Chakma receives departmental research award

PhD Student Gangotree Chakma received one of the EECS Department's outstanding graduate researcher awards and the annual Gonzalez EECS Departmental Awards Dinner. Chakma, a productive researcher focusing on memristive circuits, has been an author on many of our group's publications, including:

• Energy and Area Efficiency in Neuromorphic Computing for Resource Constrained Devices
• Applying Memristors Towards Low-Power, Dynamic Learning for Neuromorphic Applications
• Memristive Mixed-Signal Neuromorphic Systems: Energy-Efficient Learning at the Circuit-Level
• A Programming Framework for Neuromorphic Systems with Emerging Technologies
• A Mixed-Signal Approach to Memristive Neuromorphic System Design
• A Synchronized Axon Hillock Neuron for Memristive Neuromorphic Systems
• Circuit Techniques for Online Learning of Memristive Synapses in CMOS-Memristor Neuromorphic Systems
• A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers
• Applying Memristors Towards Low-Power, Dynamic Learning for Neuromorphic Applications
• A Hafnium-Oxide Memristive Dynamic Adaptive Neural Network Array

Chakma