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My research focuses on reasoning by analogy from visual perception. I start from the assumption that how and why we reason about the world is informed by the nature and structure of the world itself. Thus, I want to understand and computationally model in particular those ways in which we form and use visual reasoning.
The research I do is very closely aligned with the broader goals of the cognitive systems initiative: explaining human cognition in computational terms and reproducing the entire range of the mind’s abilities in mechanical artifacts, with a concern for high-level cognition, event understanding, and learning, and a strong emphasis on rich representation. I believe my research addresses important questions in artificial intelligence, robotics, cognitive science, and cognitive psychology.
I have been an entrepreneur for four decades. I am keen on translating what I know and what I’ve observed during that time into an operational framework for university researchers and students. I am extending and applying the emerging customer development and lean startup methodologies to the large body of scientific inventions found at modern research universities. My work directly addresses strategic concerns of universities and the nation’s research agencies. My courses in entrepreneurship are award-winning and contemporary with the best offered world-wide. I am a recognized national and international leader in this field.
I have been instrumental in creating new entrepreneurial curriculum at Georgia Tech, especially within the College of Engineering. In 2014, I created and taught two new course offerings, Startup Lab and Startup Summer, both centerpieces of GT’s Create-X program. In 2017, I reinvented the curriculum for the EMBA Capstone in Management of Technology for the College of Business. In 2018 and 2021, I was honored to be named a Professor of the Year for that course. In 2019, I received GT’s highest curriculum award for my work in these entrepreneurship courses. In 2022, I created the largest entrepreneurship class offered at Georgia Tech for the OMSCS program (more than 160 students enrolled for Fall 2023), with the intent of understanding how to teach entrepreneurship at scale.
Kralik, J.D., Lee, J.H., Rosenbloom, P.S., Jackson, P.C., Epstein, S.L., Romero, O.J., Sanz, R., Larue, O., Schmidtke, H.R., Lee, S.W., McGreggor, K. (2018). “Metacognition for a Common Model of Cognition.” Procedia Computer Science, 145, pp. 730-739.
McGreggor, K., Kunda, M., & Goel, A. K. (2014). "Fractals and Ravens." Artificial Intelligence. October, pp. 1-23.
Kunda, M., McGreggor, K., & Goel, A. K. (2012). "A computational model for solving problems from the Raven's Progressive Matrices intelligence test using iconic visual representations." Cognitive Systems Research, 22-23, pp. 47-66.
McGreggor, K., & Goel, A.K. (2014) “A Computational Strategy for Fractal Analogies in Visual Perception.” Computational approaches to analogical reasoning - Current trends, Prade, H. & Richard, G. (eds). Springer Publishing Company, Inc.
Novoa, M., Sánchez-Roig, K., Bridges, B.D., McGreggor, K., Ramírez-Gelpi, P. (2021) “The Impact of a Customer Discovery Boot Camp on Puerto Rico’s Startup Ecosystem.” LACCEI International Multiconference on Entrepreneurship, Innovation, and Regional Development. Virtual.
Kuthalam, M., McGreggor, K., Goel, A. (2021) “Entrepreneurship: A New Frontier in a Computational Science of Creativity.” 12th International Conference on Computational Creativity, Mexico City, Mexico.
Forest, C.R., Sivakumar, R., Vito, R.P., Saxena, R., Harris, J., Perkins, R., Davidson, D., Ramachandran, K., McGreggor, K., Olufisayo, O., Klaus, C., McLaughlin, S. (2021) “CREATE-X: Toward student entrepreneurial confidence," IEEE Potentials, vol. 40, no. 3, pp. 14-22.
Yang, Y, McGreggor, K., Kunda, M. (2020) “Not Quite Any Way You Slice It: How Different Analogical Constructions Affect Raven’s Matrices Performance.” Proceedings of the 8th conference of Advances in Cognitive Systems, 2020.
McGreggor K., Goel A. (2016) “Bistable Perception and Fractal Reasoning.” In: Jamnik M., Uesaka Y., Elzer Schwartz S. (eds) Diagrammatic Representation and Inference. Diagrams 2016. Lecture Notes in Computer Science, vol 9781. Springer, Cham
Fitzgerald, T., McGreggor, K., Akgun, B., Thomaz, A., & Goel, A. K. (2015). “Visual Case Retrieval for Interpreting Skill Demonstrations.” Proceedings of the 23rd International Conference on Case-Based Reasoning. Frankfurt, Germany. September, 2015.
McGreggor, K., & Goel, A. (2014). “Confident Reasoning on Raven’s Progressive Matrices Tests.” AAAI National Conference. Quebec, Canada, July 2014.