Dimitris Margaritis
Assistant Professor
Department of Computer Science
Iowa State University

Education

• PhD in Computer Science, Carnegie-Mellon University, 2003.
• MS in Computer Science, State University of New York at Stony Brook, 1995.
• BS in Physics, University of Athens, Athens, Greece, 1991.

Interests

I am interested in machine learning with special emphasis on learning probabilistic models (Bayesian and Markov networks) from centralized and distributed data, data mining, and very large database modeling and bioinformatics applications.

Publications

Teaching

• ComS 472/572: Principles of Artificial Intelligence, fall 2002, fall 2003, fall 2004, and fall 2005.
• ComS 321: Introduction to Computer Architecture and Machine-Level Programming, fall 2005.
• ComS 352: Introduction to Operating Systems, spring 2004 and spring 2005.
• ComS 490: Independent Study (Steve Tangeman), spring 2004 (local copy).

Current students:

• Facundo Bromberg (PhD).
  • Interests: Efficient Markov network structure induction using conditional independence tests, distributed Markov network structure discovery.
• Haitao Cheng (PhD, jointly advised with Robert Jernigan).
  • Interests: Sequence analysis, Algorithms in Bioinformatics and Computational Biology, Protein structure and interactions. Ongoing research includes Regulatory Protein Molecular Model Construction Protein secondary structure predictions Protein-protein interaction, protein networks.
• Parichey Gandhi (MS).
• Tu-Liang (Alan) Lin (PhD).
• Brian Patterson (PhD).
  • Interests: Machine learning (Bayesian networks, hidden variables, continuous variables), alternative representations of uncertainty, computational complexity theory. Brian has completed a Master's degree on learning hidden variables in Bayesian networks and continues work in this area and that of continuous variables in Bayesian networks. He is funded by a teaching assistantship from the department of Computer Science and is participating in the PFF (Preparing Future Faculty) program at ISU.

Graduated students:

• Kyongryun Lee (MS, graduated May 2005).
  MS Thesis: A Mixture Model of Bayesian Networks. [ PDF ]
• Sandeep Yaramakala (MS, graduated December 2004).
  MS Thesis: Fast Markov Blanket Discovery. [ PDF ]
• Brian Patterson (MS, graduated August 2004).
  MS Thesis: Essential Hidden Variables: An Introduction. [ PDF ]
• Haitao Cheng (MS, jointly advised with Robert Jernigan, graduated August 2004).
  MS Thesis: Identifying Structure Fragments by Sequence Alignments to Predict Protein Secondary Structures.
• Steve Tangeman (undergraduate, ComS 490: Independent Study, Spring 2004). Simulation of Food-gathering in Ant Colonies (local copy).

Contact: