Maithilee Kunda is an Assistant Professor of computer science and computer engineering in the department of Electrical Engineering and Computer Science at Vanderbilt University. Her work in artificial intelligence, in the area of cognitive systems, looks at how visual thinking contributes to learning and intelligent behavior with a focus on applications for individuals on the autism spectrum. She holds a B.S. in mathematics with computer science from MIT and a Ph.D. in computer science from Georgia Tech, and she currently directs the laboratory for Artificial Intelligence and Visual Analogical Systems. In 2016, she was recognized as a visionary on the MIT Tech Review’s annual list of 35 Innovators Under 35.
mkunda [at] vanderbilt [dot] edu
2301 Vanderbilt Place
Nashville, TN 37235-1679, USA
Kunda, M., & Goel, A. K. (2011). “Thinking in Pictures as a cognitive account of autism.” Journal of Autism and Developmental Disorders, 41 (9), pp. 1157-1177.
Kunda, M., McGreggor, K., & Goel, A. K. (2013). “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.
Kunda, M., & Ting, J. (2016). “Looking around the mind’s eye: Attention-based access to visual search templates in working memory .” Advances in Cognitive Systems, 4, 113–129.
McGreggor, K., Kunda, M., & Goel, A. K. (2014). “Fractals and Ravens.” Artificial Intelligence, 215, pp. 1-23.
A more complete list of publications can be found here.
Computation and Cognition (CS 8395). Offered Fall 2017. Computational approaches to understanding human cognition, including research design and methods for integrating models with theory and observation. Topics include knowledge representation, concept formation, reasoning and search, analogy, mental imagery, and connectionism, as well as multidisciplinary perspectives on mind, brain, behavior, and society.
Computational Mental Imagery (CS 8395). Computational basis of visual mental imagery in human cognition and in artificial intelligence (AI) systems. Topics include knowledge representations and operations in mental imagery, role of mental imagery in problem solving, creativity, education, and scientific discovery, and variations in mental imagery in cognitive conditions such as autism.
Projects in AI (CS 4269) – Computation and Cognition. Offered Fall 2017. This course will be co-taught with Computation and Cognition; see above for course description.
Projects in AI (CS 4269) – Introduction to Machine Learning. Offered Spring 2018. Fundamentals of machine learning, with a focus on supervised learning. Topics include decision trees, neural networks, and deep learning, as well as impacts of ML on society, such as issues related to data privacy, human subjects protections, and case studies of ML successes and failures.