Zhongzhan Huang

Artificial Intelligence PhD @ SYSU πŸš€

Hi, I am Zhongzhan Huang (黄中展), a Second-year Artificial Intelligence PhD student in Sun Yat-sen University, advised by Prof. Liang Lin in Human-Cyber-Physical Intelligence Integration (HCP-l2) Lab. My research interest include the foundations of deep learning, neural network formulation (e.g. network pruning, design of effective network architectures, attention mechanism), and artificial intelligence for scientific computing.

Recently, I try to think about how to apply artificial intelligence technology to science problems (e.g. physics, medical, mathematics and so on), and make meaningful AI work for human society.

The life can be what you want it to be. Right? πŸ’ͺ

Contact: zhongzhanhuang [at] foxmail [dot] com
Follow: Google Scholar | github

News

Jan, 2022 I have one paper, SANN, accepted to ICLR 2022 ! πŸš€
Sep, 2021 I have one paper, CWDA, accepted to NeurIPS 2021 ! πŸš€
Sep, 2021 I go back to the campus and start pursuing PhD degree in SYSU! Enjoy it! :fire:

Academic Service

Invited Conference Reviewer: CVPR, ECCV, AAAI, ICANN
Invited Journal Reviewer: None

Selected Work

2022

  1. Arxiv
    Accelerating Numerical Solvers for Large-Scale Simulation of Dynamical System via NeurVec
    Huang, Zhongzhan, Liang, Senwei, Zhang, Hong, Yang, Haizhao, and Lin, Liang
    arXiv preprint (in submission), 2022
  2. Arxiv
    The Lottery Ticket Hypothesis for Self-attention in Convolutional Neural Network
    Huang, Zhongzhan, Liang, Senwei, Liang, Mingfu, He, Wei, Yang, Haizhao, and Lin, Liang
    arXiv preprint (in submission), 2022
  3. ICLR 2022
    Stiffness-aware neural network for learning Hamiltonian systems
    Liang, Senwei, Huang, Zhongzhan, and Zhang, Hong
    International Conference on Learning Representations (ICLR), 2022

2021

  1. NeurIPS 2021
    Rethinking the Pruning Criteria for Convolutional Neural Network
    Huang, Zhongzhan, Shao, Wenqi, Wang, Xinjiang, Lin, Liang, and Luo, Ping
    The Conference on Neural Information Processing Systems (NeurIPS), 2021
  2. ICANN 2021
    Blending Pruning Criteria for Convolutional Neural Networks
    He, Wei, Huang, Zhongzhan (co-first author), Liang, Mingfu, Liang, Senwei, and Yang, Haizhao
    International Conference on Artificial Neural Networks (ICANN), 2021
  3. ICRA 2021
    Continuous Transition: Improving Sample Efficiency for Continuous Control Problems via MixUp
    Lin, Junfan, Huang, Zhongzhan, Wang, Keze, Liang, Xiaodan, Chen, Weiwei, and Lin, Liang
    IEEE International Conference on Robotics and Automation (ICRA), 2021
  4. Arxiv
    AlterSGD: Finding Flat Minima for Continual Learning by Alternative Training
    Huang, Zhongzhan, Liang, Mingfu, Liang, Senwei, and He, Wei
    arXiv preprint (Technical report), 2021

2020

  1. AAAI 2020
    Instance enhancement batch normalization: An adaptive regulator of batch noise
    Liang, Senwei, Huang, Zhongzhan (co-first author), Liang, Mingfu, and Yang, Haizhao
    The AAAI Conference on Artificial Intelligence (AAAI), 2020
  2. AAAI 2020
    DIANet: Dense-and-implicit attention network
    Huang, Zhongzhan, Liang, Senwei, Liang, Mingfu, and Yang, Haizhao
    The AAAI Conference on Artificial Intelligence (AAAI), 2020
  3. Arxiv
    Efficient Attention Network: Accelerate Attention by Searching Where to Plug
    Huang, Zhongzhan, Liang, Senwei, Liang, Mingfu, He, Wei, and Yang, Haizhao
    arXiv preprint (in submission), 2020
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