Research Areas
We investigate machine learning (ML)-based methodologies for the design of advanced computing systems using emerging technologies to enable energy-efficient, high-performance, and reliable inference and training of emerging ML models. Our research focuses on cross-layer hardware and software co-design spanning across applications, architecture, and advanced packaging.
Specific topics include:
Design of advanced computing systems using emerging technologies (e.g., compute-in-memory, silicon photonics)
ML for design space exploration and dynamic resource management in computing systems
Design for reliability in advanced packaging (e.g., 2.5D chiplets and 3D integration)
Emerging Compute Substrates
EDA challenges in Compute-in-memory to Quantum computing
Neuromorphic Computing
Ultra-low power computing at the edge using Spiking Neural Networks
Advanced Packaging
Tackling thermomechanical issues, power delivery network, etc in advanced packaging
Our Latest Updates
Prospective Students
Our Partners
