Xingyi Yang

I am a second year master student of University of California, San Diego. I am now working under the supervision of Prof.Pengtao Xie. I am also fortunate to work with Prof.Rose Yu and Prof.Fenglong ma. I got my bachelor degree in Computer Science and Engineering from Southeast University, China in 2019. I used to be a visiting student at University of Ottawa, supervised by Prof.Robert Laganière.

My current research interest can be summarized into 3M scheme:

  • Statistical Machine learning. Focus on generative modeling and robust learning.
  • Minimal supervision. Focus on self-supervised & weak-supervised learning, transfer learning, knowledge-grounded learning.
  • Medical data analysis, especially in the outbreak of the pandemic.

CV

I believe in Slow Science

News

  • [2021/01] One paper accepted by ICASSP2021, Kalman Optimizer for Consistent Gradient Descent.
  • [2021/01] Invited as the reviewer for ICCV2021.
  • [2020/12] Invited as the reviewer for Journal of Biomedical and Health Informatics (JBHI).
  • [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.
  • [2020/09] Invited as the reviewer for IJCAI2021, CVPR2021.
  • [2020/07] One paper accepted by ECCV2020, Single Viaew Metrology in the Wild