News


Xinyuan Zhu 

Lab for Data Science
Department of Electronic Engineering and Information Science
University of Science and Technology of China

100, Fuxing Road, Hefei, China

Email: zhuxinyuan@mail.ustc.edu.cn

[Github]

I am a third-year Ph.D. student @ University of Science and Technology of China since Sep 2021, co-supervised by Prof. Xiangnan He and Prof. Fuli Feng.

I obtained B.Eng in Artificial Intelligence and Information Security in the University of Science and Technology of China. I was affiliated with the School of the Gifted Young, which originates from the first undegraduate program for special young talents in China.

My research interests lie in deep learning based methods for biology and healthcare. Previously I actively researched in the field of Recommender System and Causal Inference.

Publications

pdf Improving Prostate Cancer Risk Prediction through Partial AUC Optimization
Xinyuan Zhu, Xiaohan Ren, Wentao Shi, Changming Wang, Xuehan Liu, Yuqing Liu, Tao Tao, Fuli Feng
The Web Conference 2024 - Health Day
pdf Mitigating Hidden Confounding Effects for Causal Recommendation
Xinyuan Zhu, Yang Zhang, Fuli Feng, Xun Yang, Dingxian Wang, Xiangnan He
IEEE Transactions on Knowledge and Data Engineering (TKDE)

Education

University of Science and Technology of China
Master in Electronic Engineering                                                         Sep 2021 - , Hefei, Anhui, China
Advisor: Prof. Xiangnan He and Prof. Fuli Feng.
University of Science and Technology of China
B.Eng. in Information Security and Artificial Intelligence              Sep 2017 - June 2021, Hefei, Anhui, China
Advisor: Prof.Xiangnan He and Prof.Fuli Feng.

Experiences

Research Intern, BioGeometry, Apr 2023 - Jul 2023
Mentor: Dr. Meng Qu and Prof. Jian Tang
• During my internship at BioGeometry, a pioneering AI Drug Discovery startup,I played a key role in designing and developing the advanced RAG system for biomedicine. This state-of-the-art system leveraged the power of LLMs and vast repositories of biomedical information, including texts, patents, molecular data, and protein information, to greatly accelerate the drug discovery process.
Research Assistant, Lab for Data Science, USTC, Sep 2021 - May 2022
Advisor: Prof.Xiangnan He and Prof.Fuli Feng.
• Highlight confounding effects in recommender models and shortcomings of existing methods in handling hidden confounders.
• Incorporate causal graph and other causal inference-based techniques to remove hidden confounders during recommender training and outperform existing state-of-the-art methods.
Research Intern, Theory Dept., 2012 Lab, Huawei Technologies Co., Ltd, Jan 2020 - June 2020
Mentor: Dr. Sen Wang and Dr. Peng Wang
• Design privacy-preserving learning mechanism with (local) differential privacy for edge-cloud collaborative learning.
• Use model inversion attack and membership inference attack to test the performance of the system.
• The built prototype Mistnet has been transferred to Plato (a federated learning framework) and Sedna (AI Toolkit over KubeEdge).

Awards


USTC Outstanding Graduate 2021
Qiangwei Scholarship, 2021
Cyrus Tang Scholarship, 2017 - 2021
Challenge Cup, National Third Prize, 2020
Neural Network Intelligence (NNI) by MSRA, Outstanding Project 2020
Robotics Competition of USTC, Bronze Medal, 2019
National Undergraduate Mathematical Contest in Modeling, Second Prize, 2019
The fifth national university student entrepreneur training summer camp, Second prize, 2019

Activities

Teaching Assistant
• Probability and Statistics B. Lecturer: Prof. Weiwei Zhuang 2020.1 - 2020.6 @USTC
• Advanced Computer Programming. Lecturer: Prof. Weihai Li 2020.9 - 2020.12 @USTC
• Introduction to Cryptography. Lecturer: Prof. Weihai Li 2021.1 - 2021.6 @USTC