Welcome to the Intelligent Computing Architecture & Nanosystem (ICAN) Group at UC Riverside.
The ICAN Group is directed by Prof. Wantong Li in the Department of Electrical and Computer Engineering.

We explore interdisciplinary research opportunities in integrated circuits, computing hardware, heterogeneous integration, and artificial intelligence. Our intellectual pursuit is to develop efficient and robust machine intelligence for the edge, including in challenging environments. By conducting innovative research across the stack, we also aim to drive advancements in the emerging application spaces of smart sensing, healthcare, and autonomous systems.

Research Interests

  • Memory-Centric Computing
    • In/near-memory computing, in/near-sensor computing, emerging memory and post-CMOS technologies
  • Reliable and Robust IC Design
    • PVT-robust circuits, fault tolerance, hardware security, cryogenic microelectronics
  • Heterogeneous Integrated Nanosystems
    • Monolithic/heterogeneous 3-D systems, chiplets and system-in-package, BEOL circuits, thermal management
  • SW/HW Co-Design for Embedded AI
    • Efficient tiny ML, AI-infused medical and autonomous systems, intelligent sensor data reduction


Opportunities

We are looking for talented and motivated students to join ICAN. There are multiple fully-funded Ph.D. positions for Spring and Fall 2025. We also welcome Undergraduate and Master’s researchers. Please read this page for more details.

Recent News

Nov, 2024 Wantong Li joins Department of Computer Science and Engineering (CSE) as a Cooperating Faculty member.
Oct, 2024 Wantong Li is invited to serve as a conference review committee member for DAC, ISCAS, and VLSID.
Aug, 2024 Our paper “MAC-ECC: In-Situ Error Correction and Its Design Methodology for Reliable NVM-Based Compute-in-Memory Inference Engine” is awarded the Best Paper with honorable mentions by JETCAS.
Jul, 2024 Wantong Li joins UC Riverside Department of Electrical and Computer Engineering (ECE) as a tenure-track Assistant Professor.
Apr, 2024 Our paper “Machine Learning Algorithm Co-Design for a 40 nm RRAM Analog Compute-in-Memory Accelerator” is awarded the Best Paper by ORSS.
Jan, 2024 Wantong Li gives an invited talk “Efficient, Robust, and Heterogeneous Compute-in-Memory for Edge Intelligence” in the CESG seminar series of Texas A&M University.
Nov, 2023 Wantong Li presents “Enabling Ultra-Low Power Ultrasound Imaging with Compute-in-Memory Sparse Reconstruction Accelerator” at BIOCAS.
Sep, 2023 Our paper “H3DAtten: Heterogeneous 3D Integrated Hybrid Analog and Digital Compute-in-Memory Accelerator for Vision Transformer Self-Attention”, published in TVLSI, is awarded the Best Paper by SRC CHIMES Center.
Aug, 2023 Our paper “A Reconfigurable Monolithic 3D Switched-Capacitor DC-DC Converter with Back-End-of-Line Oxide Channel Transistor” wins the Best Paper Award at MWSCAS.
Jul, 2023 Wantong Li presents “Efficient and Reliable Vision Accelerator with Compute-in-Memory” at DAC Ph.D. Forum.
Jul, 2023 Wantong Li gives an invited talk “Efficient & Reliable RRAM-based Compute-in-Memory for Edge Intelligence” at In-Memory Architectures and Computing Applications Workshop (iMACAW) @ DAC.
Apr, 2023 Wantong Li presents “Efficient and Reliable Vision Accelerator with Compute-in-Memory” at DATE Ph.D. Forum.
Mar, 2023 Wantong Li and Xitie Zhang (advised by Prof. Shaolan Li) are awarded the inaugural INSPIRE Fellowship on the collaborative proposal “Enabling Ultra-Low Power Portable Ultrasound Imaging: Adaptive Sub-Sampled Transceiver with Model-Based Deep Learning and Compute-in-Memory Accelerator”.
Sep, 2022 Wantong Li presents “A 40nm RRAM Compute-in-Memory Macro with On-Chip Write-Verify, Temperature-Independent ADC References, and In-Situ Error Correction” at SRC TECHCON.
Aug, 2022 Wantong Li presents “RRAM-based Compute-in-Memory Macro with Temperature-Independent ADC References and Parallelism-Preserving MAC-ECC” at SRC ASCENT Center annual review.
Jun, 2022 Our paper “A 40nm Analog-Input ADC-Free Compute-in-Memory RRAM Macro with Pulse-Width Modulation between Sub-arrays” is recognized as a highlight paper at Symposium of VLSI.
Jan, 2022 Wantong Li gives an invited talk “In-Situ Error Correction for Reliable NVM-Based CIM Inference Engines” in the seminar series of SRC ASCENT Center.
Oct, 2021 Wantong Li presents “A 40nm MLC-RRAM CIM Macro with Sparsity Control, On-Chip Write-Verify, and Temperature-Independent ADC References” at IBM AI Hardware Forum.


Contact

Dr. Wantong Li
Marlan and Rosemary Bourns College of Engineering
Department of Electrical and Computer Engineering
Riverside, CA 92507