About

Since Sept. 2020, Wentao Zhang (张文涛) is pursuing his Ph.D. degree in Computer Science at Peking University, under the supervision of Prof. Bin Cui. He previously interned in HKUST working with Prof. Lei Chen, Tencent working with the Angel team, and Apple Research working with Meng Cao, Ping Huang and Danny Bickson.

Email: wentao.zhang@pku.edu.cn

Office: Room 425, Yanyuan Building, Peking University, Beijing, China, 100871.

Research Interests

Graph Machine Learning from the following three perspectives:

  • Data: data privacy, data collection, data generation and data correction.

  • Model: scalable, flexible, and efficient graph learning.

  • System: large-scale distributed training, AutoML.

What's New

  • June 2021: One paper as third author, related to our AutoML system – VocalnoML, has been accepted by the coference VLDB 2021.
  • June 2021: One paper as co-first author, related to the graph data privacy, was submitted to the journal VLDBJ 2021.
  • May 2021: One paper as first author, related to the scalable graph learning, was submitted to the coference NeurIPS 2021.
  • May 2021: One paper as first author, related to the graph data collection, was submitted to the coference NeurIPS 2021.
  • May 2021: One paper as collaborator, related to the large scale k-core decomposition, was submitted to the coference CIKM 2021.
  • May 2021: One paper as first author, related to sparse graph data, has been accepted by the coference SIGKDD 2021.
  • May 2021: One paper as co-first author, related to Graph Decomposition and GNN, has been accepted by the coference SIGKDD 2021.
  • May 2021: One paper as third author, related to our blackbox optimization (BBO) system – OpenBox, has been accepted by the coference SIGKDD 2021.
  • April 2021: One paper as first author, related to graph data selection, received major revision from the coference VLDB 2021.
  • April 2021: As the only person in Chinese mainland, I was supported by the Apple Scholars in AI/ML PhD fellowship. Many thanks to Apple!
  • April 2021: One paper as co-first author got major revision from the journal TKDE 2021.
  • April 2021: One survey paper as corrsponding author, related to GNN-based Recommendation, was submitted to the journal ACM Computing Surveys.
  • March 2021: One paper as first author has been accepted by the coference SIGMOD 2021. Looking forward to the meeting in Xi’an this summer!

Awards

  • Apple PhD Fellowship, 2021
  • Leo KoGuan Scholarship of PKU (Top 1%), 2020
  • Academic Innovation Award of PKU (Top 0.5%), 2020
  • Pacemaker to Merit Student of PKU (Top 1%), 2020
  • National Scholarship of PKU (Top 1%), 2019
  • Merit Student of PKU (Top 5%), 2019
  • Academic Excellence Award of PKU (Top 5%), 2018
  • Outstanding Winner of the BDIC big data competition (1/575), 2018

Contributed Open-source Projects

  • Angel: a high-performance distributed machine learning and graph computing platform.

  • Volcano-ML: a powerful AutoML system, which automates feature engineering, algorithm selection and hyperparameter tuning.

  • OpenBox: an efficient open-source system designed for solving generalized black-box optimization (BBO) problems.