Weiyan Zhang

About Me

I am an AI and computer systems researcher specializing in ML, LLMs, computer architecture, and embedded systems. I obtained my Bachelor’s and Master’s degrees in Electrical Engineering from Beijing Institute of Technology and the University of Bremen, respectively.

I previously worked as a researcher in the Group of Computer Architecture at the University of Bremen , and in the Cyber-Physical Systems (CPS) research department at the German Research Center for Artificial Intelligence (DFKI) . My research focused on applying ML and LLMs to performance modeling and analysis of embedded software, particularly for RISC-V processors.

Currently, I am seeking opportunities in industry where I can apply my research experience to AI engineering and software development.

Publications

• Sallar Ahmadi-Pour, Weiyan Zhang, and Rolf Drechsler. Timed-VP: Early and Configurable Timing Estimation Models for Virtual Prototypes. Available at SSRN 4916829.
• Weiyan Zhang, Muhammad Hassan, and Rolf Drechsler. LLM-assisted Performance Estimation of Embedded Software on RISC-V Processors . In 28th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS), pp. 7–12, IEEE, 2025.
• Weiyan Zhang, Mehran Goli, Muhammad Hassan, and Rolf Drechsler. Efficient ML-Based Performance Estimation Approach across Different Microarchitectures for RISC-V Processors . In 26th Euromicro Conference on Digital System Design (DSD), pp. 693–699, IEEE, 2023.
• Weiyan Zhang, Mehran Goli, Alireza Mahzoon, and Rolf Drechsler. ANN-based Performance Estimation of Embedded Software for RISC-V Processors . In International Workshop on Rapid System Prototyping (RSP), pp. 22–28, IEEE, 2022.
• Weiyan Zhang, Mehran Goli, and Rolf Drechsler. Early Performance Estimation of Embedded Software on RISC-V Processor using Linear Regression . In 25th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS), pp. 20–25, IEEE, 2022.

Contact

📧 weiyan@weiyanzhang.com 💻 GitHub | 🔗 LinkedIn | 📚 Google Scholar