Associate Professor, ECE
New Jersey Institute of Technology
Date: Thursday August 3, 2017
Time: 11:00 am
Place: 750 CEPSR
Host: John Kymissis
The new iPhone processor has more than 3 billion transistors, and can perform more than 300 GFLOPS (300 billion floating point operations per second), consuming less than 10 Watts. The human brain, with more than 100 billion neurons, is estimated to be capable of performing an astounding 20 Million GFLOPS equivalent, while consuming a mere 20 Watts! Clearly, nature’s methods and engines for information processing are far superior to the best man-made systems. How does computation and learning emerge in neural networks that communicate using spikes through adaptive synapses? Is it possible to build computing systems that mimic the cognitive abilities of the brain, at the size and scale of biology? These questions need to be answered to realize the long-standing goal of reverse engineering the brain and develop the next generation of information processing systems. In this talk, I will discuss some new algorithms, devices and systems that we have engineered in our laboratory, inspired by the brain.
Bipin Rajendran received a B. Tech degree from I.I.T. Kharagpur, in 2000, and M.S. and Ph.D. degrees in Electrical Engineering from Stanford University, in 2003 and 2006, respectively. He was a Master Inventor and Research Staff Member at IBM T. J. Watson Research Center in New York during 2006-’12 and a faculty member in the Electrical Engineering Department at I.I.T. Bombay during 2012-’15. His research focuses on building algorithms, devices and systems for braininspired computing. He has authored over 60 papers in peer-reviewed journals and conferences, and has been issued 55 U.S. patents. He is currently an Associate Professor in the Department of Electrical & Computer Engineering at New Jersey Institute of Technology.