My current research interest can be summarized into 3M scheme:
- Statistical Machine learning. Focus on generative modeling, trust-worthy learning (interpretability and robustness) and graph learning.
- Minimal supervision. Focus on self-supervised & semi-supervised & weak-supervised learning, transfer learning, knowledge-grounded learning.
- Medical data analysis, especially during the outbreak of the pandemic.
I believe in Slow Science
- [2021/05] Two paper accepted by ACL2021, one about Medical report generation and one on COVID-19 Dialogues.
- [2021/02] One paper accepted by CVPR2021, DSRNA: Differentiable Search of Robust Neural Architectures.
- [2021/01] One paper accepted by ICASSP2021, Kalman Optimizer for Consistent Gradient Descent.
- [2020/09] I am co-organizing NeurIPS 2020 workshop “Self-Supervised Learning – Theory and Practice”, serving as the Workflow Chair.
- [2020/09] One oral paper accepted by ISVC2020.
- [2020/07] One paper accepted by ECCV2020, Single View Metrology in the Wild