About me

I am a 3rd-year Ph.D. student at Cornell University, advised by Prof. Kevin Ellis. I completed my bachelor and master degrees in Shanghai Jiao Tong University.

My research interest lies in the generalizability of AI models, in particular, generalizing/adapting to out-of-distribution samples (e.g., inputs of larger scales, unseen combinations, and new concepts/domains). I currently focus on neuro-symbolic program synthesis to integrate neural networks with programmatic prior for better generalizability and interpretability. It involves fields such as program synthesis, latent abstraction learning, and learning to optimize.

Publications

  • From Perception to Programs: Regularize, Overparameterize, and Amortize
    Hao Tang, and Kevin Ellis
    ICML 2023 [arxiv],
    ICML Differentiable Everthing workshop 2023, PLDI MAPS symposium 2022.
  • Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous GNNs
    Hao Tang, Zhiao Huang, Jiayuan Gu, Bao-Liang Lu, and Hao Su
    NeurIPS 2020 [arxiv] [code] [short-video] [poster] [pdf] [appendix].
  • Refactoring Policy for Compositional Generalizability using Self-Supervised Object Proposals
    Tongzhou Mu*, Jiayuan Gu*, Zhiwei Jia, Hao Tang, and Hao Su
    NeurIPS 2020 [arxiv] [code].
  • Belief Propagation Neural Networks
    Jonathan Kuck, Shuvam Chakraborty, Hao Tang, Rachel Luo, Jiaming Song, Ashish Sabharwal, and Stefano Ermon
    NeurIPS 2020 [arxiv].
  • Emotion Recognition using Multimodal Residual LSTM Network
    Jiaxin Ma*, Hao Tang*, Wei-Long Zheng, and Bao-Liang Lu
    ACM Multimedia 2019 [pdf].
  • Investigating Sex Differences in Classification of Five Emotions from EEG and Eye Movement Signals
    Lan-Qing Bao, Jie-Lin Qiu, Hao Tang, Wei-Long Zheng, and Bao-Liang Lu
    IEEE International Engineering in Medicine and Biology Conference (EMBC) 2019.
  • Multimodal Emotion Recognition Using Deep Neural Networks
    Hao Tang, Wei Liu, Wei-Long Zheng, and Bao-Liang Lu
    International Conference on Neural Information Processing (ICONIP) 2017 [pdf].

Misc.

  • Top Reviewer of NeurIPS, 2022.