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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

May 13, 2022

OPUS Undergraduate Researcher Andrea Ni has been selected as a Texas Instruments URP Scholar by SRC. Congratulations Andrea!

February 22, 2022

Andrea and Navid's paper shows how invertible logic with p-bits can be useful to solve maximum satisfiability problems using sophisticated optimization algorithms such as parallel tempering. 

January 31, 2022

We are awarded an ONR grant to work on Scalable Probabilistic Computers for Optimization and Quantum Simulation.

January 25, 2022

We are thrilled to welcome Andrea as a visiting PhD student! 

December 20, 2021

We are thrilled to have Shaila Niazi join our team!

November 1, 2021

OPUS Lab receives support from SAMSUNG in collaboration with Tohoku University. 

September 24, 2021

OPUS Lab, in collaboration with Prof. Luke Theogarajan, receives IEE seed funding to build a scaled up p-computer using CMOS technology. 

September 18, 2021

Navid's paper "Computing with Invertible Logic: Combinatorial Optimization with Probabilistic Bits" has been accepted to the International Electron Devices Meeting (IEDM), 2021.  

July 29, 2021

We are thrilled to have Kemal Selçuk join the OPUS lab from Sabanci University. 


July 7, 2021

Andrea is investigating novel device opportunities for probabilistic computing.