Keren Zhu is currently a research assistant professor in the Department of Computer Science and Engineering at the Chinese University of Hong Kong. In 2022, he received his Ph.D. from the Department of Electrical and Computer Engineering at The University of Texas at Austin, USA. He earned his B.S. in Electrical Engineering with the highest distinction from the University of Wisconsin-Madison, USA, in 2016. Dr. Zhu’s research focuses on physical design automation, analog integrated circuit design automation, machine learning for EDA, and computing systems with emerging technologies. During his Ph.D. studies, Dr. Zhu was one of the key contributors to the development of MAGICAL, an open-source analog layout automation software. He has authored dozens of technical papers on electronic design automation, circuit design, and machine learning, which have been published in leading venues, as well as multiple book chapters. His research has received recognition through nominations for best paper awards at several conferences.
- Keren Zhu, Mingjie Liu, Yibo Lin, Biying Xu, Shaolan Li, Xiyuan Tang, Nan Sun, David Z. Pan: GeniusRoute: A New Analog Routing Paradigm Using Generative Neural Network Guidance. ICCAD 19.
- Hao Chen, Mingjie Liu, Xiyuan Tang, Keren Zhu, Abhishek Mukherjee, Nan Sun, David Z Pan: MAGICAL 1.0: An Open-Source Fully-Automated AMS Layout Synthesis Framework Verified With a 40-nm 1GS/s Δ∑ ADC. CICC 21.
- Keren Zhu, Hao Chen, Mingjie Liu, Xiyuan Tang, Nan Sun, David Z Pan: Effective Analog/Mixed-signal Circuit Placement Considering System Signal Flow. ICCAD 21.
- Mingjie Liu, Keren Zhu, Jiaqi Gu, Linxiao Shen, Xiyuan Tang, Nan Sun, David Z Pan: Towards Decrypting the Art of Analog Layout: Placement Quality Prediction via Transfer Learning. DATE 20.
- Keren Zhu, Mingjie Liu, Hao Chen, Zheng Zhao, David Z Pan: Exploring Logic Optimizations with Reinforcement Learning and Graph Convolutional Network. MLCAD 20.