Computational Intelligence: Cognitive, Dynamic and Adaptive Architectures
Speaker: Dr. Robinson Pino
Faculty Host: Professor Helen Li.
Abstract
Parallel intelligent computing architectures offer exciting possibilities for reaching higher levels of performance and capacity. However, as amazing as the technological possibilities are so are the challenges for its practical integration within complex computing systems. For example, neuromorphic computing promises to allow for the development of intelligent systems able to imitate natural neuro-biological processes. This is achieved by artificially re-creating the highly parallelized computing architecture of the mammalian brain. In particular, neuromorphic computers are suitable for applications in pattern recognition, i.e. image, voice, etc. In order to achieve high levels of intelligence within systems, neuromorphic computing must exploit novel complex materials and structures to achieve very large scale integration with highly parallel and dense neural architectures. Our recent research efforts at the Air Force Research Laboratory (AFRL), Information Directorate, focus on the development of neuromorphic computational devices, mathematical models, novel materials, and computational applications to develop neuromorphic computing processors. However, in order to achieve nanoscale device powered technologies, we must develop design methodologies that take advantage of the highly non-linear and environment sensitive physical behavior of such novel devices. Therefore, as we work to develop next generation nanotechnologies, we must address technological challenges such as modeling, characterization, integration, manufacturability, and resources. This talk will focus on the technology challenges that we are seeking to overcome to enable nanoscale parallel computing architectures.
About the Speaker
Dr. Robison E. Pino is a Senior Electronics Engineer for the United States Air Force Research Laboratory (AFRL) where he leads as principle scientist the Computational Intelligence and Neuromorphic Computing research efforts. Dr. Pino's expertise is within technology development, management, modeling, and characterization. Dr. Pino’s professional experience include working at IBM Microelectronics as an Advisory Scientist/Engineer Development of CMOS technologies and as Business Analyst at IBM's Photomask business unit where he was responsible for development and manufacturing spending, capacity planning, lean manufacturing, and business process automation. In addition, Dr. Pino has been an adjunct professor at the University of Vermont teaching graduate and undergraduate courses in Electrical Engineering, 2007-2009. Dr. Pino won the AFRL Early Career Award in 2012, was named Distinguished Lecturer of IEEE, EDS, in 2010, AFRL Information Directorate Scientist/Engineer of the Year in 2011, named Top 200 Most Influential Hispanics in Technology by HE&IT Magazine in 2011 and IEEE Mohawk Valley Section Engineer of the Year in 2011. Dr. Pino received the Ph.D. and M.S. degrees in Electrical Engineering from Rensselaer Polytechnic Institute, Troy, NY in 2005 and 2003 and B.E. (E.E.) degree with honors from the City University of New York, City College, in 2002.