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Hanqing Zhu

Chinese Name

University of Texas at Austin

Email  /  Google Scholar  /  Github  /  CV

About Me

I am a final-year Ph.D. candidate in Electrical Computer Engineering 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 on efficient AI algorithms at UT Austin and Prof. Jiaqi Gu on emerging ML hardware at ASU.

Previously, I received the B.Eng. degree in Microelectronics Science and Engineering from Shanghai Jiaotong University with highest honor, in 2020. I grew up in a small town in southwest China, where I received my education pre college.

I was recognized as one of the ML and Systems Rising Stars in 2025 (38 out of 150+). [More Honors]

Recent Updates: I will join Meta as Research Scientist Intern this summer to study Llama Foundation Models Efficiency, under supervision of Dr. Tijmen Blankevoort.

Research Interests

My research interests lie in Efficient AI computing, focusing on Efficient ML Hardware/Systems and Efficient AI Algorithms with Hardware/Systems Awareness. I firmly believe that the co-design of hardware and algorithms is key to unlocking the ultimate efficiency in AI computing, shaping my expertise across both domains.

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

ML and System Rising star (2025), Graduate School Continuing Fellowship Nomination (1 of 2 in the ECE department), Texas ECE Graduate Achievement Award

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

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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

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Work Experience

Meta AI, CA, USA
Research Scientist Intern, Efficient Large-scale Training
Advisor: Dr. Jinwon Lee
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Lightelligence Inc., MA, USA
Software Research Intern, Low-bit Noise-aware Training for Photonic AI Chips
Advisor: Dr. Weifeng Zhang
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Google Brain (now Google Deepmind), CA, USA
Student Researcher, Google Brain, RL-based Chip Placement
Advisor: Dr. Joe Jiang
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Selected Publications
Full publication list at Google Scholar

I published papers across top conferences in design automation, computer architecture, and machine learning, e.g., MLSys, HPCA, Neurips, ICCV, DAC, ICCAD, TCAD. (* denotes equal contribution.)

Conferences

APOLLO: SGD-like Memory, AdamW-level Performance
Hanqing Zhu*, Zhenyu Zhang*, Wenyan Cong, Xi Liu, Sem Park, Vikas Chandra, Bo Long, David Z Pan, Zhangyang Wang, Jinwon Lee
MLSys 2025, online late December 2024 GitHub stars  
PACE: Pacing Operator Learning to Accurate Optical Field Simulation for Complicated Photonic Devices
Hanqing Zhu, Wenyan Cong, Guojin Chen, Shupeng Ning, Ray T Chen, Jiaqi Gu, David Z Pan
NeurIPS 2024  
Lightening-transformer: A dynamically-operated optically-interconnected photonic transformer accelerator
Hanqing Zhu, Jiaqi Gu, Hanrui Wang, Zixuan Jiang, Zhekai Zhang, Rongxing Tang, Chenghao Feng, Song Han, Ray T Chen, David Z Pan
HPCA 2024  GitHub stars
Pre-RMSNorm and Pre-CRMSNorm Transformers: Equivalent and Efficient Pre-LN Transformers
Zixuan Jiang, Jiaqi Gu, Hanqing Zhu, David Pan
NeurIPS 2023, Spotlight 
DOTA: A Dynamically-Operated Photonic Tensor Core for Energy-Efficient Transformer Accelerator
Hanqing Zhu, Jiaqi Gu, Hanrui Wang, Rongxin Tang, Zhekai Zhang, Chenghao Feng, Song Han, Ray T. Chen, David Z. Pan
MLSys 2023, Workshop on Systems for Next-Gen AI Paradigms (SNAP) 
NeurOLight: A Physics-Agnostic Neural Operator Enabling Parametric Photonic Device Simulation
Jiaqi Gu, Zhengqi Gao, Chenghao Feng, Hanqing Zhu, Ray Chen, Duane Boning, David Pan
Neurips 2022 
Fuse and Mix: MACAM-Enabled Analog Activation for Energy-Efficient Neural Acceleration
Hanqing Zhu, Keren Zhu, Jiaqi Gu, Harrison Jin, Ray T Chen, Jean Anne Incorvia, David Z Pan
ICCAD 2022 
L2ight: Enabling on-chip learning for optical neural networks via efficient in-situ subspace optimization
Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Zixuan Jiang, Ray Chen, David Pan
Neurips 2021 
ELight: Enabling Efficient Photonic In-Memory Neurocomputing with Life Enhancement
Hanqing Zhu, Jiaqi Gu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T Chen, David Z Pan
ASP-DAC 2021 
Towards Memory-Efficient Neural Networks via Multi-Level in situ Generation
Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T Chen, David Z Pan
ICCV 2021 

Journal

Photonic-Electronic Integrated Circuits for High-Performance Computing and AI Accelerators
Shupeng Ning*, Hanqing Zhu*, Chenghao Feng, Jiaqi Gu, Zhixing Jiang, Zhoufeng Ying, Jason Midkiff, Sourabh Jain, May H Hlaing, David Z Pan, Ray T Chen
Journal of Lightwave Technology 2024 
Domain Wall-Magnetic Tunnel Junction Analog Content Addressable Memory Using Current and Projected Data
Harrison Jin, Hanqing Zhu, Keren Zhu, Thomas Leonard, Jaesuk Kwon, Mahshid Alamdar, Kwangseok Kim, Jungsik Park, Naoki Hase, David Z Pan, Jean Anne C Incorvia
IEEE Transactions on Nanotechnology 2023 
A Compact Butterfly-Style Silicon Photonic–Electronic Neural Chip for Hardware-Efficient Deep Learning
Chenghao Feng, Jiaqi Gu, Hanqing Zhu, Zhoufeng Ying, Zheng Zhao, David Z Pan, Ray T Chen
ACS Photonics 2022 
ELight: Toward Efficient and Aging-Resilient Photonic In-Memory Neurocomputing
Hanqing Zhu, Jiaqi Gu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T Chen, David Z Pan
TCAD 2022 

Honors & Awards

  • ML and Systems Rising Stars(38 out of 150+), ML Commons, 2025
  • 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

Services

  • Journal Reviewers: 
    TNNLS, TCAD, Photonic Network Communications.
  • Conference Reviewers: 
    ICML, NeurIPS, ICLR, AAAI, DAC, ICCAD, FPGA, AICAS.