Microelectronics is an indispensable driving force in every aspect of our lives, from mobile phones to satellites, household robots to autonomous vehicles, and personal healthcare to education infrastructure. After successful scaling and growth for several decades, microelectronics now demands fundamentally new innovations inspired by both physical and computational sciences.
Welcome to the Microelectronics Co-design Research Group (MEC) at the University of Minnesota! Our research applies new understandings in computer engineering and semiconductor technology, focusing on hardware-algorithm co-design for energy-efficient computing. Through physical analysis and integrated circuit design, our goal is to advance the frontier in computing hardware, paving the path toward future intelligent systems.
Group News
March 2025: Sharad won the Best Poster Award, Theme 3, at the CoCoSys annual review. This poster, "A 22nm Reconfigurable Chiplet for FFT and AI Inference," is in collaboration with John, Jacob, Nikhil, Ashish, Gopi, Jeff, and Jae-sun. Congratulations to the team!
March 2025: Gopi completed his Ph.D. and joins AMD. Congratulations!
February 2025: Zhenyu completed his Ph.D. and joins Ambarella. Congratulations!
December 2024: Pragnya's research on chiplets and heterogenous integration is highlighted in the Spotlight on Research by CoCoSys.
October 2024: Our work on HISIM is the winner of Embedded Systems Software Competition (ESSC) at 20th ACM/IEEE Embedded Systems Week (ESWEEK). Congratulations!
July 2024: HISIM, a fast simulation tool for 2.5D/3D system design exploration, is released at GitHub: github.com/mec-UMN/HISIM
June 2024: The second Workshop on Chiplet-based Heterogeneous Integration and CO-design (CHICO) is organized at Design Automation Conference (DAC).
May 2024: Prof. Cao is appointed as the Louis John Schnell Professor of Electrical and Computer Engineering.
April 2024: Jingbo completed his Ph.D. and joins Intel. Congratulations!
February 2024: Prof. Cao visit the University of Notre Dame and present at the department seminar of Electrical Engineering.
January 2024: Prof. Cao presents an invited talk at Asia and South Pacific Design Automation Conference (ASP-DAC), South Korea, on 3D heterogeneous integration.
January 2024: We receive a new grant to collaborate with Sandia National Labs on spiking vision transformers.
December 2023: Our paper on transformer-based saliency and super-resolution is accepted by the AAAI Conference on Artificial Intelligence.
December 2023: Our work on predictive modeling for 14nm cryogenic CMOS design is published in IEEE Journal of Exploratory Solid-State Computational Devices and Circuits.
November 2023: Our 65nm design on 3D in-sensor computing is published at IEEE Asian Solid-State Circuits Conference (ASSCC).
October 2023: We contribute to two book chapters:
“In-memory computing for AI accelerators: Challenges and solutions,” in Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing, Springer Nature
“Overview of recent advancements in deep learning and artificial intelligence,” in Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning, IEEE Press and Wiley
September 2023: Prof. Cao delivers the keynote on 2.5D/3D simulation at the DOT-PIM workshop, ESWEEK.
July 2023: The first Workshop on Chiplet-based Heterogeneous Integration and Co-design (CHICO) is organized at DAC.
May 2023: Prof. Cao delivers the IEEE CAS Distinguished Lecture on reliable in-memory computing to the Lille Chapter, France.
April 2023: We receive a new grant by the DARPA Next Generation Microelectronics Manufacturing (NGMM) program, Phase 0.
January 2023: We join the DARPA/SRC JUMP 2.0 Center for the Co-Design of Cognitive Systems (CoCoSys)!
December 2022: Prof. Cao delivers the IEEE CAS Distinguished Lecture on reliable in-memory computing to the Singapore Chapter, Singapore.
October 2022: Zhenyu receives the Best Student Poster Award at the 5th IBM AI Compute Symposium.
August 2022: Gokul completed his Ph.D. and joins Meta. Congratulations!
March 2022: Our collaborative paper on sparse training with crossbars receives the Best IP Award at Design, Automation, and Test in Europe.