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James Foster

jmfoster AT gmail DOT com

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Biography

I am a graduate student at the University of Colorado Boulder (CU) pursuing a joint PhD in Cognitive Psychology, Cognitive Science, and Neuroscience.
I have a Master's in Cognitive Psychology from CU and a B.S. in Computer Science from the University of Florida.

Statement of Purpose (2011)
Statement of Purpose (2009)
Quotations to Live By


Research Interests

My research is at the intersection of cognitive psychology and artificial intelligence. My work involves cognitive modeling, machine learning, experimental design, statistical analysis, and software development. My research projects have included the automatic identification of core concepts in natural language educational resources, computational modeling of analogical reinforcement learning, and human experiments on metaphor comprehension. I compete in data science and machine learning competitions with CU's data science team.

In my current role, I serve as a data analysis and research consultant. I help graduate students, post-docs, and faculty members use technology to better conduct psychological research. I have developed customized data analysis methods and tools for statistical hypothesis testing, visualization, machine learning, and supercomputing. I have also provided consultation for experimental design and implementation, including laboratory and large-scale online data collection.

As a Ph.D. candidate, my research has focused on understanding how people and computers can learn abstract relational concepts that are useful for making predictions and guiding behavior. In my Master's thesis project, I developed a theoretical and computational framework for integrating reinforcement learning and analogical reasoning. I implemented the framework in an AI agent that autonomously discovers relational patterns (schemas) in simulations of Conway's Game of Life and two-player adversarial games. I designed, implemented, and analyzed psychological experiments to assess the psychological validity of the model's principles. I have also investigated analogical processes in language learning and processing, as well as the neural mechanisms involved in metaphor comprehension. The synergy between analogy, reinforcement learning, and language supports many uniquely human abilities. My work extends these powerful cognitive mechanisms to artificial intelligence systems.

Research Areas

Human and Machine Learning

  • Analogy and Relational Concept Learning
  • Cognitive Modeling
  • Reinforcement Learning

Language

  • Language Learning
  • Lexical Semantics - polysemy and ambiguity
  • Metaphor Interpretation
  • Word Sense Disambiguation
  • Natural Language Processing

Educational Technology

  • Multi-document Summarization
  • Automatic Essay Analysis
  • Computational Thinking


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