Microelectronics and Integrated-Systems with Neuro-centric Devices (MIND) Lab
Neuromorphic Computing and Artificial Intelligence
Artificial Intelligence (AI) has caught significant research attention. However, AI algorithms are compute resource intensive. Therefore, much emphasis has been devoted on developing specialized neuromorphic System on Chip (SoC) for accelerating AI recently. Some examples of these neuromorphic-SoC include Google’s TPU, Intel’s Nirvana and Loihi, and IBM’s TrueNorth. In spite of these significant advances, the performance of these processors are limited by the lack of novel reconfigurable memory devices that can mimic the adaptive characteristics of biological synapses. MIND lab researchers have invented new type of memory devices, referred to as, Low-Energy Evolutionary Channel Electronic Synapses (LEECHES) that can provide lucrative options for neuromorphic SoC. The student working on this project will work on this cutting-edge technology and develop neuromorphic SoC utilizing these novel memory devices. The student will perform the following tasks:
- Testing and Modeling of LEECHES in Verilog/VHDL
- Modeling and simulation of neural circuit modules around LEECHES
- Implementation of learning algorithms and performance evaluation of this novel neuromorphic SoC
- Publication and presentations.
- Training data collection on drones fitted with cameras and multiple sensors.
Trusted and Secured Microelectronics Hardware
Due to complex supply-chain of microelectronics integrated circuits (IC) design and fabrication, hardware security has emerged out to be one of the prime concerns. This project seeks to develop novel ways to design and fabricate secure microelectronics circuits using emerging nanoelectronics logic and memory devices. The students will be involved in the design of ICs, simulations, fabrication, and testing. A fundamental question we will try to answer is how can design itself be made more trust-worthy and resilient? Can emerging nanoelectronic memory and logic devices offer any inherent benefit in this area?
Professor, CEAS - Electrical and Computer Engineeri