Undergraduate Research Projects
Below are descriptions of some of the projects I worked on as an undergraduate at RPI (2005-2008).
Measures of Semantic Relatedness
Measures of Semantic Relatedness (MSRs) are computational means for calculating the association strength between terms. MSRs have been used to produce
models of human web-browsing behavior, augmented search engine technology, essay-grading algorithms for ETS, and could be useful for any cognitive models or AI agents
that have to deal with text. My work on this project varied from evaluating the effects of corpus selection on MSRs to creating new MSRs using neural networks.
Selected Papers:
Lindsey, R., Stipicevic, M., Veksler, V.D., & Gray, W.D. (2008). BLOSSOM: Best path Length on a Semantic Self-Organizing Map. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp. 481-487). Austin, TX: Cognitive Science Society.
Lindsey, R., Veksler, V. D., Grintsvayg, A., & Gray, W. D. (2007). Effects of Corpus Selection on Measuring Semantic Relatedness. Proceedings of the 8th International Conference on Cognitive Modeling, Ann Arbor, MI.
Visual Search
Visual search takes place whenever we are looking for something. But when the location of a search target has been encoded on a previous occasion, memory processes can supplement or compete with eye movements during search. The goal of this project is to illuminate the interactions of visual attention and memory by assessing how humans adapt their search strategies to the cost structure of a task environment. My work on this project involved programming cognitive models of humans in a visual search environment.
Tetris
Apart from being a game that we all know and love, Tetris is also a relatively complex cognitive task that requires dynamic task processing, advanced perceptual capabilities, and involves both top-down and bottom-up strategies. Given the lack of cognitive models designed for such dynamic tasks, we explored the Tetris environment as a way to get at human perception, learning and memory, categorization, attention, and procedure/strategy selection. For this project, I wrote a parallel genetic algorithm on TeraGrid and used it to create a good Tetris-playing program.
