Hanrui Wang

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Hanrui Wang
hanrui AT mit.edu

Welcome! I am currently a Ph.D. Student at MIT, advised by Prof. Song Han. I also closely work with Prof. Fred Chong.

Previously, I received my Master from MIT in 2020 and Bachelor from Fudan University in 2018.

My research area is ML for Quantum and Quantum for ML. On one hand, I study how to leverage classical ML to solve quantum computer system problems such as using Transformers to predict circuit fidelity, designing quantum circuits robust to quantum noise, etc. On the other, I explore how to achieve quantum advantages on machine learning problems.

GitHub  /  Google Scholar  /  LinkedIn  /  Twitter  /  YouTube

News
  • Nov. 2022. Received 1st Place in ACM Student Research Competition SRC.
  • Nov. 2022. Received 1/150 Place in ACM/IEEE TinyML Design Contest in memory size track and 3/150 place for overall score.
  • Aug. 2022. Received NSF Athena AI Institute Best Poster Award rank #1.
  • Aug. 2022. "Graph Transformer for Quantum Circuit Reliability Prediction" will appear at ICCAD 2022.
  • Jun. 2022. Variational Quantum Pulse Learning accepted to QCE 2022.
  • Jun. 2022. Welcome to attend Quantum Computer Systems Lecture Series.
Publications[Full List]
QuEst: Graph Transformer for Quantum Circuit Reliability Prediction (TorchQuantum Case Study for Robust Quantum Circuits)
Hanrui Wang, Pengyu Liu, Jinglei Cheng, Zhiding Liang, Jiaqi Gu, Zirui Li, Yongshan Ding, Weiwen Jiang, Yiyu Shi, Xuehai Qian, David Z. Pan, Frederic T. Chong, Song Han
International Conference on Computer-Aided Design (ICCAD), invited, 2022.

Variational Quantum Pulse Learning
Zhiding Liang*, Hanrui Wang*, Jinglei Cheng, Yongshan Ding, Hang Ren, Zhengqi Gao, Xuehai Qian, Song Han, Weiwen Jiang, Yiyu Shi
IEEE International Conference on Quantum Computing and Engineering (QCE), 2022.

QOC: Quantum On-Chip Training with Parameter Shift and Gradient Pruning
Hanrui Wang*, Zirui Li*, Jiaqi Gu, Yongshan Ding, David Z. Pan, Song Han
Design Automation Conference (DAC), 2022.
Paper  /  Code  /  Project Page

QuantumNAT: Quantum Noise-Aware Training with Noise Injection, Quantization and Normalization
Hanrui Wang, Jiaqi Gu, Yongshan Ding, Zirui Li, Frederic T. Chong, David Z. Pan, Song Han
Design Automation Conference (DAC), 2022.
Paper  /  Code  /  Project Page

QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits
Hanrui Wang, Yongshan Ding, Jiaqi Gu, Zirui Li, Yujun Lin, David Z. Pan, Frederic T. Chong, Song Han
International Symposium on High-Performance Computer Architecture (HPCA), 2022.
Paper  /  Poster  /  Code  /  Project Page

SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning
Hanrui Wang, Zhekai Zhang, Song Han
International Symposium on High-Performance Computer Architecture (HPCA), 2021.
Paper  /  Slides  /  Intro Video  /  Short Video  /  Project Page

HAT: Hardware-Aware Transformers for Efficient Natural Language Processing
Hanrui Wang, Zhanghao Wu, Zhijian Liu, Han Cai, Ligeng Zhu, Chuang Gan, Song Han
Annual Conference of the Association for Computational Linguistics (ACL), 2020.
Paper  /  Slides  /  Video  /  Code  /  Project Page

GCN-RL Circuit Designer: Transferable Transistor Sizing With Graph Neural Networks and Reinforcement Learning
Hanrui Wang, Kuan Wang, Jiacheng Yang, Linxiao Shen, Nan Sun, Hae-Seung Lee, Song Han
Design Automation Conference (DAC), 2020.
Paper  /  Slides  /  Poster  /  Video  /  Project Page

SpArch: Efficient Architecture for Sparse Matrix Multiplication
Zhekai Zhang*, Hanrui Wang* , Song Han, William J. Dally (*Equal Contributions)
International Symposium on High-Performance Computer Architecture (HPCA), 2020
Paper  /  2-min Intro  /  Intro  /  Talk  /  Slides  /  Project Page

MicroNet for Efficient Language Modeling
Zhongxia Yan, Hanrui Wang, Demi Guo, Song Han
Journal of Machine Learning Research, 2020.
Paper  /  Talk (Starts from 26:17)  /  Code  /  Project Page

PointAcc: Efficient Point Cloud Accelerator
Yujun Lin, Zhekai Zhang, Haotian Tang, Hanrui Wang, Song Han
International Symposium on Microarchitecture, 2021.

Park: An Open Platform for Learning-Augmented Computer Systems
Hongzi Mao, Parimarjan Negi, Akshay Narayan, Hanrui Wang, Jiacheng Yang, Haonan Wang, Ryan Marcus, ravichandra addanki, Mehrdad Khani Shirkoohi, Songtao He, Vikram Nathan, Frank Cangialosi, Shaileshh, Venkatakrishnan, Wei-Hung Weng, Song Han, Tim Kraska, Mohammad Alizadeh
Advances in Neural Information Processing Systems (NeurIPS), 2019
Paper  /  Code

APQ: Joint Search for Network Architecture, Pruning and Quantization Policy
Tianzhe Wang, Kuan Wang, Han Cai, Ji Lin, Zhijian Liu, Hanrui Wang, Yujun Lin, Song Han
Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
Paper

Learning to Design Circuits
Hanrui Wang*, Jiacheng Yang*, Hae-Seung Lee, Song Han (*Equal Contributions)
Advances in Neural Information Processing Systems (NeurIPS) Workshop on ML for Systems, 2018
Paper  /  Project Page

AMC: AutoML for Model Compression and Acceleration on Mobile Devices
Yihui He*, Ji Lin*, Zhijian Liu, Hanrui Wang, Li-Jia Li, Song Han (*Equal Contributions)
The European Conference on Computer Vision (ECCV), 2018
Paper  /  Code  /  Models  /  Project Page

Understanding Performance Differences of FPGAs and GPUs
Jason Cong, Zhenman Fang, Michael Lo, Hanrui Wang, Jingxian Xu, Shaochong Zhang (Alphabetical Order)
International Symposium On Field-Programmable Custom Computing Machines (FCCM), 2018
Paper
Honors and Awards
  • 2022 1st Place in ACM Student Research Competition
  • 2022 1/150 Place in ACM/IEEE TinyML Design Contest in memory size track, 3/150 Place for overall score
  • 2022 NSF Athena AI Institute Best Poster Award rank #1.
  • 2022 DAC Young Fellowship
  • 2021 Qualcomm Graduate Fellowship
  • 2021 Baidu Graduate Fellowship
  • 2021 Analog Devices Outstanding Student Designer Award
  • 2021 Global Top 100 Chinese Rising Stars in AI Award
  • 2020 Nvidia Graduate Fellowship Finalist
  • 2020 DAC Young Fellow Best Presentation Award
  • 2020 DAC Young Fellowship
  • 2019 Champion of NeurIPS 2019 MicroNet efficient Language Model Competition
  • 2019 Best Paper Award of ICML 2019 Reinforcement Learning for Real Life Workshop
  • 2018 Bronze Medal in Kaggle TensorFlow Speech Recognition Challenge
  • 2017 UCLA CSST Fellowship & CSST Best Research Award
  • 2016 Chun-Tsung Research Fellowship
  • 2015/16/17 China National Scholarship
Services
Invited Reviewer for ICML, NeurIPS, ICLR, EMNLP, ACL, JMLR, IJCV, TCAS-II, TMLR, TODAES, TNNLS, TQC, MLR, ICITED, TASE, ADVCOMP, Pattern Recognition, FUZZ, IJCNN, JOSS, CEC, WCCI, ICECCME, ICECET