Home Banner

Our lab is focused on designing and creating efficient hardware systems to meet the growing computational needs of Machine Learning and Artificial Intelligence. We pursue a Physics-to-Systems approach where we combine algorithmic understanding with tailored hardware and architectures. We try to map unique features of emerging materials to the needs of algorithms and applications to build natural and energy-efficient computing systems. Our research interests lie at the intersection of physics, computer science and electrical engineering. 

We believe that such an interdisciplinary approach connecting architectures and algorithms to materials and devices is essential in the new era of electronics driven by domain-specific hardware. 

This is in contrast to Moore’s Law-driven era that has centered around a single device, the field-effect transistor. The new era of electronics calls for a new kind of scientist who needs to be deep in one field but also broad enough to be able to make connections to related disciplines across the computing stack. 


 Join OPUS Lab!

We are recruiting!

 Research Areas

We extend algorithms and architectures that match features of emerging hardware to cater to the needs of computation.
Designing efficient circuits with new functionalities often involves mapping materials directly to applications.
We seek to translate emerging materials and phenomena into physics-based circuit models to design benchmark circuits.

 Recent News

January 11, 2023

Our group receives the prestigious NSF CAREER award to build hybrid probabilistic computers! 

January 4, 2023

We are thrilled to have UCSB sophomore Kyle Lee to join OPUS Lab as an undergraduate researcher!

December 9, 2022

IEEE Spectrum covers latest advances in probabilistic computing presented at the IEDM, featuring our paper and a history of p-bits.


October 31, 2022

Our collaborative paper with Shriram Ramanathan's group at Rutgers University is out in Nano Letters.

Congratulations Kemal Selçuk and Navid Anjum Aadit! 

October 17, 2022

OPUS Lab receives SRC support under the Hardware for AI program to develop scaled out probabilistic computing architectures! 

October 8, 2022

We are excited to have Shuvro Chowdhury who joins OPUS Lab as a postdoctoral researcher. 

September 15, 2022

Experimental evaluation of simulated quantum annealing with MTJ-augmented p-bits has been accepted to IEDM 2022! Congratulations Andrea, Navid, Kemal, Shawn and Keito. 

August 15, 2022

We are very excited to have Saleh Bunaiyan join OPUS lab!

July 16, 2022

We are thrilled to host Keito Kobayashi from Tohoku University as a visiting graduate student. 

July 5, 2022

We are excited to have Nihal Singh join our team!