5th Neuro Inspired Computational Elements Workshop (NICE 2017)

San Jose CA

Mar 6 - 8, 2017

Neuro Inspired Computational Elements Workshop

Next generation computing systems beyond von Neumann/Turing Architecture and Moore's Law Limits

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Brian Van Essen

Informatics Group Lead / Computer Scientist, Lawrence Livermore National Laboratory

Bio: Brian is the Informatics Group leader and a Computer Scientist in the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory (LLNL). He is actively pursuing research in large-scale deep learning for scientific domains and training deep neural networks using high-performance computing systems. He is the project leader for the Livermore Big Artificial Neural Network (LBANN) open-source deep learning toolkit. Additionally, he co-leads an effort to mapping these scientific, data-intensive, and machine learning applications to Neuromorphic architectures. His research interests also include developing new Operating Systems and Runtimes (OS/R) that exploit persistent memory architectures, including distributed and multi-level non-volatile memory hierarchies, for high-performance, data-intensive computing.

Konstantinos Michmizos

Assistant Professor, Rutgers University

Bio: neuro-robotics, astrocytes

David Cox


Bio: David Cox is an assistant professor of molecular and cellular biology and of computer science, as well as a member of the Center for Brain Science at Harvard University. He completed his PhD in the Department of Brain and Cognitive Sciences at MIT with a specialization in computational neuroscience. Before joining MCB/CBS, he was a junior fellow at the Rowland Institute at Harvard, a multidisciplinary institute focused on high-risk, high-reward scientific research at the boundaries of traditional fields. His laboratory seeks to understand the computational underpinnings of high-level visual processing through concerted efforts in both reverse and forward engineering. To this end, his group employs a wide range of experimental techniques (ranging from microelectrode recordings in living brains to visual psychophysics in humans) to probe natural systems, while at the same time actively developing practical computer vision systems based on what is learned about the brain.

Brad Aimone

Prinicpal Member of Technical Staff, Sandia National Laboratories

Devanand Shenoy

Chief Engineer, U.S. Department of Energy

Emre Neftci

Assistant Professor, UC Irvine

Gary Marcus

Director, Uber AI Labs, Uber

Hava Siegelmann

Program Manager, Defense Advanced Research Projects Agency (DARPA)

James Plank

Professor, University of Tennessee

Jon Candelaria

Research Program Director, SRC

Karlheinz Meier

Chair Experimental Physics, Heidelberg University

Mark McDonnell

Associate Professor, University of South Australia

Miao Hu

Postdoc, Hewlett-Packard Laboratories

Paul Franzon

Flight lead, Bandit Flight

Sankar Basu

Program Director, NSF

Shimeng Yu

Faculty, Arizona State University

Steve Furber

Professor, University of Manchester

Wenyuan Li

Researcher PHD Student, UCLA

Andreas Tolias

Associate Professor, Baylor College of Medicine

Bruno Olshausen

Professor, Redwood Center/UC Berkeley

Christof Koch

President & CSO, Allen Institute

Dharmendra Modha

IBM Fellow, IBM

Erwin Gianchandani

Deputy Assistant Director, National Science Foundation

Fred Rothganger

SMTS, Sandia National Labs

Hesham Mostafa

Postdoc, University of California San Diego

Hyong-Euk Lee

Principal Researcher, SAIT, Samsung Electronics

Teri Fry

Co-Founder, Numenta, Inc.

Johannes Schemmel

Research Scientist, Heidelberg University

Narayan Srinivasa

Chief Research Scientist, Intel Corporation

Nga Nguyen

Postdoctoral Research Associate, Los Alamos National Laboratory

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