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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

July 11, 2023

OPUS undergraduate researcher Tianrui Hu is recognized as the outstanding CE senior. 

“I am honored to receive the award, and I humbly believe that this is a recognition of my hard work,” said Hu. “This is just the beginning of my career in engineering. It is too early to celebrate; let us move forward!”

July 4, 2023

We are thrilled to have Abdelrahman join our team.

 

May 29, 2023

We are thrilled to welcome Haruna Kaneko from Tohoku University as a visiting researcher to our lab.

 

May 26, 2023

OPUS Lab in collaboration with Northwestern University and the Zheng Zhang Lab at UCSB has received NSF funding to investigate the neural network verification problem with probabilistic computers. 

May 11, 2023

Congratulations to Sid Kannan for this exceptional achievement! As an IBM Undergraduate Research Program Scholar, Sid joins a prestigious group of individuals recognized by the Semiconductor Research Corporation to pursue undergraduate research. 

May 11, 2023

Samsung Global Research Outreach renews funding to collaborate with OPUS Lab to work on energy-efficient AI hardware. 

April 28, 2023

Shuvro's paper on accelerating quantum Monte Carlo simulations with p-computers is out in Communications Physics. 

April 20, 2023

We are thrilled to have Srijan join the team.

April 11, 2023

PillarQ, a research news publication interviews Kerem about the NSF CAREER award, probabilistic and quantum computing. 

April 10, 2023

We are excited to have Sid join OPUS as an undergraduate researcher.