Jiayi Shen (沈佳怡)

I am a third year ELLIS PhD candidate at MultiX Lab, University of Amsterdam. I am supervised by Prof. Dr. Marcel Worring and Dr. Nanne van Noord.

Prior to that, I obtained my Master's and Bachelor's degrees from Beihang University.

I am currently looking for two master students from UvA to explore some interesting research topics about multi-task learning with me. Feel free to drop your resume to my Email.

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[March 2023] I just finished my 36-month evaluation.

[March 2023] One paper was accepted by CVPR 2023.

[September 2022] One paper was accepted by NeurIPS 2022.

[February 2022] I was nominated as an ELLIS PhD!

I'm interested in Machine Learning, Bayesian Models, and Meta-Learning. Much of my research is to address challenging problems in multi-task learning.

We propose a new MTL setting which suffers from category shifts from training to test data.

We propose a Neighbor Transformer Network, or NFormer, which explicitly models interactions across all input images.

We propose variational multi-task learning (VMTL), a general probabilistic inference framework for learning multiple related tasks.

To better explore domain invariant learning, we introduce weight uncertainty to the model by leveraging variational Bayesian inference.