My name is Matthew Whitehead and I'm a Visiting Assistant Professor at Colorado College in the Math and Computer Science Department. This is my second year at CC and I'm starting to get pretty used to the block plan!
If you're interested in computer science, then feel free to stop by my office (Tutt Science Center 206A) and chat about it. My office hours are from 1:30pm-2:30pm M-Th, but please stop in whenever you see me around.
When I'm not stuck at my computer I can usually be found bicycling, hiking, playing tennis/racquetball/badminton, playing guitar rather poorly, reading, playing video games, baking bread, playing board games (Scrabble, GrabScrab, and chess in particular), writing poetry and fiction of questionable artistic value, watching sports, or generally annoying my wife, Madhuja, and my puppy, Helo.
My main research interests are in machine learning and artificial intelligence. I'm especially interested in applied ML: using machine learning to solve practical problems. I enjoy learning about new problems in all subject areas and figuring out how to use machine learning to solve those problems.
I also enjoy data mining: gathering useful information from large amounts of data. Since the amount of data we produce is drastically increasing, one of the major challenges of the coming years will be to develop programs to organize and make sense of it all.
Some projects I have worked on in the past:
- Using ensembles (groups of machine learning models) for greater decision-making accuracy. Looked into a variety of domains including breast cancer diagnosis, classifying astronomical data, and mining sociological data.
- Collaborative filtering with the Netflix dataset. If you liked movies X and Y, then you're sure to enjoy movie Z!
- Mining user opinions from the web. Automatically determining user sentiment from free-form natural language.
- Multilingual search engine using latent semantic indexing. Write a query in English or Spanish and get relevant results in either language without the use of machine translation.
- Case-based reasoning (CBR) information provenance. Used the origin of data (who/where/when did the data come from?) to help design better CBR systems.
- Using genetic algorithms to grow video game bots (computer-controlled characters) using the Unreal Game Engine.
- Combined machine learning and computer vision algorithms (egomotion) for work on analysis of movement in action sports.
- Handwriting recognition for written Chinese on the iPhone.
If you're interested in artificial intelligence, data mining, or any other cool CS topic, then come talk to me about it!
Activities & Interests
- Building a General Purpose Cross-Domain Sentiment Mining Model (Whitehead and Yaeger, CSIE, 2009)
- Sentiment Mining Using Ensemble Classification Models (Whitehead and Yaeger, SCSS, 2008)
- Case Provenance: The Value of Remembering Case Sources (Leake and Whitehead, ICCBR, 2007)
- Buddy Enhanced Return Routability for Authentication in Mobile IPv6 (Whitehead and Medidi, 2004 SPIE)
- Block 1: Mobile Computing
- Block 2: Application Design
- Block 4: Computer Science I
- Block 5: Databases
- Block 6: Probability and Statistics
- Block 7: Computer Science II
- CP122 – Computer Science I
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