Pressure makes diamonds. Office: B22 Atanasoff Hall Department of Computer Science Iowa State University Ames, IA 50011 Email: yetianc [at] iastate [dot] edu

About Me

I am a 3rd year graduate student at Department of Computer Science, Iowa State University. Currently I am working with Prof. Jin Tian on Artificial Intelligence and Machine Learning. Specifically, I am working on graphical models, Bayesian networks, probabilistic reasoning, causal inference, as well as interdisciplinary applications of these techniques.

Education

• Ph.D. Student in Computer Science, Iowa State University, Aug 2008 ~ current.
• M.S. in Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Aug 2008.
• B.S. in Biological Sciences, Minor Degree in Computer Science, Peking University, July 2003.

Research Interests

• Artificial Intelligence, Intelligent Agents and Multiagent Systems
• Machine Learning and Data Mining
• Semantic Web
• Information Integration and Information Retrieval
• Bioinformatics and Computational Biology

Teaching

• 2011 Summer, 2011 Fall, Teaching Assistant for Com S 363: Introduction to Database Systems
• 2009 Fall, Teaching Assistant for Com S 211: A Conceptual Introduction to Computer Science
• 2009 Spring, Teaching Assistant for Com S 311: Design and Analysis of Algorithms
• 2008 Fall, Teaching and Lab Assistant for Com S 252: Linux Operating System Essentials

Projects

• Spring 2010, Com S 672 Term Project, "Predicting the Cellular Localization Sites of Proteins Using Bayesian Networks and Bayesian Model Averaging", Presentation Slides, Term Paper.


• Fall 2009, Stat 430 course project, "Model-based Approach for Appendiceal Orifice Detection".


• Summer 2009, Graduate Assistant, constructed an on-line Graduate Admission System for the Department of Computer Science.


• Spring 2009, Com S 573 course project, "Learning from Imbalanced, Only Positive and Unlabeled Data", Presentation Slides, Final Report.


• Fall 2008, Com S 572 course project, "Predicting the Cellular Localization Sites of Proteins Using Decision Tree and Neural Network" , Presentation Slides, Final Report.

Presentations

• January 8, 2010 "Testing linear Structural Equation Models".


• March 2, 2010 "Bayesian Network Structure Learning Using Markov Blankets" at ComS 673.


• April 16, 2010 "Controlling the False Discovery Rate of the Association/Causality Structure Learned with the PC Algorithm".


• May 14, 2010 "Improving the Reliability of Casual Discovery from Small Data Sets using Argumentation".


• September 17, 2010 "Learning Bayesian Network: Scale to High Dimensional Data".


• Oct 27, 2010 "Learning Classifiers from Only Positive and Unlabeled Data: Theory and Applications" at ISU 2010 AI Lab Machine Learning Seminar.


• November 19, 2010 "Discovery of Structural Form of Protein Structure Space".

Publications

Coming soon...

Courses

• Spring 2011


• Stat 542 Theory of Probability and Statistics II
• Com S 634 Game Theory
• Fall 2010


• Stat 542 Theory of Probability and Statistics I
• Spring 2010


• Com S 552 Principles of Operating Systems
• Com S 672 Advanced Topics in Computational Models of Learning
• Stat 501 Multivariate Statistical Analysis (Audit)
• Fall 2009


• Com S 586 Computer Network Architectures
• Stat 430 Empirical Methods for Computer Science
• Spring 2009


• Com S 531 Theory of Computation
• Com S 573 Machine Learning
• Fall 2008


• Com S 511 Design and Analysis of Algorithms
• Com S 572 Principles of Artificial Intelligence
• Com S 592x Research Colloquium