I am a 4th-year PhD student at The University of Hong Kong (HKU), where I am privileged to be advised by Prof. Han Wang and Prof. Zhongrui Wang. My research lies at the intersection of advanced semiconductor devices and next-generation Edge AI computing systems, with a specific focus on in-memory computing. My current work involves the circuit-level optimization of RRAM-based in-memory computing systems, aiming to overcome the hardware bottlenecks that limit efficient inference and on-device learning at the edge.

Beyond the chip itself, I build the embedded systems around it, with hands-on experience in circuit design, hardware-software co-design, and control system simulation, drawing on my earlier background in power electronics and motor control. I aim to empower traditional industrial frameworks by integrating the intelligent capabilities of in-memory computing, leveraging the synergistic strengths of both to build smarter and more efficient edge computing systems.

News

Education

The University of Hong Kong (HKU) 2022.09 - Present

Ph.D. Student at Department of Electrical and Computer Engineering (ECE)

Topics: In-memory computing, resistive memory and analog circuit design

Advisor: Prof. Zhongrui Wang and Prof. Han Wang

Huazhong University of Science and Technology (HUST) 2019.09 - 2022.06

M.S. at Center for Advanced Electrical Machine and Drives (CAEMD)

Topics: Active magnetic bearing, control system, power electronics

Advisor: Prof. Dong Jiang and Prof. Ronghai Qu

Huazhong University of Science and Technology (HUST) 2015.09 - 2019.06

B.S. at School of Electrical and Electronic Engineering (SEEE)

Selected Publications

(Below is a highlight, see the full list in the Publications tab)

1. Jichang Yang, et al. “Resistive memory-based neural differential equation solver for score-based diffusion model” Nature Communications, 2026.
2. Jichang Yang, et al. “Conditional Diffusion Model Acceleration with First-Demonstrated RRAM-Based In-Memory Neural Differential Equation Solver” IEEE International Electron Devices Meeting (IEDM), 2024.
3. Hegan Chen†, Jichang Yang†, et al. “Continuous-time digital twin with analog memristive neural ordinary differential equation solver” Science Advances, 2025.
4. Yi Li†, Jichang Yang†, et al. “Adaptive Redox Resistive Memory Programming for Efficient and Robust Class-Incremental Learning” Advanced Materials, 2026.

Contact

📧 Email: yangjc100@connect.hku.hk
📍 Office: [Room 324/Haking Wong Building], HKU, Hong Kong