If you're interested in computer science, then feel free to stop by my office (Tutt Science Center 206H) and chat about it.
If you're not interested in computer science, then feel free to stop by my office and we can chat about how to change that.
My office hours are usually from 1:30pm-2:30pm M-Th, but please stop in whenever you see me around.
Courses for 2014-2015
- Block 1: Computer Science 1
- Block 2: Research
- Block 3: Databases
- Block 4: Away from campus
- Block 5: Application Design
- Block 6: CS Capstone
- Block 7: Artificial Intelligence
- Block 8: Research
- Blocks 4-8: Robotics
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 (past and present):
- Using computers to generate natural language from structured data or statistics. Right now I'm trying to generate English summaries of basketball games based on statistics and play-by-play data from the game. Part of this project involves building a dynamic probabilistic language model that changes its conditional probabilities as the topic or theme of the communication changes.
- 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!
- Multi-K Machine Learning Ensembles (Whitehead and Yaeger, MAICS, 2012)
- 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)
When I'm not stuck at my computer I can usually be found bicycling, hiking, trail running, 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.
Office: Tutt Science Center (TSC) 206H
Normal Office Hours: M-Th 1:30 pm-2:30 pm
Office Phone: 719-389-6536
Mathematics & Computer Science
Tutt Science Center
14 E. Cache la Poudre St.
Colorado Springs, CO 80903