I am a professor in the Department of Computer Science, Colorado State University (CSU), working on machine learning algorithms and deep neural networks for reinforcement learning, brain-computer interfaces and high-dimensional data in general. My interests are in algorithms for classification, modeling, and control problems, the representations learned by them, and what this tells us about the data. Please contact me if you would like to explore the patterns in your data using machine learning methods. Information about our on-line graduate program is available at Degrees Without Borders: Online Programs in Artificial Intelligence.
You may also contact my AI consulting company, Pattern Exploration, whose goal is to develop custom AI solutions to important problems, such as ones related to health, environment, and energy.
I received my Ph.D. in Computer Science from the University of Massachusetts, Amherst in 1986, advised by Andrew Barto. After working for three years at GTE Labs, Waltham, MA, I joined the computer science department at Colorado State University, where I have joint appointments in the Molecular, Cellular, and Integrative Neuroscience Program, the School of Biomedical Engineering, the Graduate Degree Program in Ecology, and the Online Systems Engineering Program.
Contact: chuck.anderson [ at ] colostate.edu
Office: 444 Computer Science Building, Colorado State University
Recent Awards
- 2024, CSU Online Outstanding Distance Educator Award
- 2015, Best Overall Paper Award at the 2015 International Joint Conference on Neural Networks in Killarney, Ireland. Paper Title: Faster Reinforcement Learning After Pretraining Deep Networks to Predict State Dynamics.
Ph.D. Graduate Students
Current
- Muhammad Hamdan M Alsharif – human gesture recognition
- Dejan Markovikj – reinforcement learning
- Paras Memon – brain-computer interfaces
- Kartikay Sharma – brain-computer interfaces
- Jason Stock – attention, scattering transform, explainable/interpretable AI
Past
- Fereydoon Vafaei, 2023 – MRI analysis
- David Blondheim, 2021 – machine learning in die casting
- Elliott Forney, 2019 – brain-computer interfaces
- Saleh Alzahrani 2019 – brain-computer interfaces
- Ratna Saripalli, 2019 – reinforcement learning
- Daniel Elliott, 2018 – reinforcement learning
- Minwoo Lee, 2017 – reinforcement learning
- Rehab Ashari, 2015 – brain-computer interfaces
- Saud Alotaibi, 2015 – sentiment analysis of arabic text
- Keith Bush, 2008 – reinforcement learning
- James Nate Knight, 2008 – reinforcement learning, robust control
- David Peterson, 2007 – EEG oscillations
- Stewart Crawford, 2003 – biomedical images
- R. Matthew Kretchmar, 2000 – reinforcement learning, robust control