Area of research
Electrical and Electronic Engineering · Cognitive Neuroscience
Research interest
Research interests include Advanced Memory and Neural Computing, Ferroelectric and Negative Capacitance Devices, Neural dynamics and brain function, and Neural Networks and Reservoir Computing.
Heterogeneous Embedded Neural Processing Units Utilizing PCM-Based Analog In-Memory Computing
Neuromorphic In-Context Learning for Energy-Efficient MIMO Symbol Detection
Baseline Drift Tolerant Signal Encoding for ECG Classification with Deep Learning
Accurate deep neural network inference using computational phase-change memory
Memristors—From In‐Memory Computing, Deep Learning Acceleration, and Spiking Neural Networks to the Future of Neuromorphic and Bio‐Inspired Computing
Mixed-Precision Deep Learning Based on Computational Memory
Experimental Demonstration of Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses
Low-Power Neuromorphic Hardware for Signal Processing Applications: A Review of Architectural and System-Level Design Approaches
A 250 mV Cu/SiO<sub>2</sub>/W Memristor with Half-Integer Quantum Conductance States
Efficient scrub mechanisms for error-prone emerging memories