Academic Collaborations

Dan Alistarh’s research is on algorithms for efficient machine learning and high-performance computing, with a focus on scalable inference and training. 

David Z. Pan’s research interests include AI for chip design, design automation for digital, analog, RF, and photonic ICs, and design-technology-systems co-optimizations.

Juan Felipe Carrasquilla’s research operates at the intersection of condensed matter physics, machine learning, and quantum computing, specifically focusing on using neural networks and quantum Monte Carlo simulations to identify phases of matter and validate quantum devices. 

Tim Rogers’ research at Purdue centers on computer architecture, software systems, and performance modeling for programmable hardware accelerators such as GPUs. His work tackles key challenges in computing performance and energy efficiency, helping to shape future AI hardware and software.

Luisa Verdoliva’s scientific interests are in the field of image and video processing, with main contributions in the area of multimedia forensics and deepfake detection.

Dale Durran is exploring data-driven physics-constrained AI models for sub-seasonal, seasonal, and longer-lead time forecasts and simulation.

As a key researcher in the NanoHeat Lab, Dr. Asheghi’s work includes high-impact studies on phonon transport in silicon, advanced microcoolers for electronics, and phase-change memory technologies.

Ken Goodson specializes in heat transfer and energy conversion with applications to electric vehicles, data centers, and portable electronic devices.