• Society of Harvard Engineers and Scientists Honor Scholar (1985) .


• Harvard-MIT HST Fellowship Award (1986) .


• McDonnell Pew Foundation Young Investigator Research Award (1996) .


• NSF Faculty Career Development (CAREER) Award (2000).

Former Postdoctoral Fellows

• Matthew Smith , Ph.D. Neuroscience (2002), New York University. University of Pittsburgh.
• Xiaogang Yan , Ph.D. Biomedical Engineering (1990), Zhejiang University, PRC. York University.
• Yugou Yu , Ph.D. Physics (2001) Nanjing University, PRC. Yale University, USA.

Some Former Undergraduate Research Fellows

• Andrew Maas , Computer Science, CMU. Standford Ph.D. program in Computer Science
• Ankit Khambhati , ECE, CMU.
• Lei Liu , Neuroscience. Then attended Temple Medical School
• My Nguyen , Biology. Then attended Heinz School of Public Policy master degree, Carnegie Mellon
• Ken Shan , Mathematics. Then Ph.D. in Computer Science, Harvard University. Now, assistant professor in computer science and cognitive science, Rutgers, State U. of New Jersey.
• Matt Easterday , Computer Science/Philosophy. Then attended Carnegie Mellon, Ph.D. HCI Computer Science
• Mary Berna , Mechanical Engineering. Then attended Carnegie Mellon, Robotics Ph.D. program.
• Cindy Yang , Biology. Then attended Neuroscience Ph.D. program, UCSF.
• Scott Marmer , Electrical Engineering. Then attended Harvard Law School
• Alexandria Marino , Psychology. Then attend Yale Medical School
• Tom DuBois , Computer Science.
• Elise Cassidente , Computer Science. Then attended Law School
• Khary Mendez , Computer Science. Then became a Software Engineer.
• Iain Proctor , Computer Science.

Publications

• Stepleton, T., Ghahramani, Z., Gordon G., Lee, T.S. (2009) The Block Diagonal Infinite Hidden Markov Model Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics.
• Potetz, B., Lee, T.S. (2009) Scene statistics and 3D surface perception. In Computational Vision: From Surfaces to Objects. Chapman Hall.
• Lee, T.S. (2009) Computational approaches in visual perception Encyclopedia of Perception, Ed. E.B. Goldstein et al., SAGE Press.
• Lee, T.S., Stepleton, T, Potetz, B and Samonds J. (2008) Neural coding of scene statistics for surface and object inference In Object Categorization: perspectives from human and machine vision, Ed. Sven Dickinson, Ales Leonardis, Bernt Schiele, Michael Tarr, Cambridge University Press.
• Lee, T.S. (2008) Contextual influences in visual processing. Encyclopedia of Neuroscience, Ed. M.D. Binder, N. Hirokawa and U. Windhorst, Springer-Verlag. in Press.
• Potetz, B. and Lee, T.S. (2008) Efficient belief propagation for higher order cliques using linear constraint nodes. Computer Vision and Image Understanding. 112(1): 39-54.
• Smith, M.A., Kelly, R.C., Lee, T.S., (2007) Dynamics of response to perceptual pop-out stimuli in macaque V1. J. Neurophysiology 98: 3436-3449.
• Kelly, R.C., Smith, M.A., Samonds, J.M., Kohn, A., Bonds, A.B., Movshon, J.A., Lee, T.S., (2007) Comparison of recordings from microelectrode arrays and single electrodes in visual cortex. J. Neuroscience 27: 261-264. .
• Samonds, J., Potetz, B., Lee, T.S., (2007) Neurophysiological evidence of cooperative mechanisms for stereo computation. NIPS -- Advances in Neural Information Processing Systems 19, 1201-1208, MIT Press .
• Lee, T.S., Yuille, A (2006) Efficient coding of visual scenes by grouping and segmentation: theoretical predictions and biological relevance. in Bayesian Brain, probabilistic approaches to neural coding. Ed. K. Doya, S. Ishii, R. Rao, A. Pougeti. MIT Press, 141-185.
• Potetz, B., Lee, T.S. (2006) Scaling Laws in Natural Scenes and the Inference of 3D Shape. NIPS -- Advances in Neural Information Processing Systems 18, 1089-1096, MIT Press .
• Yu, Y., Romero, R., Lee, T.S. (2005) Preference of sensory neural coding for 1/f signals. Physics Review Letters, 94 , 108103, 1-4.
• Yu, Y., Lee, T.S. (2005) Adaptive contrast gain control and information maximization Neurocomputing, 65-66(2005): 111-116.
• Yu, Y., Potetz, B., Lee, T.S. (2005) The role of spiking nonlinearity in contrast gain control and information transmission. Vision Research, 45(2005): 583-592.
• Stepleton, T., Lee, TS (2005) Using Co-occurrence and Segmentation to Learn Feature-based Object Models from Video. WACV/MOTION 2005 , 129-134
• Deco, D., Lee, T.S. (2004) The role of early visual cortex in visual integration: a neural model of recurrent interaction. European Journal of Neuroscience 20: 1089-1100.
• Kelly, R. and Lee, T.S. (2004) Decoding V1 Neuronal Activity using Particle Filtering with Volterra Kernels. Advances in Neural Information Processing Systems 15, MIT Press. . Ed. Thurn, S., Lawrence, KS, Bernhard, S. 1359-1366.
• Kelly, R. and Lee, T.S. (2004) Decoding visual input based on V1 neuronal activities with particle filtering. Neurocomputing. . 58-60: 849-855.
• Yu, Y. and Lee, T.S. (2004) Nonlinear dynamics of spike generation account for contrast adaptation. Proceedings of the Computational Neuroscience conference. . Spain.
• Yu, Y., Liu, F., Wang W., Lee, T.S. (2004) Optimal synchrony state for maximum information transmission. NeuroReport 15(10): 1605-1610.
• Lee, T.S., Mumford, D. (2003) Hierarchical Bayesian inference in the visual cortex. Journal of Optical Society of America, A. . 20(7): 1434-1448.
• Yu, Y., Lee, T.S. (2003) Dynamical mechanisms underlying contrast gain control in single neurons. Physics Review, E.. 68(1): 1901-1907.
• Lee, T.S. (2003) Neural basis of attentive perceptual organization. . In Perceptual Organization in Vision: Behavioral and Neural Perspectives Ed. M. Behrmann, C. Olson and R. Kimchi, Lawrence Erlbaum Associates, 431-457.
• Lee, T.S. (2003) Analysis and synthesis of visual images in the brain: evidence for Pattern theory. In Mathematical methods in computer vision, Lecture notes in Mathematics and its Application. Ed. P. Olver and A. Tannenbaum. Springer-Verlag, 87-106.
• Potetz, B., Lee, T.S. (2003) Statistical correlations between 2D images and 3D structures in natural scenes. Journal of Optical Socity of America, A. . 20(7): 1292-1303.
• Lee, T.S. (2003) Computations in the early visual cortex. J. Physiology (Paris) , 97(203), 121-139.
• Romero, R.D., Yu, Y., Afshar, P., Lee, T.S. (2003) Adaptation of the temporal receptive fields of Macaque V1 neurons Neurocomputing (52-54): 135-140.
• Yu, Y., Lee, T.S. (2003) Adaptation of the transfer function of the Hodgkin-Huxley (HH) neuronal model. Neurocomputing (52-54): 441-445.
• Lee, T.S., Yang, C., Romero, R.D., and Mumford, D. (2002) Neural activity in early visual cortex reflects behavioral experience and higher order perceptual saliency. Nature Neuroscience 5(6) . 589-597.
• Lee, T.S. (2002) The nature of illusory contour computation. Neuron 33(5) 667-668.
• Lee, T.S. (2002) Top-down influence in early visual processing: A Bayesian perspective. Behaviors and Physiology 77(4-5): 645-650.
• Romero, R., Lee, T.S. (2002). Spike train analysis for single trial data using Hidden Markov Model Neurocomputing 44-46: 597-604, Elsevier Press.
• Deco, G., Lee, T.S. (2002). An unified model of spatial and object attention based on inter-cortical biased competition. Neurocomputing 44-46: 769-774, Elsevier Press
• Yu, S., T.S. Lee, T. Kanade (2002) A hierarchical Markov Random Field Model for figure-ground Segregation Lecture Notes in Computer Science, 2134, pp 118-133, Springer-Verlag.
• Lee, T.S., Nguyen, M. (2001). Dynamics of subjective contour formation in early visual cortex. Proceedings of the National Academy of Sciences, U.S.A. , 98(4) 1907-1911.
• Romero, R.D., Lee T.S. (2001) Estimation of temporal kernels for cells in V1. Proceedings of Annual Conference in Computational Neuroscience .
• Lee, T.S., Yu, S. (2000) An information-theoretic framework for understanding saccadic behaviors. Advances in Neural Information Processing Systems 12: 834-840 , Ed. S.A. Solla, T.K. Leen, K-R. Muller. MIT Press.
• Yu, S., Lee T.S. (2000) What V1 neurons tell us about saccadic suppression. Neurocomputing Elsevier Press, 32-33, 271-277.
• Cassidente, E., Yan X.G, Lee T.S. (2000) A Bayesian decision approach to evaluate local and contextual information from spike trains. Neurocomputing , 32-33, 1013-1020 Elsevier Press.
• Yan, X.G. and Lee, T.S. (2000). Informatics of spike trains in neuronal ensemble. Proceedings of the International Conference of Biomedical Engineering . 5978-655226, 1-6.
• Lee, T.S., D. Mumford, R. Romero and V.A.F. Lamme (1998). The role of primary visual cortex in higher level vision. Vision Research 38, 2429-2454.
• Lee, T.S., D. Mumford, S.C. Zhu and V.A.F. Lamme (1997). The role of V1 in shape representation. Proceedings of the Annual Conference of Computational Neuroscience 96 .
• Lee, T.S. (1996). Image representation using 2D Gabor wavelets. IEEE Transection of Pattern Analysis and Machine Intelligence. Vol. 18, No. 10, October, 959-971.
• Lee, T.S. (1995). Neurophysiological evidence for image segmentation and medial axis computation in primate V1. Computational Neuroscience . (Ed. Jim Bower). Academic Press. 373-378.
• Lee, T.S. (1995). A Bayesian framework for understanding texture segmentation in the primary visual cortex. Vision Research 35, 2643-2657..
• Zhu, S.C., Lee, T.S., and Yuille, A. (1995). Region competition: unifying snakes, region growing and MDL for image segmentation. Proceedings of the Fifth International Conference in Computer Vision 416-425.
• Lee, T.S. (1994). Representational strategy in the visual cortex. Proceedings of First International Conference in Image Processing, Texas,1994. 2: 590-595.
• Lee, T.S., D. Mumford, A. Yuille (1992). Texture segmentation by minimizing vector-valued energy functionals: the coupled-membrane model. Lecture Notes in Computer Science 588, 165-173, Springer-Verlag.