Hanqing Zhu

I am a final-year ECE Ph.D. candidate at University of Texas at Austin, under the supervision of Prof. David Z. Pan (Fellow of ACM, IEEE, SPIE) and Prof. Ray T. Chen (Fellow of NAI, IEEE, OSA, SPIE). I work closely with Prof. Zhangyang "Atlas" Wang at UT Austin and Prof. Jiaqi Gu at ASU.

Previously, I received the B.Eng. degree in microelectronics science and engineering from Shanghai Jiaotong University with highest honor, in 2020.

Email / Google Scholar / Github / CV

Research

My research interests primarily center on efficient AI computing, focusing on both Emerging ML Hardware/Systems and Hardware-aware Efficient AI Algorithms. I have published papers in top conferences in design automation, computer architecture, and machine learning, such as NeurIPS, HPCA, DAC, ICCAD, and TCAD.

Hardware-Software Co-Design for Emerging AI Hardware and Computing Systems:
E.g., Lightening-Transformer (HPCA'24), PACE (NeurIPS'24).
Efficient training and inference for large foundation models:
E.g., APOLLO (arXiv'24), Efficient Pre-LN Transformers (NeurIPS'23 Spotlight).

Selected Publications

* denotes equal contribution. For the full publication list, please refer to my Google Scholar .

Education

The University of Texas at Austin

Ph.D. in Electrical and Computer Engineering (2020 - 2025)

First year (2020-2021) conducted part-time in China due to COVID-19

Advisor: Prof. David Z. Pan (Fellow of ACM, IEEE, SPIE)

Shanghai Jiao Tong University

B.Eng. in Microelectronics Science and Engineering (2016 - 2020)

Graduated with Highest Honors

Overall GPA: 3.81/4.00, Ranking: 2/57

Work Experience

Meta AI, CA, USA
Research Scientist Intern, Efficient Large-scale Training
Advisor: Dr. Jinwon Lee

Lightelligence Inc., MA, USA
Software Research Intern, Low-bit Noise-aware Training for Photonic AI Chips
Advisor: Dr. Weifeng Zhang

Google Brain (now Google Deepmind), CA, USA
Student Researcher, Google Brain, RL-based Chip Placement
Advisor: Dr. Joe Jiang

Services

Conference Reviewer:
- ICML, NeurIPS, ICLR, AAAI, DAC, ICCAD, FPGA, AICAS
Journal Reviewer:
- TNNLS, TCAD, Photonic Network Communications

Talks

Towards Reliable and Self-Learnable Photonic Neural Network from the Lens of Software-Hardware Co-design, Lightelligence,, 2023

Honors & Awards

Texas ECE Graduate Achievement Award , UT Austin 2024
UT Graduate School Continuing Fellowship Nomination (1 of 2 nominees in the entire ECE department), UT Austin 2024
1st Place in IEEE/ACM MLCAD FPGA Macro-Placement Contest, MLCAD, 2023
MLSys Student Travel Award, MLsys 2023
Winner of Robert S. Hilbert Memorial Optical Design Competition, Synopsys, 2022
DAC Young Fellow, 2021
Shanghai Outstanding Graduate, 2020
Hongyi Scholarship, 2019
Outstanding Undergraduate Scholarship, 2019
Samsung Scholarship Scholarship, 2018
Zhiyuan College Honors Scholarship, 2018
1st Prize, National Mathematical Contest in Modeling, hanghai Division, 2018
Academic Excellence Scholarship, 2017-2019

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