I am currently looking for the 2022 phd position!
Yu

I am the fourth year student in School of the Gifted Young in University of Science and Technology of China. I have finished plenty of projects in Artificial Intelligence and Machine Learning. Consequently, I have published or submitted several papers to various conferences. Check out my CV.

I am currently looking for the 2022 phd position.

Research Interests and Experiences

My research interests span from Information Retrieval to Natural Language Processing, along with Machine Learning, Statistics, Reinforcement Learning and Causal Inference.

I became a member in Lab for Data Science in October, 2020, under the supervision from Prof. Xiangnan He and Dr. Xin Xin. Then from April, 2021, I feel extremely lucky to have an internship in CSAIL, MIT, advised by Prof. Samuel Madden and Dr. Lei Cao. Besides, It's also my honor to have cooperated with Dr. Huaxiu Yao. Currently, I am an intern in NExT++, advised by Dr. Xiang Wang and Prof. Tat-Seng Chua.

Publications

[1] Meta-Learning with an Adaptive Scheduler.
Huaxiu Yao*, Yu Wang*, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Ying Wei, Chelsea Finn.
Published as a Conference paper in NeurIPS 2021

[2] Improving Out-of-Distribution Robustness via Selective Augmentation.
Huaxiu Yao*, Yu Wang*, Sai Li, Weixin Liang, Linjun Zhang, James Zou, Chelsea Finn.
Submitted to ICLR 2022

[3] Learning Robust Recommenders through Cross-Model Agreement.
Yu Wang, Xin Xin, Zaiqiao Meng, Xiangnan He, Joemon Jose, Fuli Feng.
Submitted to WWW 2022

[4] Invariant Causal Discovery.
Yu Wang, An Zhang, Xiang Wang, Xiangnan He, Tat-Seng Chua.
Submitted to JMLR

[5] Interpretable Outlier Summarization
Yu Wang, Lei Cao, Samuel Madden.
Submitted to PVLDB 2022

[6] Probabilistic and Variational Label Denoising.
Xin Xin*, Yu Wang*, Zaiqiao Meng, Xiangnan He, Joemon Jose, Fuli Feng.
Going to be submitted to TOIS

[7] AutoOD: Automatic Outlier Detection.
Lei Cao, Yizhou Yan, Yu Wang, Samuel Madden, Elke A. Rundensteiner.
Under Submission



Supervisor

  • Xiangnan He
  • Samuel Madden
  • Tat-Seng Chua
  • ...


Advisor



Cooperator

Why recruiting Yu?

Knowledgeable

Get acceleration in daily research with sophisticated built-in technology tree, covering theoretical machine learning, reinforcement learning, causal inference, meta-learning and so on.

Adaptable

Quickly adapts to new techniques and new research subjects. Technology tree is always kept updated.

Reputable

2 years into production, 100% positive feedback from users, well-tested and robust.

Detailed Information

Check out my CV for more information.