Hi all, welcome to my personal website. I am a 5th year PhD student in the CS department of Georgia Institute of Technology, who is passinoate about efficient/automated ML and algorithm-hardware co-design!

My CV is available at here in case you are interested !

Research Experience

  • 12/2022Present: PhD Student at Georgia Tech
  • 08/201912/2022: Master Degree at Rice University
  • 09/201506/2019: Bachelor Degree at Huazhong University of Science and Technology

For more information, refer to our Lab’s homepage [Website] [LinkedIn] [Twitter] [Github] [Youtube]

Internship Experiences

  • Upcoming
    • Summer 2023: Join Startup Launch Program organized by CREATE-X and Venture Lab!
      • [07/2023] Release the pitch video [Youtube]
      • [05/2023] Received $25K Tech-Ready Grant [GT News]
      • [04/2023] Received $10K Commercialization Funding
  • Past
    • 08/202212/2022: Part-time Research Intern @ Meta Reality Labs
    • 05/202208/2022: Full-time Research Intern @ Meta Reality Labs
    • 08/202104/2022: Part-time Research Intern @ Baidu Research (USA)
    • 05/202108/2021: Full-time Research Intern @ Baidu Research (USA)

Publication List

> Conference:

  • H. You*, H. Shi*, Y. Guo*, Y. Lin.
    ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer. In NeurIPS 2023 (Acceptance rate: 26%).
    [Paper] [Code]

  • H. You*, Y. Xiong*, X. Dai, B. Wu, P. Zhang, H. Fan, P. Vajda, Y. Lin.
    Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention During Vision Transformer Inference. In CVPR 2023 (Acceptance rate: 25%).
    [Paper] [Code] [Project] [Slide] [Poster] [Talk@CVPR]

  • H. You, Z. Sun, H. Shi, Z. Yu, Y. Zhao, Y. Zhang, C. Li, B. Li, Y. Lin.
    ViTCoD: Vision Transformer Acceleration via Dedicated Algorithm and Accelerator Co-Design. In HPCA 2023 (Acceptance rate: 25%).
    Selected as the Meta Faculty Research Award of 2022 !
    [Paper] [Code] [Project] [Slide] [Poster] [Talk@GT] [Talk@HPCA]

  • H. You, B. Li, Z. Sun, X. Ouyang, Y. Lin.
    SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning. In ECCV 2022 (Acceptance rate: 20%).
    [Paper] [Code] [Slide] [Poster] [Talk@ECCV]

  • H. You, B. Li, H. Shi, Y. Fu, Y. Lin.
    ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks. In ICML 2022 (Acceptance rate: 20%).
    [Paper] [Code] [Project] [Slide] [Talk@ICML]

  • H. You*, C. Wan*, Y. Zhao*, Z. Yu*, Y. Fu, J. Yuan, S. Wu, S. Zhang, Y. Zhang, C. Li, V. Boominathan, A. Veeraraghavan, Z. Li, Y. Lin.
    EyeCoD: Eye Tracking System Acceleration via FlatCam-Based Algorithm and Accelerator Co-Design. In ISCA 2022 (Acceptance rate: 17%).
    Selected as the IEEE Micro’s Top Pick of 2023 !
    [Paper] [Code] [Project] [Slide] [Poster@ISCA] [Poster@CoCoSys] [Talk@ISCA] [IEEE Micro’s TopPick’23]

  • H. You, T. Geng, Y. Zhang, A. Li, Y. Lin.
    GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design. In HPCA 2022 (Acceptance rate: 30%).
    [Paper] [Code] [Slide] [Talk@HPCA]

  • H. You, Z. Lu, Z. Zhou, Y. Fu, Y. Lin
    Early-Bird GCNs: Graph-Network Co-Optimization Towards More Efficient GCN Training and Inference. In AAAI 2022 (Acceptance rate: 15%).
    [Paper] [Code] [Slide] [Poster] [Talk@AAAI]

  • H. You, X. Cheng, Y. Zhang, S. Liu, Z. Liu, Z. Wang, Y. Lin.
    ShiftAddNet: A Hardware-Inspired Deep Network. In NeurIPS 2020 (Acceptance rate: 20%).
    [Paper] [Code] [Slide] [Poster] [Talk@NeurIPS] [Talk@RICE]

  • H. You, C. Li, P. Xu, Y. Fu, Y. Wang, X. Chen, R.G. Baraniuk, Z. Wang, Y. Lin.
    Drawing Early-Bird Tickets: Towards More Efficient Training of Deep Networks. In ICLR 2020 Spotlight (Acceptance rate: 4%).
    Selected as an ICLR Spotlight !
    [Paper] [Code] [Slide] [OpenReview] [Talk@ICLR]

  • Y. Fu, H. You, Y. Zhao, Y. Wang, C. Li, K. Gopalakrishnan, Z. Wang, Y. Lin.
    FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training. In NeurIPS 2020 (Acceptance rate: 20%).

  • Y. Zhang, H. You, Y. Fu, T. Geng, A. Li, Y. Lin.
    G-CoS: GNN-Accelerator Co-Search Towards Both Better Accuracy and Efficiency. In ICCAD 2021 (Acceptance rate: 23%).

  • H. Shi, H. You, Y. Zhao, Z. Wang, Y. Lin.
    NASA: Neural Architecture Search and Acceleration for Hardware Inspired Hybrid Networks. In ICCAD 2022 (Acceptance rate: 24%).

  • Y. Zhao, Z. Li, H. You, Y. Fu, Y. Zhang, C. Li, C. Wan, S. Wu, X. Ouyang, V. Boominathan, A. Veeraraghavan, Y. Lin
    i-FlatCam: A 253 FPS, 91.49 µJ/Frame Ultra-Compact Intelligent Lensless Camera System for Real-Time and Efficient Eye Tracking in VR/AR. In VLSI 2022.
    Won the first place in University Best Demonstration at DAC 2022 !
    [Paper] [Demo]

  • C. Li, T. Chen, H. You, Z. Wang, Y. Lin.
    HALO: Hardware-Aware Learning to Optimize. In ECCV 2020 (Acceptance rate: 27%).

  • Y. Zhao, X. Chen, Y. Wang, C. Li, H. You, Y. Fu, Y. Xie, Z. Wang, Y. Lin.
    SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation. In ISCA 2020 (Acceptance rate: 18%).

  • T. Geng, C. Wu, Y. Zhang, C. Tan, C. Xie, H. You, M. Herbordt, Y. Lin, A. Li
    I-GCN: A GCN Accelerator with Runtime Locality Enhancement through Islandization. In MICRO 2021 (Acceptance rate: 22%).

  • C. Li, Z. Yu, Y. Fu, Y. Zhang, Y. Zhao, H. You, Q. Yu, Y. Wang, C. Hao, Y. Lin.
    HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark. In ICLR 2021 Spotlight (Acceptance rate: 4%).

  • Y. Fu, Z. Ye, J. Yuan, S. Zhang, S. Li, H. You, Y. Lin.
    Gen-NeRF: Efficient and Generalizable Neural Radiance Fields via Algorithm-Hardware Co-Design. In ISCA 2023 (Acceptance rate: 21%).

  • S. Li, C. Li, W. Zhu, B. Yu, Y. Zhao, C. Wan, H. You, H. Shi, Y. Lin.
    Instant-3D: Instant Neural Radiance Fields Training Towards Real-Time AR/VR 3D Reconstruction. In ISCA 2023 (Acceptance rate: 21%).

  • Z. Yu, Y. Fu, S. Wu, M. Li, H. You, Y. Lin.
    LDP: Learnable Dynamic Precision for Efficient Deep Neural Network Training and Inference. In TinyML 2022

> Journal:

  • H. You, R. Balestriero, Z. Lu, Y. Kou, H. Shi, S. Zhang, S. Wu, Y. Lin, R. Baraniuk
    Max-Affine Spline Insights Into Deep Network Pruning. In TMLR.
    [Paper] [Code]

  • H. You, Y. Cheng, T. Cheng, C. Li, P. Zhou.
    Bayesian Cycle-Consistent Generative Adversarial Networks via Marginalizing Latent Sampling. In IEEE TNNLS.
    [Paper@IEEE] [Paper@arXiv] [Code]

  • H. Shi, H. You, Z. Wang, Y. Lin.
    NASA+: Neural Architecture Search and Acceleration for Multiplication-Reduced Hybrid Networks. In IEEE Transactions on Circuits and Systems I.
    [Paper@IEEE] [Code]

  • X. Chen, Y. Zhao, Y. Wang, P. Xu, H. You, C. Li, Y. Fu, Y. Lin, Z. Wang
    SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training. In IEEE TNNLS.
    [Paper] [Code]

  • Y. Zhang, Y. Fu, W. Jiang, C. Li, H. You, M. Li, V. Chandra, Y. Lin
    DIAN: differentiable accelerator-network co-search towards maximal DNN efficiency. In ISLPED 2021.

Research Interests

Review Services

  • 2024
    • AAAI; ICLR
  • 2023
  • 2022
  • 2021
  • 2020