Sebastian Seung | Computer Science Department at Princeton University

Title/Position

Evnin Professor in Neuroscience, Professor of Computer Science and Princeton Neurosciences Institute

Degree

Ph.D., Harvard University, 1990

sseung (@cs.princeton.edu) (609) 258-7713 153 Princeton Neuroscience Institute

Homepage

https://www.cs.princeton.edu/~sseung

Other Affiliations

PNI

Research

Interests: Machine learning, computational biology

Ho-Am Prize in Engineering, 2008; McKnight Scholar Award, 2000

Research Areas:

Short Bio

Sebastian Seung is Professor at the Princeton Neuroscience Institute and Department of Computer Science. Seung has done influential research in both computer science and neuroscience. Over the past decade, he helped pioneer the new field of connectomics, developing machine learning and social computing technologies for reconstructing neural circuits from high resolution brain images. His lab created EyeWire, a site that has recruited over 150,000 players from 130 countries to a game to map neural connections.

Seung is also known for his efforts to communicate neuroscience to the general public. His TED Talk "I am my connectome" has more than 750,000 views, and has been translated into 26 languages. His book Connectome: How the Brain's Wiring Makes Us Who We Are was chosen by the Wall Street Journal as Top Ten Nonfiction of 2012.

Before joining the Princeton faculty in 2014, Seung studied at Harvard University, worked at Bell Laboratories, and taught at the Massachusetts Institute of Technology. He is an External Member of the Max Planck Society, and winner of the 2008 Ho-Am Prize in Engineering.

Selected Publications

J. S. Kim, M. J. Greene, A. Zlateski, K. Lee, M. Richardson, S. C. Turaga, M. Purcaro, M. Balkam, A. Robinson, B. F. Behabadi, M. Campos, W. Denk, H. S. Seung, and the EyeWirers. Space-time wiring specificity supports direction selectivity in the retina. Nature 509, 331-6 (2014).
M. Helmstaedter, K. L. Briggman, S. C. Turaga, V. Jain, H. S. Seung, and W. Denk. Connectomic reconstruction of the inner plexiform layer in the mouse retina. Nature 500, 168-74 (2013).
V. Jain, S. Turaga, K. Briggman, M. Helmstaedter, W. Denk, and H. S. Seung. Learning to agglomerate superpixel hierarchies. Adv. Neural Info. Proc. Syst. 24, 648-656 (2011).
V. Jain, H. S. Seung, and S. C. Turaga. Machines that learn to segment images: a crucial technology for connectomics. Curr Opin Neurobiol. 20, 653-66 (2010).
S. C. Turaga, J. F. Murray, V. Jain, F. Roth, M. Helmstaedter, K. Briggman, W. Denk, and H. S. Seung. Convolutional networks can learn to generate affinity graphs for image segmentation. Neural Comput. 22, 511-38 (2010).
V. Jain, B. Bollmann, M. Richardson, D. Berger, M. Helmstaedter, K. Briggman, W. Denk, J. Bowden, J. Mendenhall, W. Abraham, K. Harris, N. Kasthuri, K. Hayworth, R. Schalek, J. Tapia, J. Lichtman, and H. S. Seung. Boundary Learning by Optimization with Topological Constraints. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2488-2495 (2010).
S. C. Turaga, K. L. Briggman, M. Helmstaedter, W. Denk, and H. S. Seung. Maximin affinity learning of image segmentation. Adv. Neural Info. Proc. Syst. 22:1865-1873 (2009).
Y. Loewenstein, D. Prelec, and H. S. Seung. Operant matching as a Nash equilibrium of an intertemporal game. Neural Computation 21, 2755-2773 (2009).
H. S. Seung. Reading the Book of Memory: Sparse Sampling versus Dense Mapping of Connectomes. Neuron 62, 17-29 (2009).
V. Jain and H. S. Seung. Natural Image Denoising with Convolutional Networks. Adv. Neural Info. Proc. Syst. 21: 769-776 (2009).
V. Jain, J. F. Murray, F. Roth, S. Turaga, V. Zhigulin, K. L. Briggman, M. N. Helmstaedter, W. Denk, and H. S. Seung. Supervised Learning of Image Restoration with Convolutional Networks. Proceedings of the IEEE 11th International Conference on Computer Vision (ICCV) (2007).