Qi Wan

Qi Wan

Hi! I’m Qi Wan (万琪), a first year master’s student at University of Science and Technology of China (USTC), advised by Prof. Xiangnan He and Prof. Xiang Wang. Previously, I studied at School of the Gifted Young, USTC, where I received a bachelor degree in Computer Science.

My research interest mainly lies in graph neural networks and information retrieval with applications in molecules, recommendations and social networks. Currently, I am working on developing expressive and reliable models for molecule representation learning.

Publication

Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo, Ruiming Tang
January, 2022 In WWW 2022
Cross Pairwise Ranking for Unbiased Item Recommendation

We develop a new learning paradigm named Cross Pairwise Ranking (CPR) to alleviate the popularity bias in recommender systems. It achieves unbiased recommendation without knowing the exposure mechanism.
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Education

 
 
 
 
 
School of Data Science, University of Science and Technology of China
Master of Engineering, Computer Science and Technology
School of Data Science, University of Science and Technology of China
Jul 2021 – Present
 
 
 
 
 
School of the Gifted Young, University of Science and Technology of China
Bachelor of Engineering, Computer Science and Technology
School of the Gifted Young, University of Science and Technology of China
Jul 2017 – Jun 2020

Industrial Experience

 
 
 
 
 
Speech and Language Computing Group, Huawei Noah’s Ark Lab
Research Intern
Speech and Language Computing Group, Huawei Noah’s Ark Lab
Jan 2020 – Feb 2020

Accomplishments

USTC
Outstanding Undergraduate Thesis Award
USTC Jul 2021
USTC
Huaxia Talent Program for Computer Science and Technology
USTC Jul 2018 – Jun 2021
USTC
Keshaosihua Scholarship
USTC Jun 2018
USTC
Gold award, USTC Outstanding Student Scholarship
USTC Jun 2017

Skills

Programming skills

  • Python, PyTorch, TensorFlow
  • C/C++

Language tests

  • GRE: Verbal 164 + Quantitative 169 + Analytical Writing 3

Contact