Michael Lewicki

Professor, Computer and Data Sciences Department
Develops theoretical models of computation and representation in sensory coding and perception
Office: 508 Olin Phone Number: (216) 368-3168 Email: michael.lewicki@case.edu

Education

Ph.D., Computation and Neural Systems, California Institute of Technology, 1996
B.S., Math and Cognitive Science (double major), Carnegie Mellon University, 1989

Publications

Doi, E., & Lewicki, M. S. (2014). A simple model of optimal population coding for sensory systems. PLoS Computational Biology, 10 (8), 14.
DiMattina, C., Fox, S., & Lewicki, M. S. (2012). Detecting natural occlusion boundaries using local cues. J Vision, 12 (13), 15–15.
Doi, E., & Lewicki, M. S. (2011). Characterization of minimum error linear coding with sensory and neural noise.. Neural Computation, 23 (10), 2498–2510.
Karklin, Y., & Lewicki, M. S. (2009). Emergence of complex cell properties by learning to generalize in natural scenes. Nature, 457 (7225), 83–86.
Cavaco, S., & Lewicki, M. S. (2007). Statistical modeling of intrinsic structures in impact sounds. Journal of the Acoustical Society of America, 121 (6), 3558-3568.
Doi, E., Balcan, D., & Lewicki, M. S. (2007). Robust Coding over Noisy Overcomplete Channels. IEEE Transactions on Image Processing, 16 (2), 442-452.
Smith, E., & Lewicki, M. S. (2006). Efficient Auditory Coding. Nature, 439 , 978 - 982.
Smith, E., & Lewicki, M. S. (2005). Efficient coding of time-relative structure using spikes. Neural Computation, 17 (1), 19-45.
Karklin, Y., & Lewicki, M. S. (2005). Modeling non-stationary distributions with a hierarchical density component model. Neural Computation, 17 (2), 397 - 423.
Karklin, Y., & Lewicki, M. S. (2003). Learning higher-order structures in natural images.. Network: Computation in Neural Systems, 14 , 483-499.
Lewicki, M. S. (2002). Efficient coding of natural sounds. Nature Neuroscience, 5 (4), 356-363.
Lee, T., & Lewicki, M. S. (2002). Unsupervised classification, segmentation and enhancement of images using ICA mixture models. IEEE Trans. Image Proc., 11 (3), 270-279.
Lewicki, M. S., & Sejnowski, T. S. (2000). Learning overcomplete representations. Neural Computation, 12 (2), 337-365.
Lee, T., Lewicki, M. S., & Sejnowski, T. S. (2000). ICA Mixture Models for Unsupervised Classification of Non-Gaussian Sources and Automatic Context Switching in Blind Signal Separation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22 (10), 1078-1089.
Lewicki, M. S., & Olshausen, B. S. (1999). A Probabilistic Framework for the Adaptation and Comparison of Image Codes. Journal of the Optical Society of America A, 16 (7), 1587-1601.
Lewicki, M. S. (1998). A review of methods for spike sorting: the detection and classification of neural action potentials.. Network: Computation in Neural Systems, 9 (4), R53-R78.
Lewicki, M. S., & Arthur, B. S. (1996). Hierarchical organization of auditory context sensitivity.. J. Neurosci., 16 (21), 6987–6998.
Lewicki, M. S. (1996). Intracellular Characterization of Song-Specific Neurons in the Zebra Finch Auditory Forebrain. J. Neurosci., 16 (18), 5854–5863.
Lewicki, M. S., & Konishi, M. S. (1995). Mechanisms underlying the sensitivity of songbird forebrain neurons to temporal order. Proc. Natl. Acad. Sci. USA, 92 , 5582–5586.
Lewicki, M. S. (1994). Bayesian modeling and classification of neural signals. Neural Computation, 6 , 1005–1030.