Paul Merolla
My research focus is to build more intelligent computers, drawing inspiration from neuroscience, engineering, and machine learning. I have been a lead designer on more than 10 brain-inspired chips, including Stanford’s Neurogrid and IBM’s TrueNorth chip. While my main expertise is designing low-power neural hardware, I am also passionate about developing algorithms for these systems aimed at solving real world problems.
Recently, I co-founded Neuralink, a startup based in San Francisco developing a high bandwidth interface for the nervous system. Before that, I was a research scientist in IBM's Brain-Inspired Computing group (2010 - 2016), and before that, I was a postdoctoral scholar in Stanford's Brains in Silicon lab (2006 - 2010). I received my PhD from the University of Pennsylvania in Bioengineering (2006) and a BS from the University of Virginia in Electrical Engineering (2000).
Michael Milford
Professor Milford conducts interdisciplinary research at the boundary between robotics, neuroscience and computer vision and is a multi-award winning educational entrepreneur. His research models the neural mechanisms in the brain underlying tasks like navigation and perception to develop new technologies in challenging application domains such as all-weather, anytime positioning for autonomous vehicles. He is also one of Australia’s most in demand experts in technologies including self-driving cars, robotics and artificial intelligence, and is a passionate science communicator. He currently holds the position of Professor at the Queensland University of Technology, as well as Australian Research Council Future Fellow, Microsoft Research Faculty Fellow and Chief Investigator at the Australian Centre for Robotic Vision.
John Paul Strachan
John Paul is a Master Technologist and research team leader at Hewlett Packard Labs in Palo Alto, CA. He runs the Rebooting Computing team that builds novel types of hardware accelerators from emerging device technology, with expertise spanning materials, device physics, circuits, architectures, benchmarking and building prototype systems. The team’s interests span applications in machine learning, network security, and optimization.
John Paul has degrees in physics and electrical engineering from MIT and a PhD in applied physics from Stanford University. He has over 50 patents, has authored or co-authored over 65 peer-reviewed papers, and been the PI in many USG research grants. He has previously worked on nanomagnetic devices for memory for which he was awarded the Falicov Award from the American Vacuum Society, and has developed sensing systems for precision agriculture in a company which he co-founded. He serves in many professional societies including IEEE IEDM ExComm, the Nanotechnology Council ExComm, past program chair and steering member of the International Conference on Rebooting Computing.
Dimitri Kusnezov
Dr. Dmitri Kusnezov received A.B. degrees in Physics and in Pure Mathematics with highest honors from UC Berkeley. Following a year of research at the Institut fur Kernphysik, KFA-Julich, in Germany, he attended Princeton University earning his MS in Physics and Ph.D. in Theoretical Nuclear Physics. At Michigan State University, he conducted postdoctoral research and then became an instructor.
In 1991, he joined the faculty of Yale University as an assistant professor in physics, becoming an associate professor in 1996. He has served as a visiting professor at numerous universities around the world. Dr. Kusnezov has published over 100 articles and a book.
He joined federal service at the National Nuclear Security Administration in late 2001 and is a member of the Senior Executive Service and is also a Visiting Researcher at Yale. He currently serves as Deputy Under Secretary for A.I. and Technology.
Catherine Schuman
Catherine (Katie) Schuman is an Assistant Professor at the University of Tennessee. Prior to her appointment at UoT, she was a Liane Russell Early Career Fellow at Oak Ridge National Laboratory (ORNL). She received her Ph.D. in Computer Science from the University of Tennessee in 2015, where she completed her dissertation on the use of evolutionary algorithms to train spiking neural networks for neuromorphic systems. Katie has a joint faculty appointment with the Department of Electrical Engineering and Computer Science at the University of Tennessee, where she, along with four other professors at UT, leads a neuromorphic research team made up of more than twenty faculty members, graduate student researchers, and undergraduate student researchers. Katie has over 30 publications as well as four patents in the field of neuromorphic computing. Katie has spoken on neuromorphic computing at over 25 conferences and workshops.
Alec Talin
A. Alec Talin received the B.A. degree in chemistry from the University of California, San Diego, CA, USA, in 1989 and the Ph.D. degree in materials science and engineering from the University of California, Los Angeles, CA, in 1995.,He is a Principal Member of technical staff with Sandia National Laboratories, Livermore, CA, an adjunct Fellow with the Center for Nanoscale Science and Technology, National Institute of Standards and Technology, Gaithersburg, MD, USA, and an adjunct Associate Professor of materials science and engineering with the University of Maryland, College Park, MD. Prior to joining Sandia in 2002, he spent six years as a Research Scientist with the Motorola Corporate Labs, Phoenix, AZ, USA. His research interests include charge transport in nanostructures, contacts, novel electronic materials, solid-state batteries, and photoelectrochemistry.
