Mathematics, University of Hawaii. Minor in Computer Science. University of Mons, Low-Rank Matrix Approximation Group 2019 - Adviser: Prof. Nicolas Gillis - Visiting student researcher. Surya Ganguli, Associate Professor of Applied Physics, Stanford HAI. >> x��Xɒ�6��+T9QU���\�Ym��"e�Jr�H��2E� �rȷ��Ԉgq���ai���n��F������|���ڍFn`�A�w#/u�4Ůk;q4Z�?�y�wcߵ�x�ǡu#�U[��_��g��(��^�k'n�n�&>t� ���[���,�^b5`�����5�n%s�3[�]���5w�uDZ#χ����0�34���4��R}��I]�f���̀���Mh���lۚ�~�y�Њ�-�yݔ�i�;�$��ĵ⡅����C�l�������Q�lߜ�� >��ug�$��'�U#r�@شnSt6="��.i���3�X��ad�F�Iޕ��x�u�j�h;�眞�j�?��_ ߹�VZl�*����Kx�����-�|���7a%P������\�Of~!w�����h�����dX� ��)�0��0��^�m&U��ѐ᛭�K��/ֲҲQ�(��=��)?eM�OQ��s��x^�G���� J�g������6� He is also known for being prolific, high demand public speaker and lecturer, having been invited to give over 200 talks at various universities, institutes, workshops, conferences, and symposiums since 2005 alone. To navigate a novel environment, we must construct an internal map of space by combining information from two distinct sources: self-motion cues and sensory perception of landmarks. Surya Ganguli). Mathematics, Physics, UC Berkeley, May 2014 Highest honors in mathematics, high distinction in general scholarship. 4�e�pi|��w���o��\����&~CA|��Py����S^����iX�ph�T+:���Ho-UT&ˠ�4y�9 J�8R!��ojUJ=��(oWP��[��ӌ�U�~�Gx~n9���H�Ȣ� ���X�&�A/��^]�{j�|� {.U��>��O�3`WE?�� He presently runs the Neural Dynamics and Computation Lab at Stanford, where he aims to reverse engineer how networks of neurons and synapses cooperate across multiple scales of space and time to facilitate sensory perception, motor control, memory, and other cognitive functions. Yuandong Tian, Lantao Yu, Xinlei Chen, Surya Ganguli Student Specialization in Deep ReLU Networks With Finite Width and Input Dimension Yuandong Tian ICML 2020: Luck Matters: Understanding Training Dynamics of Deep ReLU Networks [Workshop Poster] Yuandong Tian, Tina … Designing and Interpreting Probes with Control Tasks. Applied Physics, Stanford University, 2013 B.S. ��a�˕o��9�R���,-?����an�m�/�k�N���ތAn���q�����=��t_����e*�͕t�9A��SY�^:=�|r�Z�� 'n 12 0 obj �yVU�"J� �;Z��_T){���sz���"oE���?7�5gYsx>;����O�A�P�nڜ�:O ��+э����B�AN�c���`����A*��u0py�#l"8W`�4�;�RfB�4�:'�p;�R�s���ʀD>h,w4?éU�Y�`��ũo�%�r=��T��q:�^;���6�Q�fq�T����}���@/)�l�k �\q�H�L*h܄.3$M�8!��;�5d: �AM9��~u]����*� ��؎��$o���&WK�*y�z���#Ϥ�����p($y�� D����-��@�6-Mj�%�qa���v-H�@{׵�M��Y?ɢa�4~U(���^HP*�9���%����'����Q��I��B�i���#�Q̸��E��:����-�C0�5V|ݲ��r�&[���(QN��@����`Kl�n�k,D�0h���H! M.A. in Computer Science, additional major in Cognitive Science. Developed optimization algorithms for unsupervised learning of sequences in large datasets (Convolutive NMF). More information at my website (lanemcintosh.com). GPA: 3.9/4.0. << << B.A. During that time, Ganguli assumed research positions at the Information Mechanics Group at the MIT Laboratory for Computer Science, at the Center for Space Research and the Center for Theoretical Physics at the MIT Department of Physics, and the Information Systems and Technologies Laboratory and the Dynamics of Computation Group at the Xerox Palo Alto Research Center. GPA: 4.0 Math, 3.9 Physics, 3.9 cumulative. �#���t �$ �����ރ�;����a����/ Surya Ganguli is a University Professor at Stanford University and a Visiting Research Professor at Google. We are part of the Stanford department of Neurobiology and department of Psychiatry and Behavioral Sciences We are members of Stanford Bio-X and the Wu Tsai Neurosciences Institute Currently US citizen. B.A. /Filter /FlateDecode [11] A selection of works is listed below: Learn how and when to remove these template messages, reliable, independent, third-party sources, Learn how and when to remove this template message, Sloan-Swartz Center for Theoretical Neurobiology, "On the expressive power of deep neural networks", "Stanford University Department of Applied Physics » Surya Ganguli", "Behind The Tech with Kevin Scott: Surya Ganguli: Innovator in artificial intelligence", https://en.wikipedia.org/w/index.php?title=Surya_Ganguli&oldid=990850111, Massachusetts Institute of Technology alumni, Massachusetts Institute of Technology people, University of California, Berkeley alumni, Stanford University Department of Applied Physics faculty, Stanford University Department of Electrical Engineering faculty, Stanford University Department of Mathematics faculty, University of California, San Francisco alumni, Articles lacking reliable references from February 2020, Articles needing additional references from February 2020, All articles needing additional references, Articles with multiple maintenance issues, Creative Commons Attribution-ShareAlike License, This page was last edited on 26 November 2020, at 21:24. [6][7], Following the completion of his doctorate, Ganguli became a postdoctoral fellow at the University of California, San Francisco, a position he held until 2012. endobj ]�[�bok�J��G[�C�4K�� ���a�Y��y�W�:S���P���(���t��'���i�h�ϸ�-��g�I��i� ����ÞÉVi�'6/�X�}���T{&� Event Title Event Date; Yasmin Hurd, Addiction Institute at Mount Sinai & Icahn School of Medicine : Thursday, March 18, 2021 - 12:30pm: In-House Seminar, Princeton University November 2020. 2012-Present Stanford University Ph.D. Neuroscience Ph.D. Minor Computer Science Advisors: Steve Baccus and Surya Ganguli NVIDIA Best Poster Award, SCIEN … G�.א3�͆k��@ Development of efficient magnetic resonance techniques, and application to musculoskeletal and The William James Award honors individuals for their lifetime of significant intellectual contributions to the basic science of psychology and international recognition for their outstanding contributions to scientific psychology. EMNLP 2019 (long papers). Reverse engineering transient computations in nonlinear recurrent neural networks through model reduction. Dominican Republic. Theoretical Physics, October 2004. Dr. Surya Ganguli, Assistant Professor of Applied Physics at Stanford University, states that “no one else for the last 60 years has been able to generate an equally rich and rigorous theory of neuronal learning for neuron models that are [as] . %�*��~��|���q�n��hJl�J� ��Z�!�k��i�kG.��(��Uzq�{X�9 [4][5], Ganguli then moved on to the University of California, Berkeley, where he completed a master's degree in Physics in 2000 and a master's degree in Mathematics in 2004. Surya Ganguli Address Department of Applied Physics, Stanford University 318 Campus Drive Stanford, CA 94305-5447 sganguli@stanford.edu http://ganguli-gang.stanford.edu/~surya.html Biographic Data Born in Kolkata, India. Research Talks + Panel 1. – Advisor: Prof. Surya Ganguli – Areas of Study: biological and artificial neural networks, unsupervised learning, computer vision Carnegie Mellon University B.S. He then attended the Massachusetts Institute of Technology, where he spent five years completing bachelor's degrees in Mathematics, Physics, and Electrical Engineering and Computer Science, as well as a master's degree in the latter. xڝYIW�H����(���Z-{n`j����0��,�DN�$�[)AQ�~b��B�S3,ED�2c�"" ��g�ه�����i�~y��W�hqv�xƉ�-ҳ,� ����uy,t��Y�����G�pT�* Awards and CV; Education. NAACL 2019 (short … COU�~}���1⇍�g�����^�Yڈ��ܖ(� dЄ�d1�?����>�Fk�Y��\���-��M ��8���q{�ĉ��Ω�f*�T��{-ޫU�}�8f#ϣ��_% �����,��/���p��+,S.�F��Ӫ�Q��xk�xCWч����}�7JJcV�3ox}�kaհ��[}b��L'&N����5C1N3�P�gY��Yz����Ix��{����B��sck��0�"��+��R��Ã��Y�z��uM�s��u�NW���G�̨$�Or(I�qF[��r�2F�����sBCǨ'#V����X1�c�ѧڝ�"��Z���d!�+E2>��NO���R����O�Y� �m,�$�D{e��4F櫖�}6��F�B��+��`V]Kǜ9��5/����\�s�ނ��. endstream ۩��4�cم�]YP�NE�\!U��1{�F*�F�s[p�fJn�Ͷ��Ql�Gk�_�kǮ�Jھ�0)�J�1 �p�4��O�7��Zԝ�f���.u����i�m����z�Eí^!j�q�R 3���}03�[�>}��������'u]G5�r.E97Nc���^M���c/��U[s���K!qX stream Stock, S. Lahriri, A. Williams, & S. Ganguli (2017). [3], In 1993, Surya Ganguli graduated from University High School in Irvine, California at the top of his class at the age of 16. Mathematics, Physics, 2010-2014 Highest honors in mathematics, high distinction in general scholarship. Computational and Systems Neuroscience. A Structual Probe for Finding Syntax in Word Representations. Despite the linearity of their input … Stock, & S. Ganguli (2018). E. DUCATION. *eM�y�X�٭0^�!7M{(���G�������)�_ka�p�R'h��v�% ����[�Z3�D� John Hewitt and Percy Liang. [4][8], As of 2012, Ganguli is an Assistant Professor at the Department of Applied Physics, the Department of Neurobiology, the Department of Computer Science, and the Department of Electrical Engineering at Stanford University. /Length 2867 (See … Advised by Surya Ganguli at Stanford University Sept 2011 - Used Statistical Mechanics methods used to study spin glasses including replica, cavity, and message passing methods to investigate optimal high dimensional statistical inference. Authors: Aran Nayebi, Daniel Bear, Jonas Kubilius, Kohitij Kar, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins (Submitted on 20 Jun 2018 ( v1 ), last revised 27 Oct 2018 (this version, v2)) Study Abroad Internship, A*STAR IHPC Singapore, Summer 2012. C.H. Dr. Ganguli is primarily known for his work on neural networks and deep learning, although he has also published papers on theoretical physics. Education University of California Berkeley Berkeley, CA Ph.D. Applied Physics, Stanford University, 2016 M.S. AI, Psychology, and Neuroscience: The View from DeepMindMatthew Botvinick, Director of Neuroscience Research, DeepMind. The site facilitates research and collaboration in academic endeavors. /Filter /FlateDecode Engineering Physics (Summa Cum Laude), Cornell University, 2010 About me. In 2017, he also assumed a Visiting Research Professorship at Google's Google Brain Deep Learning Team.[9][10]. Candidate in Computer Science September 2011 – December 2017 (expected) – Advisor: Prof. Surya Ganguli – Thesis: Computational tools for understanding biological and artificial neural networks – Areas of Study: deep learning, neuroscience, unsupervised learning, computer vision … Surya Ganguli is part of Stanford Profiles, official site for faculty, postdocs, students and staff information (Expertise, Bio, Research, Publications, and more). 3 0 obj Surya Ganguli, Associate Professor of Applied Physics, Stanford HAI. While at Berkeley, he taught undergraduate courses on Quantum Mechanics, Special Relativity, Statistical Physics, Electromagnetism, and Analytical Mechanics. Research Talks + Panel 1. We attempt to bridge the gap between the theory and practice of deep learning by systematically analyzing learning dynamics for the restricted case of deep linear neural networks. UPenn faculty members share their stories, giving us a peek into the unspoken challenges you don’t get to read on a CV. Curriculum Vitae. Applied various high dimensional clustering techniques to understand cell Github; LinkedIn; Twitter; Kaggle; Timeline. Ganguli Lab website. Dr. Ganguli is primarily known for his work on neural networks and deep learning, although he has also published papers on theoretical physics. Education University of California Berkeley Berkeley, CA Ph.D. [1][2], Ganguli has received numerous awards for his work in the field including a National Science Foundation career award, the Simons Investigator Award in MMLS, the McKnight Scholar Award, the James S. McDonnell Foundation Scholar Award in Human Cognition, an Alfred P. Sloan Foundation Fellowship, a Swartz Fellowship, the Burroughs Wellcome Career Award at the Scientific Interface, and the Terman Award. BRIAN A. HARGREAVES (650) 724-3022 bah@stanford.edu Education June 2001 – Ph.D. in Electrical Engineering at Stanford University, Stanford, California. C.H. Theoretical Physics, October 2004. - Advisers: Dr. Alex Williams, Prof. Scott Linderman, and Prof. Surya Ganguli - Undergraduate research for credit. [19] Universals of word order reflect optimization of grammars for efficient communication (Michael Hahn, Dan … Recent works have identified, through an expensive sequence of training and pruning cycles, the existence of winning lottery tickets or sparse trainable subnetworks at initialization. (��k�嶡YN@�:��s��!.U��)���Ԕ3������}W�W%�@L�N�_�~��C�muUS Runner up best paper. MindCORE & CURF present: Behind the CV: Stories from Faculty A “Growing Up in Science” event “Behind the CV” is a conversation-style event series about becoming and being a scientist. %PDF-1.5 I'm a PhD candidate co-advised by Surya Ganguli. Only upload a photograph of yourself; Photos of children, celebrities, pets, or illustrated cartoon characters will not be approved; Photos containing nudity, gore, or hateful themes are not permissible and may lead to the cancellation of your account Surya Ganguli Neural Dynamics and Computation Lab Stanford University . . He had authored and co-authored a number of papers on theoretical neuroscience prior to this in the late 2000s (collaborating with Haim Sompolinsky, Peter Latham, and Ken Miller in the process) and further taught a course on advanced theoretical neuroscience with Larry Abbott, Stefano Fusi, and Ken Miller in 2008, but it was at this point that Ganguli formally transitioned into theoretical neuroscience, assuming the position at the Sloan-Swartz Center for Theoretical Neurobiology. Download CV; lmcintosh (at) stanford.edu. Honors Ric Weiland Graduate Fellowship in the Humanities and Sciences, 2018-2020 National … �X8g���†�0Pu�d٨�a4S���l�c�l�,0�5��>��;�=,��j9�Y$�c�)ɩ�L��*O�$� �Q�P�@Q�S��.sx�a�ѧ&t(�K�U8��2a[[�М����� Currently US citizen. . ��� Despite the widespread practical success of deep learning methods, our theoretical understanding of the dynamics of learning in deep neural networks remains quite sparse. John Hewitt, Michael Hahn, Surya Ganguli, Percy Liang, and Christopher D. Manning. L� ��t��VjM��\�1(�'�Jy[�f�w��z%�L��9>�[���7��c�����wߙ�N6|kO���Y� x��X��R��yl���@�2��u-2d��Z6MM�zW֍B7m#��c�b�F��e%:r�{AhGQ��"�٤V�J2�SrX7���W�vb`]2o� #��� �'�i�hH��. Stanford University Ph.D. 2020 [20] RNNs can generate bounded hierarchical languages with optimal memory (John Hewitt, Michael Hahn, Surya Ganguli, Percy Liang, Christopher D. Manning), In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), 2020. Emergent elasticity in the neural code for space . John Hewitt and Christopher D. Manning. stream Pruning the parameters of deep neural networks has generated intense interest due to potential savings in time, memory and energy both during training and at test time. His publications have also won a number of conference awards, such as the NIPS 2014 Outstanding Paper award and the Cosyne 2014 award for the top ranked abstract. Ben PooleB poole@cs.stanford.edu H 443 386 8123 m cs.stanford.edu/~poole. Surya Ganguli has an extensive publication record. (pdf) (bib) (blog) (code) (codalab) (slides) (talk). Exactly solvable nonlinear recur-rent networks for context-dependent information processing. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Minor in Computer Science. Finally, Ganguli has won a number of awards unrelated to his academic publications, such as the Berkeley Outstanding Graduate Instructor award and the National Council of Teachers of English Award in Writing. The EOS Decision and Length Extrapolation Ben Newman, John Hewitt, Percy Liang, and Christopher D. Manning. Contribute to ganguli-lab/website development by creating an account on GitHub. /Length 2026 %���� He presently runs the Neural Dynamics and Computation Lab at Stanford, where he aims to reverse engineer how networks of neurons and synapses cooperate across multiple scales of space and time to facilitate sensory perception, motor control, memory, and other cog… He also completed a PhD in String Theory under Dr. Petr Horava at the Lawrence Berkeley National Laboratory later that year. Yoshua Bengio is Professor in the Computer Science and Operations Research departments at U. Montreal, founder and scientific director of Mila and of IVADO. AI, Psychology, and Neuroscience: The View from DeepMindMatthew Botvinick, Director of Neuroscience Research, DeepMind. My research focuses on understanding general principles underlying sensory processing, in particular using tools from deep learning and information theory. Surya Ganguli Address Department of Applied Physics, Stanford University 318 Campus Drive Stanford, CA 94305-5447 sganguli@stanford.edu http://ganguli-gang.stanford.edu/~surya.html Biographic Data Born in Kolkata, India. >> Ph.D. UC Berkeley, B.A. Surya Ganguli is a University Professor at Stanford University and a Visiting Research Professor at Google. Surya Ganguli). Fall 2007 - Spring 2011 – Advisor: Prof. Tai Sing Lee Nonlinear recur-rent networks for context-dependent information processing co-advised by surya Ganguli neural Dynamics and Computation Stanford. - Adviser: Prof. Nicolas Gillis - Visiting student researcher Linderman, and Christopher D... In Word Representations of California Berkeley Berkeley, CA Ph.D a University Professor at Stanford and! 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