Shaoyi Huang

Openings: I am looking for 2~3 highly motivated Ph.D. students (will be fully-funded) for Spring / Fall 2025. If you are interested, please send your CV, trasncripts, research interests to shaoyi.hiring@gmail.com

Application link: https://www.stevens.edu/program/computer-science-doctoral-program

Shaoyi is a tenure-track assistant professor in CS department at Stevens Institute of Technology. She received her PhD degree from the School of Computing at University of Connecticut under the supervision of Prof. Caiwen Ding and Prof. Omer Khan. Her research agenda is grounded in advancing AI systems, including algorithm-system co-design for AI acceleration, emerging deep learning models inference acceleration (i.e., Transformer and LLM), privacy preserving machine learning, and machine learning for EDA. Shaoyi’s work has been published in high-impact conferences such as HPCA, ASPLOS, SC, DAC, ICCAD, ACL, ICCV, NeurIPS, IJCAI, etc.

She was selected as a Machine Learning and Systems Rising Star 2024. She was awarded Marion and Frederick Buckman Engineering Fellowship for outstanding academic achievement in 2024 and both Predoctoral Prize for Research Excellence, GE Fellowship for Excellence from UConn in 2023 and 2022. She was the recipient of Eversource Energy Graduate Fellowship in 2022, Synchrony Fellowship in 2022, and Cigna Graduate Fellowship in 2021. Her work on FPGA-based language models acceleration through sparse attention and dynamic pipelining won DAC'22 Publicity Paper Award. She was invited as a student panelist to share experience with the female researchers and K-12 students at the 6th Workshop for Women in Hardware and Systems Security (WISE).

Email  /  CV  /  Google Scholar  /  Github  /  LinkedIn

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Publications Teaching Internship Talks Awards Services Misc
Research Interests

  • Efficient machine learning algorithm

  • Algorithm-system co-design for AI acceleration (including emerging deep learning models, such as GNNs, LLMs, Diffusion models, etc.)

  • Large-scale machine learning for chip design

  • Energy efficient privacy preserving machine learning

News

  • 10/2024: I will serve as a session chair for ICCAD 2024.
  • 10/2024: Invited to serve as a TPC member for DAC 2025.
  • 09/2024: Invited to serve as Guest Editor of Special Issue, High-Performance Computing for AI: Architecture, Systems, and Algorithm.
  • 09/2024: Invited to serve on the 2024 WISE organizing committee. See u in IBM T.J. Watson Research Center, New York.
  • 09/2024: Invited to serve as a Reviewer for ICLR 2025.
  • 09/2024: Shaoyi joined Stevens CS department.
  • 08/2024: Invited to join the Program Committee of IPDPS’25 - the 39th IEEE International Parallel & Distributed Processing Symposium.
  • 05/2024: Honored to be selected as a Machine Learning and Systems Rising Star 2024, see u in NVIDIA, Santa Clara, CA.
  • 05/2024: Glad to volunteer at NSF IUCRC Center for Hardware and Embedded Systems Security and Trust (CHEST).
  • 05/2024: Honored to receive Marion and Frederick Buckman Engineering Fellowship for outstanding academic achievement from the School of Computing.
  • 04/2024: Invited to write an article for ACM Sigda newsletter "what is column".
  • 10/2023: One paper was accepted to ASPLOS 2024.
  • 10/2023: One paper was accepted to HPCA 2024.
  • 10/2023: Received travel grant from CACC. Thanks, CACC!
  • 09/2023: Honored to be invited to be the student panelist and to receive the student travel grant from WISE 2023.
  • 09/2023: One proposal on Efficient Multi-party Computation-based Private Inference was accepted to WISE 2023 (The 6th Workshop for Women in Hardware and Systems Security).
  • 09/2023: One paper was accepted to NeurIPS 2023.
  • 09/2023: Honored to be invited to give a guest lecture at the University of Rochester.
  • 09/2023: Invited to serve as a PC member for SDM 2024.
  • 09/2023: Honored to present at TechCon organized by Semiconductor Research Corporation (SRC). See u in Austin.
  • 07/2023: One paper was accepted to ICCAD 2023.
  • 07/2023: One paper was accepted to ICCV 2023.
  • 07/2023: Invited to serve as a PC member for AAAI 2024.
  • 06/2023: Received the GE Fellowship for Excellence from UConn School of Engineering.
  • 05/2023: Honored to give a talk and a poster presentation at Semiconductor Research Corporation (SRC) AIHW & CADT Annual Review in IBM Research. See u in San Jose.
  • 05/2023: Received the Predoctoral Prize for Research Excellence from UConn CSE.
  • 03/2023: Honored to be invited to give a talk at MLNLP.
  • 03/2023: One paper was accepted to IJCAI 2023.
  • 03/2023: Two papers on sparse training were accepted to DAC 2023. See u in San Francisco.
  • 01/2023: Invited to serve as a reviewer for the First Workshop on DL-Hardware Co-Design for AI Acceleration at AAAI 2023.
  • 12/2022: Invited to serve as a PC member for KDD 2023.
  • 08/2022: Received the GE Fellowship for Excellence from the School of Engineering. Thanks for the support!
  • 07/2022: Invited to serve as a PC member for AAAI 2023.
  • 07/2022: Received the Synchrony Fellowship from Connecticut Advanced Computing Center. Thanks, CACC!
  • 05/2022: Started to work at TikTok (ByteDance) as a research intern.
  • 05/2022: Received the Predoctoral Prize for Research Excellence from UConn CSE.
  • 05/2022: Received the Eversource Energy Graduate Fellowship from Eversource Energy Center. Thanks, Eversource!
  • 04/2022: Our DAC 22 paper “A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining” was recognized as a Publicity Paper.
  • 02/2022: One paper was accepted to ACL 2022.
  • 02/2022: One paper was accepted to DAC 2022.
  • 02/2022: One paper was accepted to ISQED 2022.
  • 08/2021: Received the Cigna Graduate Fellowship from UConn CSE. Thanks, Cigna!
  • 07/2021: One paper was accepted to ICCAD 2021.
  • 06/2021: One paper was accepted to SC 2021.
  • 04/2021: Three papers were accepted to GLSVLSI 2021.
  • 02/2021: One paper was accepted to ISQED 2021.
Selected Publications

Full publication list

2024
3DSP MaxK-GNN: Towards Theoretical Speed Limits for Accelerating Graph Neural Networks Training
H. Peng, X. Xie, K. Shivdikar, M. A. Hasan, J. Zhao, S. Huang, O. Khan, D. Kaeli, C. Ding
[ASPLOS 2024] Paper
3DSP PruneGNN: An Optimized Algorithm-Hardware Framework for Graph Neural Network Pruning
D. Gurevin, M. Shan, S. Huang, M. A. Hasan, C. Ding, O. Khan
[HPCA 2024] Paper
(Acceptance rate: 75/410=18.3%)

2023
3DSP Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off
S. Huang, B. Lei, D. Xu, H. Peng, Y. Sun, M. Xie, C. Ding
[DAC 2023] Paper
(Acceptance rate: 263/1156=22.7%)
3DSP Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration
S. Huang, H. Fang, K. Mahmood, B. Lei, N. Xu, B. Lei, Y. Sun, D. Xu, W. Wen, C. Ding
[DAC 2023] Paper
(Acceptance rate: 263/1156=22.7%)
3DSP AutoReP: Automatic ReLU Replacement for Fast Private Network Inference
S. Huang*, H. Peng*, T. Zhou*, W. Wen, X. Xu, C. Ding, et al.
[ICCV 2023] Paper / Code
(Acceptance rate: 26.8%)
3DSP Towards Lossless Head Pruning through Automatic Peer Distillation for Large Language Models
B. Li, Z. Wang, S. Huang, M. Bragin, J. Li, C. Ding
[IJCAI 2023] Paper
(Acceptance rate: 15%)
3DSP Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks
X. Xie, H. Peng, A. Hasan, S. Huang, J. Zhao, H. Fang, W. Zhang, T. Geng, O. Khan, C. Ding
[ICCAD 2023] Paper / Code
3DSP LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference
H. Peng, R. Ran, Y. Luo, J. Zhao, S. Huang, K. Thorat, T. Geng, C. Wang, X.lin Xu, W. Wen, C. Ding
[NeurIPS 2023] Paper / Code
(Acceptance rate: 26.1%)

2022
3DSP Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm
S. Huang, D. Xu, I. E. Yen, S. Chang, B. Li, C. Ding, et al.
[ACL 2022] Paper / Code
(Acceptance rate: 714/3350=21.3%)
In collaboration with Moffett AI
3DSP A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining
S. Huang*, H. Peng*, S. Chen, B. Li, T. Geng, A, Li, W. Jiang, W, Wen, J, Bi, H. Liu, C. Ding
[DAC 2022] Paper
Publicity paper award
3DSP Towards Sparsification of Graph Neural Networks
H. Peng, D. Gurevin, S. Huang, T. Geng, W. Jiang, O. Khan, C. Ding
[ICCD 2022] Paper / Code
3DSP Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification
Y. Wang, N. Xu, S. Huang, K. Mahmood, D. Guo, C. Ding, W. Wen, S. Rajasekaran
[IEEE BigData 2022] Paper
3DSP CoDG-ReRAM: An Algorithm-Hardware Co-design to Accelerate Semi-Structured GNNs on ReRAM
Y. Luo, P. Behnam, K. Thorat, Z. Liu, H. Peng, S. Huang, S. Zhou, O. Khan, A. Tumanov, C. Ding, T. Geng
[ICCD 2022] Paper

2021
3DSP E.T.: Re-Thinking Self-Attention for Transformer Models on GPU
S. Huang*, S. Chen*, S. Pandey, B. Li, G. Gao, C. Ding, H. Liu
[SC 2021] Paper / Code
(Acceptance rate: 86/365=23.6%)
3DSP Accelerating Framework of Transformer by Hardware Design and Model Compression Co-Optimization
P. Qi, E. Sha, Q. Zhuge, H. Peng, S. Huang, Z. Kong, Y. Song, B. Li
[ICCAD 2021] Paper
3DSP HMC-Tran: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU
S. Huang, S. Chen, H. Peng, D. Manu, Z. Kong, G. Yuan, L. Yang, S. Wang, H. Liu, C. Ding
[GLSVLSI 2021] Paper
3DSP Accelerating Transformer-based Deep Learning Models on FPGAs Using Column Balanced Block Pruning
H. Peng, S. Huang, T. Geng, A. Li, W. Jiang, H. Liu, W. Wang, C. Ding
[ISQED 2021] Paper
Teaching
  • Guest Lecturer

    • ECE 403-1: Advanced Computer Architecture for Machine Learning, Sep 2023, University of Rochester

  • Teaching Assistant at University of Connecticut

    • CSE 4502/5717 - BigData Analytics, Spring 2023
      Instructor: Prof. Suining He   

    • CSE5819 - Introduction to Machine Learning, Fall 2022
      Instructor: Prof. Fei Miao   
      As a co-instructor, I designed final project, developed and delivered coding tutorials, led final project presentation courses, supervised students on course projects, held office hours and graded assignments.

  • Teaching Assistant at University of Rochester

    • Microcontroller, Spring 2018
      Instructor: Prof. Qiang Lin   

    • Circuits & Signals LAB, Fall 2017
      Instructor: Prof. Jack G. Mottley   
      I led the laboratory sessions and provided hands-on instruction to around 100 undergraduate students.

  • Mentoring

    • Amit Hasan, Ph.D. Student at University of Connecticut
      Topic: LLM Inference Acceleration

    • Yifan Shan, Undergraduate at University of Connecticut (Now master at Cornell Tech)
      Project: Evaluating the Impact of Preferential Trade Agreements on Agricultural and Food Trade: New Insights from Natural Language Processing and Machine Learning

    • Jiwon Kim, Undergraduate at University of Connecticut
      Project (NSF-REU): Utilization of DeepShift for Privacy Based Machine Learning

    • Alison Menezes, Undergraduate at Clemson University
      Project (NSF-REU): Deep Leakage from Gradients on GNNs

    • Maryam Abuissa, Undergraduate at Amherst College
      Project (NSF-REU): Sequestered Encryption for GPU

Internship

  • May 2022 - Aug 2022, Research Intern, ByteDance, Austin, TX

  • May 2021 - Aug 2021, Research Intern, Moffett AI, Los Altos, CA

Talks

  • Student panelist - The 6th Workshop for Women in Hardware and Systems Security
    Oct 2023, California State University, Fullerton, Fullerton, CA

  • Towards Efficient Model Inference and Training
    Sep 2023, University of Rochester
    Guest Lecture of ECE 403-1: Advanced Computer Architecture for Machine Learning.
    Host: Prof. Tony Geng

  • Towards Efficient Training and Inference Under Pretrain-and-Finetune Paradigm
    Sep 2023, TechCon - Semiconductor Research Corporation (SRC), Austin, TX

  • Exploring Extreme Sparsity in Training and Inference for Graph Neural Networks to Achieve High Performance Scaling on Large Core Count Machines
    May 2023, Semiconductor Research Corporation (SRC) AIHW \& CADT Annual Review, IBM Research, San Jose, CA

  • Towards Efficient Model Inference and Training
    Apr 2023, Machine Learning and Natural Language Processing Community (MLNLP)
    MLNLP Outstanding Speaker

Honors and Awards
  • Machine Learning and Systems Rising Star, 2024
  • Marion and Frederick Buckman Engineering Fellowship, 2024
  • NeurIPS Travel Grant from CACC, 2023
  • WISE Student Travel Award, 2023
  • GE Fellowship of Excellence, 2023
  • Predoctoral Prize for Research Excellence, 2023
  • GE Fellowship for Excellence, 2022
  • Synchrony Fellowship, 2022
  • DAC Publicity Paper Award, 2022
  • Predoctoral Prize for Research Excellence, 2022
  • Eversource Energy Graduate Fellowship, 2022
  • DAC Young Fellow, 2021
  • Cigna Graduate Fellowship, 2021
Professional Services
  • Panelist
    • The 6th Workshop for Women in Hardware and Systems Security (WISE)
  • Program Committee Member
    • ICLR'25
    • ACL'24
    • AAAI'25, 24, 23
    • NeurIPS'23 Datasets and Benchmarks
    • KDD'24, 23
    • SDM'24
    • DCAA'23
  • Conference External Reviewer
    • NeurIPS'23
    • DAC'23, 22, 21
    • ICCAD'23, 22, 21
    • AAAI'23, 22, 21
    • EMNLP'23, 22
    • IJCAI'23, 22, 21
    • ICCD'23, 22
    • EACL'22
    • FPGA'21
    • NAACL'21
  • Journal Reviewer
    • Neurocomputing
    • Pattern Recognition
    • Engineering Applications of Artificial Intelligence
    • Neural Networks
    • Journal of Systems Architecture
    • IEEE Transactions on Neural Networks and Learning Systems
    • ACM Transactions on Intelligent Systems and Technology
    • ACM Transactions on Design Automation of Electronic Systems
  • Journal External Reviewer
    • ACM Transactions on Architecture and Code Optimization
    • IEEE Transactions on Neural Networks and Learning Systems
    • IEEE Network Magazine
    • Journal on Emerging Technologies in Computing Systems
Misc

  • Playing with Nobel:

    nobel

  • Painting:

    watermelon

  • Outdoor activities: mushroom hunting (Boletus edulis, Honey mushroom, Chicken of the Woods, Chanterelles I found in Connecticut); sea foraging (crab, oyster, clam and mussel I found in Connecticut, Long island, Boston, New Jersey):

    mushroom mushroom mushroom mushroom
    crab oyster shell mussel

Last updated on 05/2024 EDT.
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