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
More details on my research and my list of publications can be found here.
- Research topics I'm currently working on:
- Anomaly detection, time series classification, human-in-the-loop learning, species distribution modeling
- Ph.D. from Carnegie Mellon University, 2004
- M.S. from Carnegie Mellon University, 2001
- B.S. from University of British Columbia, 1997
- Shubhomoy Das, Ph.D., Anomaly detection
- Xinze Guan, Ph.D., Time series classification
- Travis Moore, Ph.D., Computational Sustainability
- Satpreet Singh M.Sc.
- Taj Morton (co-advised with Molly Megraw), M.Sc., Prediction of Gene Transcription Start Sites and Initiation Patterns from DNA Sequence Content, Nov. 2014 (Counsyl)
- Matt Unrath, Honors Thesis, Spring 2014
- Jun Yu, Ph.D., Machine Learning for Improving the Quality of Citizen Science Data, Dec 2013 (eBay Research).
- Michael Anderson, M.Sc., Physical Activity Recognition of Free-Living Data Using Change-Point Detection Algorithms and Hidden Markov Models, June 2013 (Microsoft).
- Yonglei Zheng, M.Sc., Predicting Activity Type and Energy Expenditure from Accelerometer Data, Aug 2012 (Amazon.com).
- Doug Bryant Jr, Ph.D. (Co-advised with Todd Mockler), Algorithms for Massive Biological Data Sets, Fall 2011 (Danforth Institute)
- Paul Wilkins, M. Sc., Application of Conditional Topic Models to Species Distribution Prediction, Fall 2010 (Instructor at Lane Community College)
- Ian Oberst, M.Sc., On Feature Relevance Feedback Methods: Incorporating Labeled User Features, Spring 2010 (Huron Consulting Group)
- Chris Mills-Price, M.Sc., Preference Learning with Structured Prediction: An Empirical Comparison of SVM-Struct and Structured Gradient Boosting, Spring 2010 (Grass Valley)
- Pavan Vatturi, M.Sc., Category Detection using Hierarchical Mean Shift, Fall 2008 (Mentor Graphics)
- Dharin Maniar, M.Sc., Classification of Motion Capture Sequences, Fall 2008 (Nextag)
- Matt Hillier, M.Sc., Visualization and analysis of species distributions, Fall 2007 (Norpac)
- Justin Silva, MSc, Automated enterprise alert monitoring, Fall 2007 (Huron Consulting Group)
- Ryan Neill, REU, Fall 2008-Spring 2009
- Walt Woods, REU, Fall 2007-Spring 2009
- Stephen Perona, REU, Spring 2008-Fall 2008
- Paul Strauss, REU, Winter 2007-Fall 2007
- AAAI 2014 Workshop co-chair
- 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 .
- Co-organizer for the CHI 2012 workshop: End-user interactions with intelligent and autonomous systems
- Program Committee: SDM 2014, AAAI 2013, SDM 2013, KDD 2011, IJCAI 2009, NIPS 2007, KDD 2007, NIPS 2006, KDD 2006, ICML 2006, AAAI 2005
- Reviewer: CHI 2012, AAAI 2011 NECTAR Track, KDD 2012 Workshop proposals, SIGIR 2008 Workshop on Beyond Binary Relevance: Preferences, Diversity, and Set-Level Judgments
- Reviewer (Journals): TKDD, DMKD, TKDE, Journal of Machine Learning, Machine Learning, Statistics in Medicine, Computer methods and Programs in Biomedicine, National Syndromic Surveillance Conference, Water Resource Research