Bio

I received my Ph.D. in Computer Science from Carnegie Mellon University, with Andrew Moore as my advisor. During my time at the AUTON lab at Carnegie Mellon, I learned the art of speeding up data mining algorithms. After finishing my Ph.D., I was a post-doc with Greg Cooper at the Department of Biomedical Informatics at the University of Pittsburgh. While working with Greg, I learned to appreciate Bayesian networks and Bayesian statistics.

General research interests: machine learning, data mining, anomaly detection

Research topics I've worked on:

Syndromic surveillance, Bayesian network structure learning, clustering, reinforcement learning

Research topics I'm currently working on:

Learning by demonstration, bioinformatics, machine learning for graphics

Education

Ph.D. from Carnegie Mellon University, 2004

M.S. from Carnegie Mellon University, 2001

B.S. from University of British Columbia, 1997

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Teaching

• (Spring 2008) CS519: Ecosystem Informatics
• (Spring 2008) CS 331: Introduction to Artificial Intelligence
• (Fall 2007) CS 162: Introduction to Computer Science II
• (Fall 2007) CS 519: Ecosystem Informatics
• (Spring 2007) CS519: Ecosystem Informatics
• (Spring 2007) CS162: Introduction to Computer Science II
• (Winter 2007) CS539: Introduction to Bayesian Networks
• (Fall 2006) CS430: Introduction to Artificial Intelligence
• (Spring 2006) CS162: Introduction to Computer Science II
• (Winter 2006) CS539: Bayesian Network Structure Learning
• (Fall 2005) CS430: Introduction to Artificial Intelligence

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Students

Current:

• Doug Bryant Jr, PhD (Co-advised with Todd Mockler), short-read sequencing
• Dharin Maniar, MSc, Motion capture classification
• Chris Mills-Price, MSc, Integrated Learning
• Ian Oberst, PhD, Explanation and rich user feedback to machine learning algorithms.
• Pavan Vatturi, MSc, Unsupervised learning.
• Paul Wilkins, PhD, Species distribution mapping
• Jun Yu, PhD, Temporal data mining

Undergraduates:

• Ryan Neill
• Walt Woods

Alumni:

• Matt Hillier, MSc, Visualization and analysis of species distributions.
• Justin Silva, MSc, Automated enterprise alert monitoring
• Stephen Perona, REU

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Service

• Guest Editor, Special Issue of the Machine Learning Journal on Event Detection.
• ICML 2007 Volunteer coordinator and local arrangements committee
• Co-chair for the Statistical Research Committee, International Society for Disease Surveillance
• Organizer for the Workshop on Machine Learning Algorithms for Surveillance and Event Detection, ICML 2006 .
• Program Committee: NIPS 2007, KDD 2007, NIPS 2006, KDD 2006, ICML 2006, AAAI 2005
• Reviewer: Journal of Machine Learning, Machine Learning, Statistics in Medicine, Computer methods and Programs in Biomedicine, National Syndromic Surveillance Conference