the equivalence of two tree mapping measures", Discrete Applied Mathematics, 88:103-128, 1998.

 

Oliver Eulenstein, Boris Mirkin and Martin Vingron. "Duplication-Based Measures of Difference Between Gene- and Species Trees", Journal of Computational Biology, 5:135-148, 1998.

 

Yan P. Yuan, Oliver Eulenstein, Martin Vingron and Per Bork,  "Towards detection of orthologues in sequence databases", Bioinformatics, 14(3):285-289, 1998.

 

Oliver Eulenstein, Boris Mirkin and Martin Vingron, "Comparison of Annotation Duplication, Tree Mapping, and Copying as Methods to Compare Gene Trees with Species Trees,” DIMACS Series in Discrete Mathematics and Theoretical Computer Sciences AMS, 1997.

 

 

DAVID FERNANDEZ-BACA, Professor of Computer Science

 

        B.S. 1980, Electrical & Computer Engineering, National University of Mexico, Mexico City

      M.S. 1983, Electrical & Computer Engineering, University of California, Davis

      Ph.D. 1986, Computer Science, University of California, Davis

 

Major Interests:

Design and analysis of algorithms, combinatorial optimization, graph algorithms, computational biology.

 

Current Research:

Dr. Fernandez-Baca's research is in the design and analysis of combinatorial algorithms.  His main area is parametric optimization, where his goal is to design efficient algorithms to analyze the sensitivity of the optimum solution to changes in the input data. Dr. Fernandez-Baca also studies combinatorial problems arising in sequence comparison and construction of evolutionary trees for sets of species.

 

Representative Publications:

D. Chen, L. Diao, O. Eulenstein, D. Fernández-Baca, and M. Sanderson. Flipping: A supertree construction method. To appear in the Bioconsensus volume of the DIMACS Series in Discrete Mathematics and Theoretical Computer Science, F. McMorris et al. (eds), American Mathematical Society, 2002.

 

D. Fernández-Baca, T. Seppäläinen, and G. Slutzki. Bounds for parametric sequence comparison. Discrete Applied Mathematics, 118:181-198, 2002.

 

D. Chen, O. Eulenstein, D. Fernández-Baca, and M. Sanderson. Supertrees by flipping. To appear in Proceedings of COCOON 2002, Springer-Verlag LNCS.

 

F. Sun, D. Fernández-Baca, and W. Yu. Inverse parametric sequence alignment. To appear in Proceedings of COCOON 2002, Springer-Verlag LNCS.

 

D. Fernández-Baca. Multiparameter matroidal knapsack problems. To appear in Theoretical Computer Science, 2002.

 

D. Fernández-Baca. The perfect phylogeny problem. In Steiner Trees in Industry, X. Cheng and D.-Z. Du (eds.), pp. 203-234, Kluwer, 2001.

 

D. Fernández-Baca. On nonlinear parametric search. Algorithmica, 30:1-11, 2001.

 

D. Fernández-Baca, T. Seppäläinen, and G. Slutzki. Parametric multiple sequence alignment and phylogeny construction. Proc. Combinatorial Pattern Matching 2000, Springer-Verlag LNCS, Vol. 1848, pp. 69--83.

D. Fernández-Baca and J. Lagergren. On the approximability of the Steiner tree problem in phylogeny. Discrete Applied Mathematics 88:129-145, 1998.

 

D. Fernández-Baca and G. Slutzki. Linear-time algorithms for parametric minimum spanning tree problems on planar graphs. Theoretical Computer Science, 181:57-74, 1997 .

 

D. Fernández-Baca and G. Slutzki. Optimal parametric search on graphs of bounded tree-width. Journal of Algorithms 22:212-240, 1997.

 

D. Fernández-Baca and J. Lagergren. A polynomial-time algorithm for near-perfect phylogeny. In proceedings of 23rd International Conference on Automata, Languages, and Programming, pp. 670-680, Springer Verlag Lecture Notes in Computer Science, 1996.

 

 

SHASHI K. GADIA, Associate Professor of Computer Science

 

        B.S. (Hons), 1969, Mathematics, Birla Inst. of Tech. & Science

        M.Sc. 1970, Mathematics, Birla Inst. of Tech. & Science

        Ph.D. 1977, Mathematics, University of Illinois

        M.S. 1980, Computer Science, Ohio State University

 

Major Interests:

Temporal, spatial, belief, security, statistical and incomplete data; database models, type hierarchy, languages, user interfaces, optimization, implementation and access methods; pattern matching in spatio-temporal data.

 

Current Research:

Models, query languages, incomplete information, implementation, index structures, and query optimization for dimensional (temporal, spatial, and belief), genetic, and other forms of data, in relational, object-oriented, and semistructured (XML) database paradigms. The goal of the research in dimensional data is to unify different forms of dimensional data seamlessly in a scalable, efficient, easy to use, and coherent framework. An object-oriented model and query language for dimensional data that is consistent with the ODMG (Object Data Management Group) standard is of interest. Database models for semistructured data are rapidly advancing under the banner of XML (Extensible Markup Language). The February 16, 2001 announcements of the XML’s Query Group of the W3 (World Wide Web) Consortium represent a major milestone that extends the established classic database style wisdom of powerful and declarative algebraic querying to XML by treating XML documents as databases. This will advance the frontiers of databases in revolutionary ways to applications such as e-business, software engineering, and genetic data where representation and/or exchange of heterogeneous and evolutionary information is required. 

 

Representative Publications:

 “A linguistic framework for multidimensional data,” Elisa Bertino, Tsz S. Cheng, Shashi K Gadia, and Giovanna Guerrini. Submitted for publication, February, 2001. 

 

“Querying multiple temporal granularity data.” Isabella Merlo, Elisa Bertino, Elena Ferrari, Shashi K Gadia, and Giovanna Guerrini.  Proceedings Seventh International Workshop on Temporal Representation and Reasoning of TIME-2000, Nova Scotia, Canada, July 7-9, 2000

 

“Algebraic identities and query optimization in the parametric model for relational temporal databases,” IEEE Transactions on Knowledge and Data Engineering. Vol 10(5), pp 793-807, 1998.

 

“Applicability of Temporal Data Models to Query Multilevel Security Databases: A Case Study, Shashi K. Gadia. Research and Practice; Etzion, Jajodia, and Sripada, eds.; Lecture Notes in Computer Science, 1399: 238-256, Springer Verlag, Berlin, 1998.

 

“Relational Database Systems With Zero Information-Loss,” Gadia, S., & Bhargava, G. (1993).  IEEE Transactions on Knowledge and Data Engineering, 5:76-87.

 

"Incomplete Information in Relational Temporal Databases,” Gadia, S., Nair, S., & Poon, Y. (1992).  Proceedings of the 18th International Conference on Very Large Databases, pp. 395-406.

 

"A Generalized Model for a Relational Temporal Database,” Gadia, S., & Yeung, C.  (1988).  ACM SIGMOD Conference on Management of Data, pp. 251-259.

 

“A Homogeneous Relational Model and Query Languages for Temporal Databases,” Gadia, S.  (1988). ACM Transactions on Database Systems, 14:418-448.

 

“A Query Language for a Homogeneous Temporal Database,” Gadia, S., & Vaishnav, J.  (1985). Proc. Fourth Annual ACM SIGACT-SIGMOD Symposium on Principles of Database Systems, pp 51-56.

 

“The concept of an error in a database: an application of temporal databases,” Gautam Bhargava and Shashi K. Gadia. Appeared in Proceedings of INSDOC COMAD90 International Conference on Management of Data, December 1990.

 

VASANT HONAVAR, Professor of Computer Science

 

B.E. 1982, Electronics Engineering, Bangalore University, India

M.S. 1984, Electrical and Computer Engineering, Drexel University

M.S. 1989, Computer Science, University of Wisconsin at Madison

Ph.D. 1990, Computer Science and Cognitive Science, University of Wisconsin at Madison

 

www:  http://www.cs.iastate.edu/~honavar/

 

Current Affiliations:

Professor, Department of Computer Science

Director, Artificial Intelligence Research Laboratory

Editor-in-Chief, Cognitive Systems Research

Project Director, Bioinformatics, Computational Molecular Biology Training Group

Associate Chair, Bioinformatics and Computational Biology Graduate Program

Faculty Member, Bioinformatics and Computational Biology Graduate Program

Faculty Member, Laurence H. Baker Center for Bioinformatics and Biological Statistics

Faculty Member, Virtual Reality Applications Center

Faculty Member, Information Security Graduate Program

Faculty Member, Neuroscience Graduate Program

 

Research and Teaching Interests:

Artificial Intelligence (Autonomous Agents; Automata Induction; Computational Learning Theory; Computational Organizational Theory; Data Mining, Knowledge Discovery and Visualization; Distributed Knowledge Networks; Cumulative Distributed Learning; Incremental Learning; Intelligent Agents and Multi-Agent Systems; Multi-Agent Coordination, Communication, and Negotiation; Knowledge Representation and Inference; Probabilistic Models and Bayesian Inference; Machine Learning; Neural Networks); Bioinformatics (Distributed Information Networks for for Data Integration, Information Extraction, Data Mining, and Knowledge Discovery; Knowledge Representation and Automated Inference); Computational Molecular Biology (Genetic Networks; Computational Characterization of Protein Sequence-Structure-Function Relationships and and Protein-Protein Interactions; Computational Genomics; Metabolic Pathways; Gene Expression Analysis; Computational Neuroscience; Evolutionary, Cellular, and Neural Computation); Distributed Information Networks (Distributed Knowledge Networks; Distributed Databases, Mediators, and Data Warehouses; Intelligent Agents, Mobile Agents, and Multi-Agent Systems); Applied Artificial Intelligence.

Examples of current projects in Honavar's laboratory on Distributed Intelligent Information Systems focuses on the design, analysis, and implementation of algorithms and software for information extraction, integration, organization, and visualization; and learning from from heterogeneous, distributed, dynamic, and autonomous data, information, and knowledge sources. In particular, we are developing ontology-driven information integration that enable analysis of data from multiple perspectives, algorithms with provable performance guarantees for distributed, incremental, and cumulative learning tasks; algorithms for learning from data and knowledge (including alternative ontologies), algorithms for learning from alternately structured (e.g. relational, graph, etc.) data; and algorithms for multi-agent learning.  This work is driven by large-scale applications of machine learning and automated inference for scientific discovery in Computational Molecular Biology and other data-rich domains.

In related work, topics in mobile agent infrastructures, inter-agent negotiation protocols, distributed problem solving, coordination and control structures for multi-agent systems, and agent-oriented software engineering are being investigated.

 Current research in Computational Molecular Biology emphasizes machine learning approaches to gene discovery, characterization of protein sequence-structure-function relationships, protein-protein interactions, discovery of genetic networks from expression data, and information theoretic, and grammatical analysis of DNA and protein sequences, and computational geometric analysis of protein structures.

Honavar's research is supported in part by grants from the National Science Foundation, Department of Defense, John Deere Foundation, Carver Foundation, Pioneer Hi-Bred, Inc., Department of Energy, and the ISU Graduate College.

 

Recent Representative Publications:

Andorf, C., Dobbs, D., and Honavar, V. (2002). Discovering Protein Function Classification Rules from Reduced Alphabet Representations of Protein Sequences. In: Proceedings of the Conference on Computational Biology and Genome

Informatics (part of the 2002 Joint Conference on Information Sciences). Durham, North Carolina.

 

Caragea, D., Silvescu, A., and Honavar, V. (2002). Invited Chapter. Multi-Agent Decision Tree Learning from Distributed Autonomous Data Sources. In: Intelligent Agent Software Engineering. Plekhanova, V. and Wermter, S. (ed.). Idea Group Publisher. In press.

 

Honavar, V., Andorf, C., Caragea, D., Dobbs, D., Reinoso-Castillo, J., Silvescu, A. (2002). Invited Chapter. Algorithmic and Systems Solutions for Computer Assisted Knowledge Acquisition in Bioinformatics and Computational Biology. In: Computational Biology and Genome Informatics. Wu, C., Wang,P., and Wang, J. (Ed.) World Scientific. In press.

 

Wang, X., Schroeder, D., Dobbs, D., and Honavar, V. (2002). Data-Driven Discovery of Protein Function Classifiers: Decision Trees Based on MEME Motifs Outperform Those Based on PROSITE Patterns and Profiles on Peptidase Families. In Proceedings of the Conference on Computational Biology and Genome Informatics (part of the 2002 Joint Conference on Information Sciences).

 

Balakrishnan, K. and Honavar, V. (2001). Evolving Neurocontrollers and Sensors for Artificial Agents. In: Advances in Evolutionary Synthesis of Intelligent Agents. Patel, M., Honavar, V. and Balakrishnan, K. (Ed). Cambridge, MA: MIT Press. pp. 109-152.

 

Caragea, D., Silvescu, A., and Honavar, V. (2001).  Invited Chapter. Analysis and Synthesis of Agents that Learn from Distributed, Dynamic Data Sources. Emergent Neural Computational Architectures. Wermter, S., Austin, J., and Willshaw, D. Springer-Verlag.

 

Caragea, D., Cook, D., and Honavar, V. (2001). Gaining Insights into Support Vector Machine Classifiers Using Projection-Based Tour Methods. In: Proceedings of the Conference on Knowledge Discovery and Data Mining (KDD-01). AAAI Press.

 

Helmer, G., Wong, J., Slagell, M., Honavar, V., Miller, L. and Lutz, R. (2001). A Software Fault Tree Approach to Requirements Analysis of an Intrusion Detection System. In: Proceedings of the Symposium on Requirements Engineering for Information Security, Indianapolis, IN, USA.

 

Mikler, A., Honavar, V. and Wong, J. (2001). Autonomous Agents for Coordinated Distributed Parameterized Heuristic Routing in Large Dynamic Communication Networks. Journal of Systems and Software.  56:231-246.

 

Parekh, R. and Honavar, V. (2001). DFA Learning from Simple Examples. Machine Learning. 44:9-35.

 

Polikar, R., Udpa, L., Udpa, S., and Honavar, V. (2001). Learn++: An Incremental Learning Algorithm for Multi-Layer Perceptron Networks. IEEE Transactions on Systems, Man, and Cybernetics. 31(4):497-508.

 

 

XIAOQIU HUANG, Associate Professor of Computer Science

 

B.S. 1982, Computer Science, Changsha Institute of Technology

M.S. 1989, Computer Science, Pennsylvania State University

Ph.D. 1990, Computer Science, Pennsylvania State University

 

Major Research Interests:

Computational biology, parallel and distributed applications.

 

Current Research:

Dr. Huang is interested in algorithms and software for solving computational problems in genome sequencing and analysis.  He has developed a number of computer programs for analysis of DNA and protein sequences.  Dr. Huang's programs have been included in a number of academic and commercial packages. Most of his programs can be used on WWW at http://bioinformatics.iastate.edu/aat/sas.html.

 

Dr. Huang is currently working on a DNA sequence assembly program for a whole-genome data set of 30 million sequences. The sequence assembly program is used to assemble short DNA sequences into long sequences in shotgun DNA sequencing projects. He is also working on a computer program for comparing all the DNA sequences of the human genome with  those of the mouse genome. The goal of this project is to develop a computer program that quickly computes

biologically interesting similarities between the two genomes. In the future, Dr. Huang will continue to work on computational programs in genome sequencing and analysis.

 

Recent Publications:

Huang, X., Wang, J., Aluru, S., Yang, S.-P. and Hillier, L. (2003). PCAP: A Whole-Genome Assembly Program, Genome Research, 13: 2164-2170.

 

Huang, X. and Chao, K.-M. (2003). A Generalized Global Alignment Algorithm, Bioinformatics, 19: 228-233.

 

Huang, X, and Madan, A. (1999).  CAP3: A DNA Sequence Assembly Program, Genome Research, 9: 868-877.

 

Huang, X, Adams, M.D., Zhou, H., and Kerlavage, A.R. (1997).  A Tool for Analyzing and Annotating Genomic Sequences, Genomics, 46(1):37-45.

 

Huang, X., and Zhang, J. (1996).  Methods for Comparing a DNA Sequence with a Protein Sequence, Computer Applications in the Biosciences, 12(6):497-506.

 

Huang, X. (1996). Fast Comparison of a DNA Sequence with a Protein Sequence Database, Microbial & Comparative Genomics, 1(4):281-291.

 

YAN-BIN JIA, Assistant Professor of Computer Science

 

B.S. 1988, Computer Science, University of Science and Technology of China

M.S. 1993, Robotics (and Computer Science), Carnegie Mellon University

Ph.D. 1997, Robotics (and Computer Science), Carnegie Mellon University

 

Major Research Interests:

Robotics, shape localization, reconstruction, and recognition, computational geometry, geometric modeling, curve computation, robot sensing, dexterous manipulation and control, hacking robot interfaces, optimization, nonlinear

control and observation, kinematics and dynamics of manipulation.

Internet: jia@cs.iastate.edu

 

Current Research:

"The hand is the cutting edge of the mind," and "The world can only be grasped by action, not by contemplation," says Bronowski in his book "The Ascent of Man".  Dr. Jia's main research objective is to make the robot execute real world tasks intelligently and skillfully.  

His investigation into robot dexterity has focused on seeking a coordinated understanding of computational and control issues in manipulation tasks. One objective of this study is dynamic retrieval of geometric information such as  shape and pose, and of mechanical information such as motion and force.  Another objective is careful engineering of the above information to make the robot exhibit skills during its execution of physical tasks. Through efforts balanced between theoretical inquiry and experimental demonstration, Dr. Jia hopes to gain in-depth knowledge about action and intelligence as they interact with each other.

For over two years Dr. Jia has been studying how to program a robotic hand to localize and recognize an object of curved shape and to execute basic operations as well as dextrous maneuvers.  This investigation makes primary use of one source of information which is ubiquitous in the physical world ---{\it contact} between two or more bodies.  He hopes to understand basic computational principles of touch sensing in the context of parts localization, model-based recognition, and shape reconstruction. 

The human learns skills through practice, so should the robot.  Dr. Jia is also interested in applying learning techniques to tackle tasks that would be computationally expensive or intractable otherwise. He would like to program the robot so that it will be able to give performances that approach the human level someday.

 

Representative Publications:

"Curvature-Based Computation of Antipodal Grasps", Yan-Bin Jia. Accepted by the IEEE International Conference on Robotics and Automation, Washington, D.C., May 11-15, 2002.

 

"Geometry and Computation of Antipodal Points on Plane Curves", Yan-Bin Jia. submitted to Computational Geometry: Theory and Applications.  Technical Report ISU-CS-01-04, CS Department, Iowa State University, Ames, IA, 2001.

 

"Localization on Curved Objects Using Tactile Information", Yan-Bin Jia. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 701-706, Maui, HI, Oct 29-Nov 3, 2001.

 

"Grasping Curved Objects through Rolling," Yan-Bin Jia. In Proceedings of the IEEE International Conference on Robotics and Automation, pp. 377-382, San Francisco, CA, April 2000. 

 

"Pose and Motion from Contact," Yan-Bin Jia and Michael Erdmann. International Journal of Robotics Research, 18(5):466-490, 1999.

 

"Local Observability of Rolling," Yan-Bin Jia and Michael Erdmann. In Robotics: The Algorithmic Perspective, P.K. Agarwal et al. (eds.), pp. 251-263, A. K. Peters, Boston, 1998. Also Proc. 3rd Int'l Workshop on the Algorithmic Foundations of Robotics, Houston, TX, March 1998. 

 

"Geometric Sensing of Known Planar Shapes," Yan-Bin Jia and Michael Erdmann. International Journal of Robotics Research, 15(4):365-392, 1996.

 

"The Complexity of Sensing by Point Sampling," Yan-Bin Jia and Michael Erdmann. In Algorithmic Foundations of Robotics, Ken Goldberg et al. (eds.), pp. 283-300, A. K. Peters, Boston, 1995. Also Proc. 1st Int'l Workshop on the Algorithmic Foundations of Robotics, San Francisco, CA, February 1994. 

 

 

GARY T. LEAVENS, Professor of Computer Science
 

      B.S. 1978, Computer & Communication Sciences, The University of Michigan

      M.S. 1980, Computer Science, The University of Southern California

      Ph.D. 1989, Computer Science, Massachusetts Institute of Technology

 

Major Interests:

Programming and specification language design and semantics, formal methods (program specification and verification), type theory, object-oriented programming languages, aspect-oriented programming languages, component-based systems,  information assurance, functional programming, distributed programming languages.

 

Current Research:

The long term goal of Dr. Leavens's research is to understand better how to solve programming problems: how to specify such problems, methods for thinking about such problems, notations for expressing solutions, ways to check that the solutions are correct, and tools for automating and assisting with these processes. In pursuing this goal, he has worked in two main areas: formal methods and programming languages.

 

Formal Methods

Dr. Leavens's work in formal methods has been focused on ways to specify and verify object-oriented (OO) software components.  The specification work involves the design and formal description of behavioral interface specification languages (BISLs).  BISLs record information about detailed design: the interfaces and functional behavior of program modules.  Dr. Leavens's group has designed a BISL for Smalltalk, called Larch/Smalltalk, a BISL for C++, called

Larch/C++, and, a BISL for Java called JML (see www.jmlspecs.org). Work on these BISLs focuses on the problem of how

to make them expressive enough for documenting existing code; this is measured using both theoretical analysis and case studies.  The group has made some progress towards solving this problem; for example, work reported at OOPSLA 2000 aims to explain needs to be specified to deriving a subclass without seeing the source code for a superclass.  However, there is a lot of information that cannot (yet) be recorded, such as performance constraints.  The current work on JML has been funded by the National Science Foundation (NSF), and tries to address some of these issues, as well as issues of practicality and how to deal with multimethods (see below). Early work on JML was done jointly with Professor Al Baker, and Clyde Ruby was and is a major contributor.  Yoonsik Cheon, designed Larch/Smalltalk and is also contributing to the design of JML. Dr. Leavens has also been working with Baker and a former Ph.D. student, Tim Wahls, on executing such specifications.

A long term interest for Dr. Leavens, in the area of formal methods for software components, is behavioral subtyping. Behavioral subtyping allows one to reason about OO programs that use message passing. To explain this, consider that the message passing mechanism of OO languages, such as C++ and Java, allows one to easily extend programs by adding new types.  This works best if objects of the new types behave like the objects of the old types; the old types are supertypes of the new types, which are called subtypes. How should one reason about programs that use subtyping and message passing?  A reasoning method, formalized by specification and verification techniques, should be "modular" in the sense that when subtypes are added to a program, unchanged modules do not have to be respecified or reverified. Modular reasoning is guaranteed by the technique of supertype abstraction, which relies on behavioral subtyping. To use supertype abstraction, one specifies and verifies code in terms of the static types of expressions written in a program (as usual), uses a type checker to ensure that the static types are supertypes of the run-time types, and then must prove that subtypes obey the specifications of their supertypes.  This last condition is behavioral subtyping.

Krishna Kishore Dhara, a former Ph.D. student supervised by Leavens, has extended the formal theory of behavioral subtyping to types whose instances have time-varying state.  Professor Don Pigozzi (of the Mathematics Department at ISU) and Leavens have found an exact algebraic characterization of behavioral subtyping for immutable types.  They are now working on effective techniques for proving behavioral subtyping. This joint research has been funded by the NSF.

The potential impact of the work in formal methods is possibly great; it might lead to the engineering of software, instead of hacking. It also seems necessary for high quality software components and reuse. But more realistically, Leavens views the research as trying to formally understand what one needs to think about when documenting and reasoning about a program or program component. This can be of great value for teaching and for the construction of tools, even if people do not use the formalism directly or on a daily basis.

 

Programming Language Design and Semantics

The other main aspect of Dr. Leavens's work has been on the design and semantics of object-oriented languages with generic functions.  Such languages are known as multimethod programming languages, because method calls can dispatch a message send on all arguments, unlike a single-dispatching OO language, such as Smalltalk, C++, or Java. Multimethod languages are interesting because they can more easily express solutions to certain problems in OO programming (binary

methods).

Leavens's work on multimethod languages is joint with Ph.D. student Curtis Clifton, and has been done in collaboration with and with Craig Chambers of the University of Washington, and Chambers's student Todd D. Millstein.  Former master's students Jianbing Chen and Sevtap Karakoy also have contributed to this work.  The work focuses on the semantics and type systems for variants of the Cecil and Java languages. To date they have published papers about an algorithm for type checking such languages with very expressive features (orthogonal inheritance and subtyping), about how to add multimethods to existing languages, and a way to add multimethods to Java. One big problem is to get a language with both a (sound) static type system and a sensible module system; however, this problem has been solved by Millstein and Chambers (as reported in ECOOP '99).  We have applied these ideas to the design of an extension to the Java programming language called MultiJava (see www.multijava.org). A long term goal is a language that allows one to program abstract data types in two styles, one of which is easier to extend (as in standard OO languages) and the other of which is easier to reason about. Programmers can use both styles in the same program. Another goal is to extend the kind of modular programming and reasoning techniques that apply to MultiJava to aspect-oriented programs.  The potential impact of these research directions might be large if this leads to more flexible, modular, and reusable coding practices. A recent NSF grant has funded research on formal methods for such languages.

 

See http://www.cs.iastate.edu/~leavens/ for details.

 

Representative Publications

Clyde Ruby and Gary T. Leavens. Safely Creating Correct Subclasses without Seeing Superclass Code. In OOPSLA 2000 Proceedings, pp. 208-228 (Volume 35, number 10 of ACM SIGPLAN Notices, October 2000).

 

Curtis Clifton, Gary T. Leavens, Craig Chambers, and Todd Millstein. MultiJava: Modular Open Classes and Symmetric Multiple Dispatch for Java. In OOPSLA 2000 Proceedings, pp. 130-145 (Volume 35, number 10 of ACM

SIGPLAN Notices, October 2000).

 

Gary T. Leavens and Don Pigozzi. A complete algebraic characterization of behavioral subtyping. Acta Informatica, 36:617-663, 2000.

 

Gary T. Leavens and Krishna Kishore Dhara. Concepts of Behavioral Subtyping and a Sketch of their Extension to Component-Based Systems. In Gary T. Leavens and Murali Sitaraman (editors), Foundations of Component-Based Systems, Cambridge University Press, 2000. Chapter 6, pages 113-135.

 

Gary T. Leavens and Todd D. Millstein.  Multiple Dispatch as Dispatch on Tuples.  In OOPSLA '98 Conference Proceedings, pages 374-387, Volume 33, number 10 of ACM SIGPLAN Notices, October 1998.

 

Gary T. Leavens and Jeannette M. Wing.  Protective Interface Specifications.  Formal Aspects of Computing, 10:59-75, 1998.

 

Gary T. Leavens. An Overview of Larch/C++: Behavioral Specifications for C++ Modules. In Haim Kilov and William Harvey (editors), Specification of Behavioral Semantics in Object-Oriented Information Modeling (Kluwer Academic Publishers, 1996), Chapter 8, pages 121-142.

 

Krishna Kishore Dhara and Gary T. Leavens. Forcing Behavioral Subtyping Through Specification Inheritance. In Proceedings 18^th International Conference on Software Engineering, Berlin, Germany, pages 258-267. IEEE, 1996.

 

Gary T. Leavens and William E. Weihl. Specification and Verification of Object-Oriented Programs Using Supertype Abstraction. Acta Informatica, 32(8):705-778, November 1995.

 

Kim B. Bruce, Luca Cardelli, Giuseppe Castagna, The Hopkins Objects Group, Gary T. Leavens, and Benjamin Pierce. On Binary Methods. Theory and Practice of Object Systems 1(3):221-242, 1995.

 

Craig Chambers and Gary T. Leavens. Typechecking and Modules for Multimethods. ACM Transactions on Programming Languages and Systems, 17(6):805-843, November 1995.

 

Yoonsik Cheon and Gary T. Leavens. The Larch/Smalltalk Interface Specification Language. ACM Transactions on Software Engineering and Methodology, 3(3):221-253, July 1994.

 

Gary T. Leavens, Modular Specification and Verification of Object-Oriented Programs. IEEE Software, 8(4):72-80, July, 1991.

 

Gary T. Leavens and William E. Weihl. Reasoning about Object-Oriented Programs that use Subtypes (extended abstract). In OOPSLA ECOOP '90 Proceedings, pages 212-223 (Volume 25, number 10 of ACM SIGPLAN

Notices, October 1990).

 

 

MARKUS LUMPE, Assistant Professor of Computer Science

 

        M.S. 1990, Computer Science, Dresden University of Technology

        PhD. 1999, Computer Science, Institute of Computer Science and Applied Mathematics, University of Berne

 

Major Research Interests:

Design and implementation of object- and component-oriented languages, Type theory for software composition, Formal semantics, Concurrent programming, Object-oriented compiler construction techniques.

Current Research:

My major research interests are in programming languages, modern compiler construction, and component technology. Within these areas, I am focusing on foundations like type systems, behavioral equivalence theories, distribution and localization of components and processes. In addition, I am very much interested in applications aspects like the modeling of compositional abstractions, component repositories, and the specification of functional and non-functional properties of components. My primary long-term goal is the development of a robust formal model to specify applications as composition of distributed components.

I have developed the pL-calculus, a variant of the p-calculus, which is used as the formal basis for Piccola, a small compo-sition language. The pL-calculus is a process calculus, in which agents communicate by passing extensible, labeled records, or so-called “forms'', rather than tuples. This approach makes it much easier to model compositional abstractions than it is possible in the plain p-calculus, since the contents of communication are now independent of position; agents are more naturally polymorphic since communication forms can be easily extended, and environmental arguments can be passed implicitly.

The next stage will be a higher-order system, which provides also means for communicating agents – agents will become first-class entities. Moreover, the next stage will employ the unifying concept that “everything is a form”, that is, every abstraction is itself a form. Therefore, the distinction between agents, channels, and forms will disappear, which will hopefully result in a unique language paradigm for software composition.

Additionally, I have an active interest in the development of modern compiler techniques and programming languages. My interests focus on (i) the definition of an object- or component-oriented framework for defining any kind of language processors, (ii) the definition of framework to map any source language to the Java virtual machine, and (iii) the definition of new higher-level programming abstractions and idioms.

 

Representative Publications:

Markus Lumpe, Jean-Guy Schneider and Oscar Nierstrasz, “Using Metaobjects to Model Concurrent Objects with PICT”, Proceedings of Languages et Modèles à Objects, Leysin, October 1996, pp. 1-12.

 

Jean-Guy Schneider and Markus Lumpe, “Synchronizing Concurrent Objects in the Pi-Calculus”, Proceedings of Langages et Modèles à Objets '97, Roland Ducournau and Serge Garlatti (Eds.), Hermes, Roscoff, October 1997, pp. 61-76.

 

Markus Lumpe, Jean-Guy Schneider, Oscar Nierstrasz and Franz Achermann, “Towards a formal composition language”, Proceedings of ESEC '97 Workshop on Foundations of Component-Based Systems, Gary T. Leavens and Murali Sitaraman (Eds.), Zurich, September 1997, pp. 178-187.

 

Markus Lumpe, “A Pi-Calculus Based Approach for Software Composition”, Ph.D. thesis, University of Bern, Institute of Computer Science and Applied Mathematics, January 1999.

 

Franz Achermann, Markus Lumpe, Jean-Guy Schneider and Oscar Nierstrasz, “Piccola - a Small Composition Language”, Formal Methods for Distributed Processing, an Object Oriented Approach, Howard Bowman and John Derrick. (Eds.), Cambridge University Press, 2000.

 

Markus Lumpe, Franz Achermann and Oscar Nierstrasz, “A Formal Language for Composition”, Foundations of Component Based System, Gary Leavens and Murali Sitaraman (Eds.), Cambridge University Press, 2000.

 

Jean-Guy Schneider and Markus Lumpe, “A Metamodel for Concurrent, Object-based Programming”, Proceedings of Langages et Modèles à Objets '2000, Hermes, Mont Saint-Hilaire, Québec, January 2000.

 

Markus Lumpe and Jean-Guy Schneider, “Forms - A Flexible Notation for Software Composition”, Proceedings of Third Australian Workshop on Software and System Architectures, John Grundy and Jun Han (Eds.), Sydney, November 2000, pp. 24-36.

 

 

 

JACK H. LUTZ, Professor of Computer Science

 

        B.G.S. 1976, Mathematics, University of Kansas

        M.A. 1979, Mathematics, University of Kansas

        M.S. 1981, Computer Science, University of Kansas

        Ph.D. 1987, Mathematics, California Institute of Technology

 

Major Interests:

Computational Complexity, including structure of complexity classes, resource-bounded measure and dimension, and probabilistic complexity.  Algorithmic Information and Randomness, including computational randomness, constructive dimension, Kolmogorov complexity, prediction, computational depth, and games.

 

Current Research:

Professor Lutz does most of his research in two areas: computational complexity and algorithmic information theory.  In computational complexity he and his students are investigating the structure of complexity classes (deterministic, non-deterministic, and probabilistic) using resource-bounded measure and dimension, complexity-theoretic generalizations of Lebesgue dimension and fractal dimension that he has developed.  Current work focuses on weak derandomization, weak completeness, average-case complexity, circuit-size complexity, strong hypotheses, real-valued functions, and the foundation of resource-bounded measure and dimension.  In algorithmic information, he and his students are investigating randomness, Kolmogorov complexity, algorithmic prediction, and computational depth.  This work is uncovering a variety of new applications of theory of computation in information theory, computational learning, fractal geometry, and games.

 

Representative Publications:

Jack J. Dai, James I. Lathrop, Jack H. Lutz, and Elvira Mayordomo. “Finite-State Dimension.” Proceedings of the Twenty-Eighth International Colloquium on Automata, Languages, and Programming, Crete, Greece, July 8-12, 2001, Springer-Verlag, 2001, pp. 1028-1039.

 

Josef M. Breutzmann, David W. Juedes, and Jack H. Lutz. “Baire Category and Nowhere Differentiability for Feasible Real Functions.” Proceedings of the Twelfth Annual International Symposium on Algorithms and Computation. Christchurch, New Zealand, December 19-21, 2001, Springer-Verlag, 2001, pp. 219-230.

 

“Gales and the Constructive Dimension of Individual Sequences.” Proceedings of the Twenty-Seventh International Colloquium on Automata, Languages, and Programming. Geneva, Switzerland, July 9-15, 2000, Springer-Verlag, 2000, pp. 902-913. 

 

“Dimension in Complexity Classes.” Proceedings of the Fifteenth Annual IEEE Conference on Computational Complexity. Florence, Italy, July 4-7, 2000), IEEE Computer Society Press, 2000, pp. 158-169.

 

Jack H. Lutz, Vikram Mhetre and Sridhar Srinivasan. “Hard Instances of Hard Problems.” SIAM Journal on Computing, to appear.

 

Jack J. Dai and Jack H. Lutz. “Query Order and NP-Completeness.” Information and Computation, to appear.

 

Jack H. Lutz and Yong Zhao. “The Density of Weakly Complete Problems under Adaptive Reductions.” SIAM Journal on Computing. 2000, 30:1197-1210.

 

David W. Juedes and Jack H. Lutz. “Modeling Time-Bounded Prefix Kolmogorov Complexity.” Theory of Computing Systems.  Mathematical Systems Theory. 2000, 33:111-123.

 

Josef M. Breutzmann and Jack H. Lutz. “Equivalence of Measures of Complexity Classes.” SIAM Journal on Computing. 2000.  29:302-326.

 

Jack H. Lutz and James I. Lathrop. “Recursive Computational Depth.” Information and Computation, 1999, 153:139-172.

 

 

ROBYN LUTZ, Associate Professor of Computer Science

 

B.A. 1974, English, University of Kansas

M.A. 1976, Spanish, University of Kansas

Ph.D. 1980, Spanish, University of Kansas

M.S. 1990, Computer Science, Iowa State University

 

Major Interests:

Software engineering, software safety, requirements engineering, formal methods for specification and verification, safety-critical product lines, and fault monitoring and recovery for spacecraft autonomy.

 

Current Research:

Dr. Lutz' research is in two overlapping areas of software engineering: (1) how to build safe systems and (2) how to specify and analyze requirements.

In the first area, her work focuses on software system safety. In particular, she is interested in developing safety analysis techniques for high-integrity product lines.  Dr. Lutz is also working on architectural analysis techniques for safety-critical systems. Her vision for future research in this area is detailed in her recent survey, "Software Engineering for Safety: A Roadmap," available on her web page (http://www.cs.iastate.edu/~rlutz).

In the second area, her interest is in formally modeling and analyzing requirements for fault detection and recovery.  Many of her results in this area have been applied to NASA spacecraft. Currently, she is also principal investigator on a NASA-funded research project to characterize critical software anomalies that escape testing to manifest themselves during flight.

 

Representative Publications: 

"Operational Anomalies as a Cause of Safety-Critical Requirements Evolution,” with C. Mikulski, The Journal of Systems and Software, to appear.

 

"Evolution of Safety-Critical Requirements Post-Launch," with C. Mikulski, Fifth IEEE International Symposium on Requirements Engineering (RE'01), August 27-31, 2001, Toronto, Canada.

 

"A Software Fault Tree Approach to Requirements Analysis of an Intrusion Detection System," with G. Helmer, J. Wong, M. Slagell, V. Honavar, and L. Miller, Symposium on Requirements Engineering for Information Security, March 5-6, 2001.

 

"Extending the Product Family Approach to Support Safe Reuse," The Journal of Systems and Software, 53(3):207-217, September 2000.

 

"Software Engineering for Safety: A Roadmap," in The Future of Software Engineering, Ed. Anthony Finkelstein, ACM Press, 2000, pp. 213-224.

 

"An Approach to Architectural Analysis of Product Lines," with Gerald C. Gannod, 22nd International Conference on Software Engineering (ICSE'00), June 7-9, 2000, Limerick, Ireland, pp. 548-557.

 

"Failure Modes and Effects Analysis," with R. Woodhouse, Encyclopedia of Electrical and Electronics Engineering, ed. J. Webster, John Wiley and Sons Publishers, Vol. 7, 1999, p. 253-257.

 

"Applying Adaptive Safety Analysis Techniques," with Hui-Yin Shaw, Tenth International Symposium on Software Reliability Engineering (ISSRE'99), Nov. 1-4, 1999, Boca Raton, FL.

 

"Using Immersive Virtual Environments for Certification," with C. Cruz-Neira, IEEE Software, Vol. 16, 4, July/Aug, 1999, pp. 26-30.

 

"Toward Safe Reuse of Product Family Specifications," Proceedings of the Fifth Symposium on Software Reusability (SSR'99), May 21-23, 1999, Los Angeles, CA, pp. 17-26.

 

"Bi-directional Analysis for Certification of Safety-Critical Software," with Robert Woodhouse, First International Software Assurance Certification Conference (ISACC'99), Feb. 28-March 2, 1999, Washington, D.C.

 

"Safety Analysis of Requirements for a Product Family," with G. Helmer, M. Moseman, D. Statezni, and S. Tockey, Proceedings of the Third IEEE International Conference on Requirements Engineering (ICRE '98), April 6-10, 1998, Colorado Springs, CO, 24-31.

 

"Experiences Using Lightweight Formal Methods for Requirements Modeling," with S. Easterbrook, R. Covington, J. Kelly, Y. Ampo, and D. Hamilton, IEEE Transactions on Software Engineering, 24(1):4-14, January 1998.

 

"Requirements Analysis Using Forward and Backward Search" with R. Woodhouse, Annals of Software Engineering, 3:459-475, 1997.

 

"Reuse of a Formal Model for Requirements Validation," Proceedings of the Fourth NASA Langley Formal Methods Workshop, 10-12 September, 1997, Hampton, VA, 75-85.

 

"Targeting Safety-Related Errors During Software Requirements Analysis," The Journal of Systems and Software, 34:223-230, September 1996.

 

 

DIMITRIS MARGARITIS, Assistant Professor of Computer Science

 

B.S. 1992, Physics, University of Athens

M.S. 1995, Computer Science, State University of New York at Stony Brook

Ph.D. 2002, Computer Science, Carnegie Mellon University

 

Major Interests:

Probabilistic modeling, methods for managing and reasoning with uncertainty/indeterminacy in Artificial Intelligence and other applications, Bayesian networks, Markov networks, data mining, machine learning, cross-disciplinary applications of these in bioinformatics, econometrics, very large databases and other domains.

 

Current Research:

Dr. Margaritis’ recent research is on new algorithms for learning the structure of Bayesian networks and applying them to real-world application domains where modeling uncertainty might be beneficial.  For example, it turns out that approximate query answering in very large databases can be done quickly using a sufficiently complex model of the database---in this case a Bayesian network.

 

He would also like to explore capturing and modeling information about influences by statistical means in bioinformatics domains such as protein structure prediction.

 

Dr. Margaritis’ long-term vision is to develop algorithms and representations that help researchers learn something about their research domain by presenting them with an automatically derived model of it. The benefit of this is to help them focus attention to the relevant portions and possibly provide them with insights that are difficult to produce otherwise.

 

Representative Publications:

D. Margaritis and S. Thrun. A Bayesian Multiresolution Independence Test for Continuous Variable. Uncertainty in Artificial Intelligence (UAI), August 2001.

 

D. Margaritis, C. Faloutsos, and S. Thrun. NetCube: A Scalable Tool for Fast Data Mining and Compression. International Conference on Very Large Databases (VLDB), September 2001.

 

D. Margaritis and S. Thrun. Bayesian Network Induction via Local Neighborhoods.  Neural Information Processing Systems (NIPS), December 1999.

 

D. Moghaddam, H. Biermann and D. Margaritis. Regions-of-Interest and Spatial Layout for Content-Based Image Retrieval.  Journal of Multimedia Tools and Applications, Kluwer Academic Publishers, Vol. 14, No. 3, July 2001.

 

D. Moghaddam, H. Biermann, D. Margaritis. Image Retrieval with Local and Spatial Queries. International Conference on Image Processing (ICIP), Vancouver, Canada, September 2000.

 

D. Margaritis and S. Thrun. Learning to Locate and Object in 3D Space from a Sequence of Camera Images. International Conference in Machine Learning (ICML), July 1998.

 

S. Waldherr, S. Thrun, R. Romero, and D. Margaritis. Template-Based Recognition of Pose and Motion Gestures on a Mobile Robot. National Conference on Artificial Intelligence (AAAI), July 1998.

 

T. C. Chieuh, D. Margaritis, and S. Varadarajan. Design, Implementation and Evaluation of a Parallel Image Shape Indexer. Visual Information Systems (Visual ‘p7), 1997.

 

D. Margaritis and S. Skiena. Reconstructing Strings from Substrings in Rounds. IEEE Foundations of Computer Science (FOCS), 1995.

 

 

LES MILLER, Professor of Computer Science

 

        B.A. 1967, Mathematics, University of South Dakota

        M.A. 1974, Mathematics, University of South Dakota

        Ph.D. 1980, Computer Science, Southern Methodist University

 

Major Interests:

Object oriented databases, Organizational decision support systems, Multi-agent systems, Knowledge management systems, Data warehouses, Computational Biology.

 

Current Research:

We are currently looking at multi-agent systems to provide the infrastructure for integrating heterogeneous data sources. In addition to the agent systems, we have developed an object-oriented data warehouse to serve as part of the integration infrastructure.  We have also been looking at tools for generating and populating data warehouse designs.  We are also concerned with applying database and machine learning techniques to problems in computational biology.

 

Representative Publications:

"Populating a data warehouse with mobile agents," Dandu, R., L. Miller, S. Nilakanta, and V. Honavar. (1999). To appear in The Tenth International Conference of the Information Resources Management Association.

 

"Distributed Knowledge Networks," Honavar, V., L.L. Miller, and J. Wong. (1998). IEEE Information Technology Conference, pp. 87-90.

 

"Object-oriented data warehouse for information fusion from heterogeneous distributed data and knowledge sources," Miller, L.L., V. Honavar, J. Wong, and S. Nilakanta. (1998).  IEEE Information Technology Conference, pp. 27-31.

 

"Data Warehouse Modeler: A Case Tool for Warehouse Design," Miller, L.L., & Nilakanta, S. (1998). Hawaiian International Conference on Systems Science, pp. 42-48.

 

"Extending the Object-Relational Interface to Support an Extensible View System for Multidatabase Integration and Interoperation," Miller, L.L., Yen, D., Sirjani, A., & Tenner, J. (1998). International Journal of Computer Systems Science and Engineering. 13:4, pp. 227-240.

 

"A Dynamic Approach for Finding the Join Sequence in a Universal Relation Interface," Miller, L.L., & Owrang, M. M.  (1998). To appear in the Journal of Integrated Computer-Aided Engineering, 4:310-318.

 

"Warehousing Structured and Unstructured Data for Data Mining." Miller, L.L., Honavar, V., & Barta, T. (1997).  ASIS '97, pp. 215-224.

 

 

ANDREW S. MINER, Assistant Professor of Computer Science

 

        B.S. 1993, Physics and Computer Science, Randolph-Macon College

        M.S. 1995, Computer Science, College of William and Mary

        Ph.D. 2000, Computer Science, College of William and Mary

 

Major Interests:

Performance reliability and logical analysis of systems, Petri nets and stochastic modeling; state space generation techniques, binary and multi-valued decision diagrams; compositional approaches, distributed algorithms for solution techniques.

 

Current Research:

Technology advancements yield increasingly complex systems. Dr. Miner's  research focuses on techniques for analyzing such systems, especially during their design stage. In particular, he considers techniques that use some high-level modeling formalism, such as stochastic Petri nets, to capture the desired behavior of the system. Using a well-defined mathematical formalism allows certain types of logical analysis, in which all the possible states of the model are examined, or performance or reliability analysis, in which the underlying stochastic process of the model (usually a Markov chain) is considered. Logical analysis is typically used to verify the correctness or robustness of a system against a set of criteria, and is especially applicable to software and hardware verification. Performance and reliability analyses are instead used to determine how well a system performs or the expected lifetime of a system, and are applied to a variety of systems, including communications systems, web servers, distributed systems, and mission-critical systems.

 

The main difficulty in these types of analyses is that even a simple model can contain an extremely large number of possible states, leading to excessive storage and CPU requirements. Indeed, the number of reachable states of a model usually determines the tractability of its analysis. Dr. Miner's work addresses this problem by developing techniques that can handle a large number of states.

 

Representative Publications:

A.S. Miner, G. Ciardo, and S. Donatelli.  "Using the exact state space of a large structured Markov model to computer approximate stationary measures." In Proc. ACM SIGMETRICS 2000, International Conference on Measurement and Modeling of Computer Systems, Santa Clara, CA, pages 207-216.  June 2000.

 

G. Ciardo and A.S. Miner, "Structural approaches for SPN analysis."  High Performance Computing Symposium, Washington, DC, USA, April 2000, pp. 345-356.

 

 

G. Ciardo and A.S. Miner.  "A data structure for the efficient Kronecker solution of GSPN's."  In P. Buchholz, editor, Proc. 8th International Workshop on Petri Nets and Performance Models (PNPM'99), Zaragoza, Spain, IEEE Computer Society Press, pages 22-31, September 1999.

 

A.S. Miner and G. Ciardo.  "Efficient reachability set generation and storage using decision diagrams."  In H. Kleijn and S. Donatelli, editors, Application and Theory of Petri Nets 1999, LNCS 1639 (Proc. 20th International Conference on Applications and Theory of Petri Nets, Williamsburg, VA, USA), pages 6-25.  June 1999. Springer-Verlag.

 

G. Ciardo and A.S. Miner. "Storage alternatives for large structured state spaces."  In R. Marie, B. Plateau, M. Calzarossa, and G. Rubino, editors, Proc. 9th International Conference on Modelling Techniques and Tools for Computer Performance Evaluation, LNCS 1245, pages 44-57, St. Malo, France, June 1997. Springer-Verlag.

 

 

GURPUR PRABHU, Associate Professor of Computer Science

 

        B.Tech. 1975, Electrical Engineering, IIT, Madras, India

        M.Tech. 1978, Computer Science, IIT, Kanpur, India

        Ph.D. 1983, Computer Science, Washington State University, Pullman

 

Major Interests:

Parallel processing, computer architecture, business process modeling and analysis.

 

Current Research:

Dr. Prabhu's current research focuses on performance issues of parallel programs and methods for business transformation.

 

Representative Publications:

"Programming is Writing: Why Programs must be Carefully Evaluated," Journal of Mathematics and Computer Education, 32:3, Fall 1998, pp. 284-295 (with Gary Leavens, Albert Baker, Vasant Honavar, and Steve LaValle).

 

"Parallelizing a very high resolution climate model using clusters of workstations with PVM and performance and load balance analyses," (with Hao Wang and Eugene Takle), Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications, 1998, pp. 1762-1765, CSREA Press.

 

"Distribution-Independent Hierarchical Algorithms for the N-body problem," Journal of Supercomputing, 12, 1998, pp. 303-323 (with Srinivas Aluru, John Gustafson, and Fatih Sevilgen).

 

"A Framework for Business Transformation," Journal of Microcomputer Applications, 17:1, 1998, pp. 1-7 (with Sree Nilakanta and Ashok Subramanian).

 

"Enterprise Integration: Art or Science?"  Summer Conference of the Society for Enterprise Engineering, June 1995.

 

"Truly Distribution-Independent Algorithms for the N-Body Problem," Prabhu, G., Aluru, S., & Gustafson, J.  Supercomputing '94, pp. 420-428.

 

"A Methodology for Business Transformation," Prabhu, G., Nilakanta, S., & Subramanian, A.  (1994). Proceedings of the Third International Conference on Systems Integration, Brazil, pp. 403-411.

 

"The Use of Microcontrollers in Mechatronics Education," Prabhu, G., & Wright, C. (1994). Proceedings of the Workshop on Mechatronics Education, Stanford, pp. 72-77.

 

LU RUAN, Assistant Professor of Computer Science

 

                B.E. 1996, Computer Science, Tsinghua University, China

                M.S. 1999, Computer Science, University of Minnesota - Twin Cities

                Ph.D. 2001, Computer Science, University of Minnesota - Twin Cities

 

Major Interests:

Computer Networking (Traffic Engineering, Quality of Service, WDM Networks, Fault Tolerance), Approximation Algorithms.

 

Current Research:

IP over WDM is being envisioned as the architecture for the next generation Internet. In this architecture, high-speed IP routers are interconnected by intelligent optical core networks.  Survivability in these networks is essential since the networks carry a high volume of traffic and a single link/node failure will cause tremendous service loss.  Dr. Ruan’s current

research focuses on the design of fast and capacity efficient protection/restoration schemes in both the IP and WDM layer to recover from link/node failures.  In addition, she is interested in developing techniques to integrate the recovery schemes in the two layers seamlessly and efficiently.  Three important objectives are to be achieved: (1) Protection bandwidth should be efficiently shared by traffic within the same layer as well as among the IP and WDM layers. (2) Recovery schemes should be decentralized to assure scalability. (3) Differentiated reliability (or quality of protection) is provided to client connections.

 

Representative Publications:

X. Jia, X. Hu, L. Ruan and J. Sun, "Multicast Routing, Load Balancing and wavelength Assignment on Tree of Rings,” IEEE Communications Letters, 6(2):79-81, Feb 2002.

 

L. Ruan, D-Z. Du, X. Hu, X. Jia, D. Li and Z. Sun, "Converter Placement Supporting Broadcast in WDM Optical Networks,” IEEE Transactions on Computers, 50(7):750-758, July 2001.

 

B. Lu and L. Ruan, "Polynomial Time Approximation Scheme for the Rectilinear Steiner Arborescence Problem", Journal of Combinatorial Optimization, 4(3):357-363, Sept 2000.

 

D. Li, X. Du, X. Hu, L. Ruan and X. Jia, "Minimizing Number of Wavelengths in Multicast Routing Trees in WDM Networks", Networks, 35(4):260-265, July 2000.

 

L. Ruan and D-Z. Du (eds.), Optical Networks-Recent Advances, Kluwer Academic Publishers, 2001.

 

L. Ruan, D-Z. Du, X. Hu, X. Jia, D. Li, "Approximations for Color-Covering Problems,” Proceedings of the International Congress of Chinese Mathematicians, pp. 203 -207, 2000.

 

GIORA SLUTZKI, Professor of Computer Science

 

        B.S. 1970, Mathematics & Physics, Hebrew University of Jerusalem, Israel

        M.S. 1973, Computer Science, Weizmann Institute of Science, Rehovot, Israel

        Ph.D. 1977, Computer Science, Tel-Aviv University, Tel-Aviv, Israel

 

Major Interests:

Algorithms and Complexity, Game Theory and Computational Economics, Formal Languages, Automata Theory, Logic.

 

Current Research:

Dr. Slutzki is currently working on complexity of some problems in abstract algebra and graph theory. He also works on parametric string alignment, problems in pursuit-evasion in polygons, and problems related to agreement and common knowledge.

 

Representative Publications:

"A Complete Pursuit-Evasion Algorithm for Two Pursuers Using Beam Detection" (with B. Simov and S. LaValle). 2002 IEEE International Conference on Robotics and Automation (ICRA '02), May 2002, Washington, DC, USA. Proceedings.

 

"Computational Complexity of Some Problems Involving Congruences on Algebras" (with C. Bergman). Theoretical Computer Science, 270 (2002), pp. 591-608. Extended Abstract appeared in LICS '00.

 

"Lower Bounds for Parametric Sequence Comparison" (with D. Fernandez-Baca and T. Seppalainen). Special Issue of Discrete Applied Mathematics (DAM), 118(3)(2002), pp. 181-199. Extended Abstract appeared in SPIRE '99.

 

"Computational Complexity of Generators and Nongenerators in Algebra" (with C. Bergman). To appear in International Journal of Algebra and Computation.

 

"A Duality Theory for Bilattices" (with B. Mobasher, D. Pigozzi, and G. Voutsadakis). Algebra Universalis, 43 (2000), pp. 109-125.

 

"An Algorithm for Searching a Polygonal Region with a Flashlight" (with B. Simov and S. LaValle). 16-th ACM Symposium on Computational Geometry (SoCG '00), June 2000, Hong Kong. Proceedings, pp. 260-269. To appear in a Special Issue of the International Journal of Computational Geometry and Applications (IJCGA).

 

"Parametric multiple sequence alignment and phylogeny construction" (with D. Fernandez-Baca and T. Seppalainen). 11-th Annual Symposium on Combinatorial Pattern Matching (CPM '00), June 2000, Montreal, Canada. Springer Verlag, LNCS 1848, pp. 69-83. To appear in Journal of Discrete Algorithms.

 

"Complexity of Some Problems Concerning Varieties and Quasi-Varieties of Algebras" (with C. Bergman). SIAM Journal on Computing, 30 (2) (2000), pp. 359-382. Extended Abstract appeared in 16-th STACS (1999).

 

"Computational Complexity of Term-Equivalence" (with C. Bergman and D. Juedes). International Journal of Algebra and Computation 9 (1) (1999), pp. 113-128.

 

"Multi-valued Logic Programming Semantics: An Algebraic Approach" (with B. Mobasher and D. Pigozzi). Theoretical Computer Science, 171 (1997), pp. 77-109.

 

"Optimal Parametric Search on Graphs of Bounded Tree-width" (with D. Fernandez-Baca). Journal of Algorithms 22 (1997), pp. 212-240.

 

"A Hierarchy of Deterministic Top-down Tree Transformations" (with S. Vagvolgyi). Mathematical Systems Theory 29 (1996), pp. 169-188.

 

"Using Sparsification for Parametric Minimum Spanning Tree Problems" (with D. Fernandez-Baca and D. Eppstein). Special SWAT issue of the Nordic Journal of Computing, 3 (4)(Winter 1996), pp. 352-366.

 

 

WALLAPAK TAVANAPONG, Assistant Professor of Computer Science

 

B.S. 1992, Computer Science, Thammasat University, Thailand

M.S. 1995, Computer Science, University of Central Florida

Ph.D. 1999, Computer Science, University of Central Florida

 

Major Interests:

Distributed Multimedia Systems, Multimedia and Communications, Multimedia Databases, Parallel and Distributed Databases, Web Performance.

 

Current Research:

The information superhighway will consist of a collection of heterogeneous high-speed networks, offering a wide variety of services. Due to these infrastructures, affordable high performance computers and peripherals, and the World Wide Web, multimedia data such as videos and audio will greatly increase its presence and significance far beyond those seen on the Internet today.  Designing efficient techniques to retrieve and deliver multimedia data to remote users is very challenging due to the unique traits of multimedia data.  First, video and audio data demand both large storage space and high communication bandwidth.  Second, the data must be presented in a timely manner without interruptions or large jitters.  Lastly, the rich and complex semantics inherent in multimedia data make it necessary to design novel search techniques.

 

Dr. Tavanapong's research addresses three critical aspects of multimedia computing: distributed multimedia caching and delivery techniques, multimedia server design, and multimedia databases.  Her research in distributed multimedia caching and delivery strategies focuses on designing innovative distributed and collaborative strategies for caching multimedia data along distributed systems to reduce service delays and wide-area-network bandwidth consumption.  Her research contribution in media server design involves novel algorithms for a high performance media server or a cluster of workstations to support a large number of concurrent users efficiently.  Lastly, her work in multimedia databases concentrates on content-based search for desire video segments from a large video database.

 

Grants

Strategies for Caching Information on Distributed Systems. NSF Career Award CCR-0092914, PI, 2001, $253,930.

 

Representative Publications:

Design and Implementation of a Video Browsing System for the Internet.  Tavanapong, W. and Hua, K.A.  To appear in Journal of Software Practice & Experience, 2001.

 

A Noise-Reduction Approach to Scene Segmentation for Large Video Databases.  Tavanapong, W. and Zhou, J.  To appear in Proc. of IEEE Int'l. Conf. on Information Technology: Coding and Computing (ITCC), 2001 (Invited paper).

 

A Characteristics-Based Bandwidth Reduction Technique for Pre-recorded Videos.  W. Tavanapong and S. Krishnamohan.  In Proc of IEEE Int'l Conf. on Multimedia and Expo, pages 1751-1754, New York City, NY, July 2000.

 

2PSM: An Efficient Framework for Searching Video Information in a Limited-Bandwidth Environment.  Hua, K.A., Tavanapong, W. and, Wang, J.Z. ACM Multimedia Systems, 7(5), 396-408, September, 1999.

 

Performance of Load Balancing Techniques for Join Operations in Shared-Nothing Database Management Systems.  Hua, K.A., Tavanapong, W., and Lo, Y.  Journal of Parallel and Distributed Computing, 56, 17-46, 1999.

 

Reducing Web Browsing Delay using Profiled-Based Prefetching. Tavanapong, W., Hua, K.A., and Sheu, S. In Proc. of WebNet 98 - World Conf. of the WWW, Internet & Intranet, pp. 879-884, Orlando, FL, November, 1998.

 

A Framework for Supporting Previewing and VCR Operations in a Low Bandwidth Environment. Tavanapong, W., Hua, K.A., and Wang, J.Z. In Proc. of ACM Multimedia '97, pp. 303-312, Seattle, WA, November, 1997.

 

Pre-admission control for Movie-on-Demand. Tavanapong, W., Hua, K.A., and Sheu, S. In Proc. of Int'l Conf. on Multimedia Information Systems, pp. 151-158, Schaumburg, IL, April, 1997.

 

Dynamic Grouping: An Efficient Buffer Management Scheme for Video-on-Demand Servers.  Sheu, S., Hua, K.A., and Tavanapong, W. In Proc. of Int'l Conf. on Multimedia Information Systems, pp. 135-142, Schaumburg, IL, April, 1997.

 

Chaining: A Generalized Batching Technique for Video-on-Demand Systems. Sheu, S., Hua, K.A., and Tavanapong, W. In Proc. of IEEE Int'l Conf. On Multimedia Computing and Systems, pp. 110-117, Ottawa, Canada, June 1997.

 

Scheduling Queries for Parallel Execution on Multicomputer Database Management Systems.  Lo, Y., Hua, K.A., and Tavanapong, W. In Proc. of Int'l Conf. on Database and Expert Systems Applications, Zurich, Switzerland, 1996.

 

A Performance Evaluation of Load Balancing Techniques for Join Operations on Multicomputer Database Systems.  Hua, K.A., Tavanapong, W., and Young H.C. In Proc. of IEEE Int'l Conf. on Data Engineering, pp. 44-51, Taipei, Taiwan, 1995.

 

 

JIN TIAN, Assistant Professor of Computer Science

 

B.S. 1992, Physics, Tsinghua University, Beijing

M.S. 1997, Physics and Astronomy, UCLA

Ph.D. 2002, Computer Science, UCLA

 

Major Interests:

Bayesian networks, probabilistic reasoning, causal reasoning and learning.

 

Current Research:

I am interested in various topics on Bayesian networks. My recent research is focused on causal reasoning and learning in the framework of causal Bayesian networks. Some topics that I am working on include: learning causal structures from data, inferring causal effects from a combination of data and qualitative causal assumptions, identifying linear causal relationships in structural equation models. The long term goal is to provide theoretical foundations that will facilitate building intelligent systems that can learn about and reason with causes and effects.

 

Representative Publications:

J. Tian and J. Pearl, A general identification condition for causal effects, in Proceedings of the National Conference on Artificial Intelligence (AAAI), 2002.

 

J. Tian and J. Pearl, On the Testable Implications of Causal Models with Hidden Variables, in Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2002.

 

J. Tian and J. Pearl, Causal Discovery from Changes, in Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2001.

 

J. Tian and J. Pearl, Probabilities of causation: Bounds and identification, in Annals of Mathematics and Artificial Intelligence 28: 287-313. 2000.

 

J. Tian, A branch-and-bound algorithm for MDL learning Bayesian networks, in Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2000.

 

JOHNNY S. K. WONG, Professor of Computer Science

 

        B.S. 1977, Mathematics & Computer Science, The University of Hong Kong

        M.S. 1982, Mathematics, The University of Sydney, NSW, Australia

        Ph.D. 1987, Computer Science, The University of Sydney, NSW, Australia

 

Major Interests:

Distributed Computing Environment (DCE), Distributed Operating Systems, Communication Protocols, Object-Oriented Systems and Databases, Common Object Request Broker Architecture (CORBA), Hypermedia Systems, Multimedia Information Systems, Web Caching, Intrusion Detection, Information Assurance.

 

Current Research:

Dr. Wong's research interests include design and implementation issues in operating systems, distributed systems and multimedia communications. Current activities center around hypermedia, distributed multi-media database systems, and intelligent mobile agents, intrusion detection and countermeasures, distributed computing environment (DCE), and Common Object Request Broker Architecture (CORBA), Web Caching, Information Assurance.

 

The current research projects are funded by the Department of Defense (DoD) on Intrusion Detection and Countermeasures (with Drs. Miller and Honavar), by the Mayo Foundation on Database Generating and X-Ray Displaying using The World Wide Web, and by NSF on the development of courseware modules on Information Assurance (IA).

 

Representative Publications:

"SMART Mobile Agent Facility'', Wong, J, Helmer, G., Naganathan, V., Polavarapu, S. Honavar, V. and Miller, L., The Journal of Systems and Software, accepted.

 

"Anomalous intrusion detection system for hostile Java Applets", G. Helmer, Wong, J. and Madaka, S., The Journal of Systems and Software, 55:273-286, January 2001.

 

"Achieving Non-repudiation of Web-based Transactions", Kalla, M., Wong, J., Albert, S. and Mikler, A., The Journal of Systems and Software, 48(3):165-175, November 1999.

 

"Intelligent Mobile Agents in Large Distributed Autonomous Coopertaive Systems", Wong, J. and Mikler, A.(1999), The Journal of Systems and Software, 47(2):75-87, July 1999.

 

"A Framework for a World Wide Web Based Data Mining System," R. Nayar, Wong, J., and Mikler, A., Journal of Network and Computer Applications, 21:163-185, July 1998.

 

"A Multimedia Presentation Toolkit for the World Wide Web", Wong, J., Rao, S., & Ramaiah, N., Software: Practice and Experience, 27(4):425-446, April 1997.

 

"Remote Access to Multimedia Databases: An object-Oriented Approach", Wong, J., & Parthasarathy, D., Software: Practice & Experience, 26(6):677-704, June 1996.

 

"Design and Implementation of Heterogeneous Distributed Multimedia System using Mosaic GSQL," Wong, J., Magavi, S., & Bodla, P., Software: Practice & Experience, 25(11):1223-1242, November 1995.

 

"Design and Implementation of National Engineering Education Delivery System  (NEEDS)," Wong, J., Schmitz, D., & Nelson, R. Software: Practice & Experience, 24(11):1051-1076, November 1994.

 

"Remote Database Access in Distributed Computing Environment," Wong, J., Marshall, W., & Goodman, R. Software: Practice & Experience, 24(4):421-434, April 1994.

 

"Detecting Unsafe Error Recovery Schedules," Wong, J., & Lutz, R. IEEE Transactions on Software Engineering, pp. 749-760, August 1992.

 

"An Efficient Process Migration Algorithm in Distributed Systems," Wong, J., & Suen, T. IEEE Transactions on Parallel and Distributed Systems, pp. 488-499, July 1992.

Adjunct Faculty

 

SRINIVAS ALURU, Assistant Professor (Major Appointment in Computer Engineering)

 

B. Tech 1989, Computer Science & Engineering., Indian Institute of Technology, Madras, India

M.S. 1991,  Computer Science, Iowa State University

Ph.D. 1994, Computer Science, Iowa State University

 

Major Interests:

Parallel models, Algorithms and Applications, Bioinformatics and Computational Biology, and Scientific Computing.

Internet: aluru@iastate.edu

 

Current Research:

Dr. Aluru is interested in developing algorithms and software systems for important applications on high-performance parallel computers and clusters. The primary application areas of target are computational biology and hierarchical methods in scientific computing. In computational biology, his research is currently focused on developing parallel data structures for

sequence data, developing intellegent database schemes for sequence data, parallel algorithms and software for gene identification using EST data and problems related to structure data. His scientific computing research is focused on developing distribution-independent sequential and parallel algorithms based on the hierarchical fast multipole method, for solving problems in computational electromagnetics. His research is funded by NSF, ARO and DOE.

 

Representative Publications:

N. Futamura, S. Aluru and D. Ranjan, "Efficient parallel algorithms for solvent accessible surface area of proteins,” IEEE Transactions on Parallel and Distributed Systems}, to appear.

 

B. Hariharan and S. Aluru, "Efficient parallel algorithms and software for compressed octrees with application to hierarchical methods,” Proc. 8th IEEE International Conference on High Performance Computing, Spring Verlag Lecture Notes in Computer Science, pp. 125-136, 2001.

 

I. Al-furaih, S. Aluru, S. Goil and S. Ranka, "Parallel construction of multidimensional binary search trees," IEEE Transactions on Parallel and Distributed Systems, 11(2):136-148, 2000.

 

F. Sevilgen, S. Aluru and N. Futamura, "A provably optimal, distribution-independent, parallel fast multipole method," Proc. 14^th IEEE International Parallel and Distributed Processing Symposium, pp. 77-84, 2000.

 

S. Aluru and F. Sevilgen, "Dynamic compressed hyperoctrees with application to the N-body problem,” Proc. 19^th International Conference on Foundations of Software Technology and Theoretical Computer Science, Springer Verlag Lecture Notes in Computer Science, 1738:21-33, 1999.

 

F. Sevilgen and S. Aluru, "A unifying data structure for hierarchical methods,” Proc. IEEE/ACM Supercomputing Conference, http://www.sc99.org., 1999.

 

S. Aluru, G.M. Prabhu, J. Gustafson and F. Sevilgen, "Distribution-independent hierarchical algorithms for the N-body problem," Journal of Supercomputing, 12:303-323, 1998.

 

S. Aluru, "Lagged Fibonacci random number generators for distributed memory parallel computers," Journal of Parallel and Distributed Computing, 45(1):1-12, 1997.

 

I. Al-furaih, S. Aluru, S. Goil and S. Ranka, "Practical algorithms for selection on coarse-grained parallel computers," IEEE Transactions on Parallel and Distributed Systems, 8(8):313-324, 1997.

 

 

 

JOHN PETER BOYSEN, Senior Systems Analyst, Academic Information Technologies, and Adjunct Assistant Professor, Computer Science

 

B.S. 1969, Physics, University of Florida

M.S. 1976, Computer Science, Iowa State University

Ph.D. 1979, Computer Science, Iowa State University

 

Major Interests:

Instructional use of computers, programming languages, object-oriented programming.

 

Current Research:

Current research involves the development of instructional applications for the Internet.  Projects include Java Instructional simulations in meterology and mathematics and the Ecademy system which is a Java-based Instructional Management System used in the creation and delivery of Web-based instructional classes.

 

Representative Publications:

“ClassNet: Managing the Virtual Classroom” Boysen, P., & Van Gorp, M., (1997). International Journal of Educational Telecommunications, 3(2/3):279-292.

 

"Interactive Computer Graphics in the Study of Human Body Planar Motion Under Free Fall Conditions,” Boysen, P., Francis, P., & Thomas, R.  (1997).  Journal of Biomechanics, 10:783-788.

 

"Reducing Object Storage Requirements in a Multi-user Environment,” Boysen, P., & Shah, P., Software-Practice and Experience, 23(3):255-241, March 1993.

 

 “Using Simulations to Fill Instructional Gaps,” Boysen, P., & Thomas, R.  EDU, 40:8-11, Winter 1986.

 

"A Taxonomy for the Instructional Use of Computers,” Boysen, P., & Thomas, R., AEDS Monitor, 22(11):12, May/June 1984.

 

"An Evaluation of the Instructional Effectiveness of a Computer Lesson in Biomechanics,” Boysen, P., & Francis, P. (1982).  Research Quarterly for Exercise and Sport, 53(3):232-235.

 

"Them Bones: The Use of Computer-Assisted Instructional Techniques in the Teaching of Human Anatomy,” Boysen, P., Francis, P., Ciskey, M., & Seastrand, P. The Computing Teacher, 9(3):11-16, November 1981.

 

"Measuring Computer Program Comprehension,” Boysen, P., & Keller, R.  ACM SIGCSE Bulletin, 12:92-102, February 1980.

 

 

MORRIS CHANG, Associate Professor (Major Appointment in Computer Engineering)

 

Ph.D. 1993, Computer Engineering, North Carolina State University
M.S.E.E. 1986, Electrical Engineering, North Carolina State University
B.S.E.E. 1983, Electrical Engineering, Tatung Institute of Technology

 

Major Interest:

High performance object-oriented systems, Computer architecture, Hardware description languages, Internet architecture, Wireless networks.

 

Current Research:

Dr. Chang is interested in studying and improving the performance of Java systems for server and embedded applications. For the server applications, his research is focused on developing strategies for memory management in multithreaded multiprocessors environment. For the emdedded applications, garbage collection algorithms that lead to low-power consumption and small memory footprint are studied. His current research interests also include: distributed object systems,

Hardware description languages and wireless networks. His current research projects are funded by the National Science Foundation.

 

Selected Publications:

C. D. Lo, W. Srisa-an and J. M. Chang, "A Study of Page Replacement Performance in Garbage Collection Heap", The Journal of Systems and Software, 58:235-245, Elsevier Science, 2001.

 

G. Koutsogiannakis, and J. M. Chang, "Java Distributed Object Models: An Alternative to Corba?" , IEEE IT Professional, 4(3):41-47,  June 2002.

 

W. Srisa-an, C. D. Lo, and J. M. Chang "Performance Enhancements to the Active Memory System ", Proceedings of IEEE International Conference on Computer Design, (ICCD 2002), Freiburg, Germany, September 16-18, 2002, pp. 249-256.

 

 

 

CAROLINA CRUZ-NEIRA, Associate Professor of Industrial & Manufacturing Systems Engineering and Associate Director of the Virtual Reality Applications Center (Major Appointment in IMSE)

 

Ph.D. 1995, Electrical Engineering & Computer Science, Electronic Visualization Laboratory, University of Illinois at Chicago
M.S. 1991, Electrical Engineering & Computer Science, Electronic Visualization Laboratory, University of Illinois at Chicago
B.S. 1987, Cum Laude, Systems Engineerng. Universidad Metropolitana de Caracas, Venezuela

Areas of Interest:
Virtual reality, high-speed networks, software engineering and interactive computer graphics.

Current Research:
Her research focuses on the development of tools, such as distributed software , engineering, and artistic virtual reality applications.

Selected Publications (* denotes students)
Bierbaum, A*, Just, C*., Hartling, P*., and Cruz-Neira, C., "VR Juggler: A vVirtual Platform for Virtual Reality Application Development, IEEE VR 2000 Conference. Yokohama, Japan, March 2001

Cruz-Neira, C., Lindahl, G.  "A Voyage into Virtual Reality: Networking Our VR Lab to Iowa Middle Schools and High Schools."  IEEE Computer Graphics and Applications. March 2000, pp. 16-19.

Cruz-Neira, C., and Lutz, R.  "Using Virtual Environments for Certification."  IEEE Software, July/August 1999. pp.26-30.

Nelson, L.*, Cook, D., and Cruz-Neira, C. "XGobi vs. the C2: Results of an Experiment Comparing Data Visualization in a 3-D Immersive Virtual Reality Environment with a 2-D Workstation Display."  Journal of Computational Statistics. Special Issue on the Use of Interactive Graphics. January 1999. pp.441-450.

RICKY A. KENDALL, Adjunct Associate Professor of Computer Science, Scientist Ames Laboratory

 

B.S.  1983, Chemistry, Indiana State University

Ph.D.  1988, Theoretical and Computational Chemistry, University of Utah

 

Major Interests:

The encompassing theme of Dr. Kendall's research is to make the development of high performance applications on parallel and distributed computing platforms more facile.  His interests include asynchronous communications software, parallel I/O, application domain specific APIs, e.g., targeted software engineering, and general application of parallel and distributed algorithms.

 

Current Research:

Currently Dr. Kendall and his students are focused on four main projects that include the development of a generalized, portable SHMEM library that provides asynchronous one-sided communication protocols (e.g., put and get operations) to applications across a wide spectrum of computational resources.  Another area is the development of a parallel I/O mechanisms that are also asynchronous on cluster based systems so that the disk facilities of cluster computers can meet the performance requirements of high performance applications.  The third focus area is the development of a generic compression library that puts state-of-the-art compression algorithms behind a user friendly API for scientific application developers.  It will provide a means of addressing sparsity in many application domains.  The fourth area is utilizing mixed mode programming models (thread based algorithms mixed with either message passing or distributed shared memory) to address the architectural designs of emerging clusters and large MPP supercomputers.

 

Representative Publications:

K. Parzyszek, J. Nieplocha and R. A. Kendall, "A Generalized Portable SHMEM Library for High Performance Computing", Proceedings of the IASTED Parallel and Distributed Computing and Systems 2000, Las Vegas, Nevada, November 2000, (M. Guizani and X. Shen, Eds.), pp. 401-406. IASTED, Calgary (2000).

 

B. Bode, D.M. Halstead, R. Kendall, Z. Lei, and D. Jackson, "The Portable Batch Scheduler and the Maui Scheduler on Linux Clusters," Proceedings from the 4th Annual USENIX Extreme Linux Conference, pp. 217-224 (2000). 

 

R.A. Kendall, E. Apra, D.E. Bernholdt, E.J. Bylaska, M. Dupuis, G.I. Fann, R.J. Harrison, J. Ju, J.A. Nichols, J. Nieplocha, T.P. Straatsma, T.L. Windus, and A.T. Wong, "High Performance Computational Chemistry; an Overview of NWChem a Distributed Parallel Application," Computer Physics Communications, 128:260-283 (2000).

 

I. Foster, J. Nieplocha, and R.A. Kendall "ChemIO: High-Performance Parallel I/O for Computational Chemistry Applications," The International Journal of High Performance Computing Applications, 12:345-363, (1998).

 

R.A. Kendall "High Performance Computing in Chemistry and Massively Parallel Computers: A Simple Transition?," International  Journal of Quantum Chemistry: Quantum Chem. Symposium, 27:769 (1993).

 

SURESH C. KOTHARI, Professor (Major Appointment in Computer Engineering)

 

        B.S. 1970, Mathematics, Poona University, India

        M.S. 1972, Mathematics, Poona University, India

        Ph.D. 1977, Mathematics, Purdue University

 

Major Interests:

Software Engineering, Parallel and Distributed Computing, Computational Science, Bioinformatics.

 

Current Research:

Our research is system oriented. The thrust areas are: (i) knowledge-centric software engineering environment with applications to development of software productivity tools and automatic code generation problems such as automatic parallelization, (ii) distributed computing environments, (iii) computational biology and computational science.

 

Representative Publications:

 

Kalayanaraman, S. Aluru, S. C. Kothari, Space and Time Efficient Parallel Algorithms and Software for EST Clustering, International Parallel and Distributed Processing Symposium (IPDPS), Workshop on High Performance Computational Biology (HiCOMB), April 2002 (to appear).

 

Murali Ravirala, S. Sivasubramanian, S. C. Kothari, Resource-Aware Real-Time CORBA in Multi-server Distributed Environment, International Parallel and Distributed Processing Symposium (IPDPS), Workshop on Parallel and Distributed Real-Time Systems (WPDRTS), April 2002 (to appear).

 

Deng Y., Kothari S., Namara Y., Program Slice Browser, 9th International Workshop on Program Comprehension, Toronto, May 2001.

 

Mitra S., Kothari S., Cho J., Krishnaswamy A., ParAgent: A domain-specific automatic parallelization tool. Proceedings of High Performance Computing Conference, India, December 2000.

 

Tandiary F., Kothari S.C., Dixit A., Anderson W., "Batrun:  Utilizing Idle Workstations for Large-Scale Computing," Kothari, S.C.  IEEE Parallel and Distributed Technology, 4-2:41-49, 1996.

 

Kothari, S., K. Subramanian, and D. Heller, Active message communication package for PVM.  Journal of Parallel and Distributed Processing, pp. 146-52, 1996.

 

SIMANTA MITRA, Adjunct Assistant Professor of Computer Science

 

Ph.D. 1997, Computer Science, Iowa State University, Ames

M.S. 1991, Computer Science , Iowa State University, Ames

B.E. 1987, Computer Science and Technology, Calcutta University, India

 

Major Interests:

Software Engineering, Programming Languages, Compilers, Parallelizing Tools,

And Performance Evaluation of Computer Systems.

 

Representative Work:

 

Patents

U.S. Patent for "An apparatus and method for parallelizing legacy computer codes". Patent No: 6,339,840 issued 01/15/2002.

 

U.S. Patent for "An apparatus and method for parallelizing legacy computer codes". Patent No: 6,243,863 issued 06/05/2001.

 

U.S. Patent for "Method for efficient soft real-time execution of portable byte code computer programs". Patent No: 6,081,665 issued 06/27/2000.

 

Papers

S.C. Kothari, J. Cho, Y. Deng, S. Mitra, et al, Software Tools and Parallel Computing for Numerical Weather Prediction Models, in proceedings of Workshop on parallel and distributed scientific and engineering computing with applications at International Conference on Parallel and Distributed Processing, 2002.

 

Simanta Mitra, Suraj C. Kothari, Jaekyu Cho, and Aravind Krishnamurthy, "ParAgent: A domain-specific automatic parallelization tool", Proceedings of the High Performance Computing Conference, Lecture Notes in Computer Science, 1970:141-149, India, Dec 2000.

 

Yunbo Deng, Suraj Kothari, Lisbeth Meum, Yogy McNamara, Jaekyu Cho, and Simanta Mitra: ParAgent: A software reengineering tool for parallel computing, IASTED 12th International Conference on Parallel and Distributed Computing and Systems, pp. 658-664,Las Vegas, November 2000.

 

Simanta Mitra, "Real-Time extensions fill a need", EE Times, Sep 19, 1999.

 

Kelvin Nilsen, Simanta Mitra, S. Sankaranarayana, and V. Thanuvan, "Asynchronous Java exception handling in a real-time context", In proceedings of the IEEE workshop on programming languages for real-time industrial applications, Madrid, Spain, Dec 1998.

 

Simanta Mitra, Suraj C. Kothari, Parallelization Agent: A new approach to parallelization of legacy codes, Eighth SIAM conference on Parallel Processing for Scientific Computing, March 1997.

 

Suraj C. Kothari, Simanta Mitra, "Analysis of Computational Balance of Parallel Numerical Algorithms", Eighth SIAM conference on Parallel processing for Scientific Computing, March 1997.

 

Suraj C. Kothari, Simanta Mitra, "A scalable 2D parallel sparse solver", Seventh SIAM conference on parallel processing for scientific computing, pp. 424-429, Feb 1995.

 

AKHILESH TYAGI, Associate Professor (Major Appointment in Computer Engineering)

 

        B.Tech. 1981, Electrical Engineering, Birla Institute of Technology & Science, Pilani, India.

        M.Tech. 1983, Computer Engineering, Indian Institute of Technology, New Delhi, India.

        Ph.D. 1988, Computer Science, University of Washington

 

Major Interests:

Computer Architecture, VLSI: Complexity Theory, Low Energy VLSI Design Synthesis.

 

Current Research:

My architecture research interests are in exploiting instruction-level-parallelism (ILP) both with the microarchitecture and compiler. One of the current projects uses branch decoupling to achieve that. In another thread, we are employing reconfigurable caches that can work both as on-chip memory and function units to speed up the processor. We are also exploring microarchitecture level support for computer security. The current focus is on protecting the program pointers through a combination of microarchitecture and compiler actions.

 

In VLSI research, we are developing a function-level model of energy consumption. We are also researching low power VLSI design issues particularly when applied to processor design.

 

Representative Publications:

"A Trace Based Evaluation of Speculative Branch Decoupling", {\it with} A. Nadkarni, {\it Proceedings of IEEE International Conference on Computer Design} (ICCD) 2000.

 

"Dynamic Branch Decoupled Architecture'', {\it with} H.C. Ng and P. Mohapatra, {\it Proceedings of IEEE International Conference on Computer Design (ICCD)}, October 1999.

 

"Hybrid Data/Configuration Caching for Striped FPGAs'', {\it with} D. Deshpande and A. Somani, in {\it Proceedings of

IEEE International Symposium on Field Programmable Custom Computing Machines},  April 1999.

 

"On Reconfiguring Cache for Computing'', {\it with} H-S. Kim and A. Somani, in {\it Proceedings of IEEE International Symposium on Field Programmable Custom Computing Machines}, April 1999.

 

"Configuration Caching Vs Data Caching for Striped FPGAs'', {\it with} D. Deshpande and A. Somani, in {\it Proceedings of ACM International Symposium on FPGAs}, pp 206-214, ACM Press, February 1999.

 

“Reduced Address Bus Switching with Gray PC,” with F. Jensen, in {\it Proceedings of Power Driven Microarchitecture Workshop at International Symposium on Computer Architecture}, ACM Press, June 1998.

 

 “Entropic Limitations on Finite State Machine Switching',” Tyagi, A., IEEE Transactions on VLSI Systems, 5:4, pp. 456-464, December 1997.

 

“Efficient Parallel Algorithms for Optical Computing with the DFT Primitive',” with J. Reif, in {\it Applied Optics}, 36:29, pp. 7327-9340, Optical Society of America, October 1997.

 

 “Branch Decoupled Architectures,” Tyagi, A.  Proceedings of Workshop on Interaction Between Compilers and Computer Architectures at IEEE High Performance Computer Architecture Symposium.  A summary to appear in IEEE TC on Computer Architecture Newsletter, pp. 13-15, June 1997.