Rashmi Jha | Department of Electrical Engineering and Computer Sciences
Laptops, smartphones, tablets, wearables, supercomputers but what next? How about making these devices think and compute like a human-brain? While computers today are extremely good at general purpose computing tasks, a human-brain outperforms them when it comes to performing complex multi-faceted tasks such as navigation, emotion recognition, extracting useful information based on surrounding activities, and providing interventions to the people in need when it is necessary. To address some of these complex issues in our society today, the next generation of microprocessors have to learn, evolve, and think like a human-brain.
Dr. Rashmi Jha and her research group in Emerging Devices for Advanced Computing Systems (EDACS) lab at the University of Cincinnati are developing the next generation of processors that can think like human-brains. The research involves understanding the cortical circuits in the brain and then developing nanoelectronic devices that can perform brain-inspired computing at ultra-low energy consumption. This is a challenging task because the brain is a complex network of billions of neurons interconnected via trillions of reconfigurable synapses. The exact mechanism behind learning, memory formation, and development of cortical circuits is still very much under study. In fact, reverse engineering the brain has been identified as a grand challenge by the National Academy of Engineering (NAE). These unknowns make our research intriguing and exciting.
Our lab is involved in developing neuro-inspired components including artificial neurons, synapses, and interconnects by exploiting the unique characteristics of nanoelectronic and nano-magnetic devices and materials. The ultimate goal is to integrate these neuro-inspired nano-devices in a brain-inspired architecture and demonstrate an intelligent and secured computing platform for ultra-low power implantable and wearable sensors, Internet of Things (IoT), Smart Phones, Robots, Smart and Connected Vehicles, and personal assistive devices.
Our research also explores avenues to train biological neuronal populations by interfacing with artificial cortical circuits to understand the underlying mechanisms of learning in biological systems for applications in not only computing areas but also for neural rehabilitations. The research is currently funded by a CAREER award and a Secure and Trustworthy Cyberspace (SaTC) award from National Science Foundation. The research aligns closely with the recent announcements from the Office of Science and Technology Policy in the areas of Nanotechnology-Inspired Grand Challenge for Future Computing.
For more information about this grand challenge, visit https://www.whitehouse.gov/blog/2015/10/15/nanotechnology-inspired-grand-challenge-future-computing.