Jichang Yang

Jichang Yang

PhD Student at Department of Electrical and Computer Engineering, HKU

Jichang Yang (杨佶昌)

I am a 4th-year PhD student at The University of Hong Kong (HKU), where I am privileged to be advised by Prof. Zhongrui Wang and Prof. Han Wang. My research lies at the intersection of advanced semiconductor devices and next-generation artificial intelligence, 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 hardware bottlenecks in energy-efficient AI deployment.

Also with a background in power electronics and motor control, I have developed capabilities in circuit design and control system simulation. 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 systems.

News

[2024.12] 🎉 Presented an oral paper at IEDM2024.
[2024.10] 🏆 Awarded Best Poster Award in 2024 Nature Conference on Neuromorphic Computing.
[2024.09] 🏆 Awarded Best TA Award for the 2023-24 academic year.
[2022.09] 🏆 Awarded Hong Kong PhD Fellowship (HKPF) and HKU Presidential PhD Scholarship (HKU-PS).
[2022.09] 🎉 I joined The University of Hong Kong as a Ph.D. student.

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. “Conditional Diffusion Model Acceleration with First-Demonstrated RRAM-Based In-Memory Neural Differential Equation Solver” IEEE International Electron Devices Meeting (IEDM), 2024.
  2. Hegan Chen†, Jichang Yang†, et al. “Continuous-time digital twin with analog memristive neural ordinary differential equation solver” Science Advances, 2025.

Contact

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