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Bingzhe Wu(吴秉哲)
wubingzheagent at gmail dot com
wubingzhe at pku dot edu

PhD students
Department of Computer Science and Engineering (affiliate)
Center for Energy-efficient Computing and Applications (CECA)
Peking University

Publications  /  Google Scholar  /  CV  /  Github  /  zhihu(知乎) /  个人博客

I am currently a senior researcher at Tencent AI Lab AI Lab. Prior to that, I received PhD's degree in computer science department of Peking university and Bachelor's degree in Mathematical Science from Peking University.
Research

My main research interests lie in privacy-preserving machine learning (PPML), Bayesian Learning, Uncertainty estimation and their applications in medical fields, such as medical image analysis, drug discovery and EHR data analysis.

In particular, I'm interested in developing theoretical tools for explainable privacy-preserving machine learning. I also aim to combine different techniques such as differential privacy, federated learning, and Bayesian learning for developing PPML algorithms which have better trade-offs among model accuracy, privacy protection strength, computation efficiency and useability.

On this basis, I apply these methods and tools for rich applications such as pathological image classification, federated GNN, recommender system and privacy-preserving Deep Learning as a Service.

Awards
  • 2021: ACM SIGSAC China Outstanding Doctoral Dissertation Award.
  • 2021: Beijing outstanding graduates.
  • 2021: Peking University outstanding graduates
  • The first place in PhD Group of 2021 CCF Academic Show.
  • 2020: Apple Ph.D Fellowship (Only one place in the China mainland.).
  • 2020: The Ten Most Talented Researchers in EECS of Peking University.
  • 2018: China National Scholarship
  • 2011: The first-prize winner of China Middle School Mathematical Competition
News
  • "Drug AI OOD Dataset Curator and Benchmark" Paper "DrugOOD" released, here comes the project page. Will be continuously updated.
  • I am invited for World-wide Global Young Scientist Summit
  • I am named as Apple PhD fellowship(Apple website and Peking University)
  • I am named as The Ten Most Talented Researchers in EECS of Peking University(学术十杰).
  • I am serving as secretary of IEEE P2830 Shared Machine Learning Working Group.
  • I start a new internship as a research intern at Ant Financial.
  • 2019.03.15 I finish my internship at IBM research, China.
  • 2017.10.10 I start a new internship at IBM research, China.
  • 2017-07-2017-08 I take part in the first Google Tensorflow summer camp at Jeju, Korea.
Academica Service
  • Conference Reviewer: ICML, ICLR, NeurIPS, AAAI, CVPR and ICCV.
  • Transaction Reviewer: TECS
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