Current Postdoctoral Fellows

• Matthew Smith , Ph.D. Neuroscience (2002) New York University. NIH NEI NRSA fellowship.
• Jason Samonds , Ph.D. Neurophysiology/Electrical Engineering (2004) Vanderbilt University. NIH NEI NRSA fellowship.

Current Undergraduate Research Fellows

• Ankit Khambhati , ECE. NSF URE, NIH Computational Neuroscience fellowship.
• Andrew Maas , Computer Science, CMU, SURG fellowship

Former Postdoctoral Fellows

• 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

• 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

• 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 et al., 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. In Press.
• 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, 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.