I am a 2nd-year Ph.D. student in Comptuer Science at Cornell University, advised by Prof. Kevin Ellis. Prior to that, I obtained my bachelor and master degrees from Shanghai Jiao Tong University.
My research interest lies in generalizable powerful AI, with a focus on neuro-symbolic program synthesis which integrates programmatic modules/architecture/prior and neural networks to achieve better generalizability and interpretabiilty. It involves many subfieds that I am excited about, such as abstraction & symbol grounding, learning to learn (or amortized inference, neural heuristics), and generally joint optimization of discrete and continuous parameters.
- From Perception to Programs: Regularize, Overparameterize, and Amortize
Hao Tang, and Kevin Ellis
PLDI-MAPS workshop 2022 [pdf].
- Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous GNNs
, 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, , and Hao Su
NeurIPS 2020 [arxiv] [code].
- Belief Propagation Neural Networks
Jonathan Kuck, Shuvam Chakraborty, , Rachel Luo, Jiaming Song, Ashish Sabharwal, and Stefano Ermon
NeurIPS 2020 [arxiv].
- Emotion Recognition using Multimodal Residual LSTM Network
Jiaxin Ma*, , 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, , Wei-Long Zheng, and Bao-Liang Lu
IEEE International Engineering in Medicine and Biology Conference (EMBC) 2019.
- Multimodal Emotion Recognition Using Deep Neural Networks
, Wei Liu, Wei-Long Zheng, and Bao-Liang Lu
International Conference on Neural Information Processing (ICONIP) 2017 [pdf].