Education
- Ph.D. in Computer Engineering, Duke University, 2022
- Advisor: Prof Yiran Chen, Prof Hai Li.
- Grade: 3.94/4.0.
- B.Eng. in ECE, City University of Hong Kong, 2017
- First Class Honours. Full Tuition Scholarship.
- Major Grade: 4.16/4.3.
Service
- Technical Program Committee Member of ICCAD 2023
- Technical Program Committee Member of ASP-DAC 2023
- Seminar Chair, IEEE CEDA Hong Kong, 2023
- Publicity Chair, IEEE CEDA Hong Kong, 2022
- Reviewer of ACM TODAES (Distinguished Reviewer), ACM JETC, ACM TECS, Springer JCST
- Reviewer of IEEE TCAD, IEEE TCAS-I, IEEE ESL, IEEE Design & Test, IEEE CAL, NeurIPS
Work Experience
- Part-time EDA Administrator, Duke University, 2020-2022
- Purchasing and providing help on all EDA tools for teaching and research purposes at Duke University.
- Research Intern, Arm, June 2020 – Nov 2020
- Advisor: Xiaoqing Xu, Shidhartha Das, Brian Cline
- Developed the first runtime on-chip power monitor that simultaneously achieves per-cycle resolution and less than 1% area overhead without compromising accuracy.
- The overall framework automatically generates training data, develops the model, and constructs the power monitor with minimum designer interference.
- It is verified on multiple industry-standard CPU cores including ARM Neoverse N1 and Cortex-A77.
- Software Engineer Intern, Synopsys, May 2019 – Aug 2019
- Advisor: Anand Rajaram, Min Pan, Aiqun Cao
- Developed a light-weighted linear model to estimate transition violation on the clock tree.
- The model is integrated into IC Compiler II and proves to improve clock tree quality by guiding CTS with early feedback.
- Research Intern, Nvidia, Sep 2018 – Dec 2018
- Advisor: Haoxing (Mark) Ren, Brucek Khailany
- Developed a customized CNN model for IR drop prediction. By incorporating switching time into power map features, this is the first design-independent estimator for both vector-based and vectorless IR drop.
- After integrating it into their in-house IR mitigation flow, hotspots in latest designs are reduced by 30%.
- Software Engineer Intern, Cadence, June 2018 – Aug 2018
- Advisor: Jie (Jack) Chen, Weibin Ding
- Developed deep neural network models for very early routability prediction even before the placement optimization. This is an early effort on routability estimation in the EDA industry.
Teaching Experience
- Instructor of ELEC 2350, HKUST, 2023
- ELEC 2350: Introduction to Computer Organization and Design (Undergraduate)
- TA of ECE 586, Duke University, 2021
- ECE 586: Vector Space Methods with Applications. (Graduate)
- TA of ECE 350, Duke University, 2021
- ECE 350: Digital Systems. (Undergraduate)
- EDA Supporter of ECE 532, Duke University, 2021
- ECE 532: Analog Integrated Circuit Design. (Graduate)
- EDA Supporter of ECE 539, Duke University, 2021
- ECE 539: CMOS VLSI Design Methodologies. (Graduate)