Zhewei Wei (魏哲巍)

魏哲巍

prof_pic.jpg

Professor (教授，博导)

Gaoling School of Artificial Intelligence
Renmin University of China
No. 59 Zhongguancun Street, Haidian District, Beijing, 100872, P.R. China

Office: Room 1715, Lide Building
Email:
Phone: (86) 010-62513716
Chinese Homepage (中文主页): gsai.ruc.edu.cn/zhewei

I am currently a Professor at Gaoling School of Artificial Intelligence, Renmin University of China. I worked as a Professor (Jul 2019 - Jul 2020), and as an Associate Professor (Sep 2014 - Jun 2019) at School of Information, Renmin University of China. I was a Postdoc researcher at MADALGO (Center for Massive Data Algorithmics), Aarhus University, from September 2012 to August 2014, working with Prof. Lars Arge. I was a Postdoc researcher at the Department of Computer Science and Engineering, HKUST, from March to August 2012. I obtained my PhD at Department of Computer Science and Engineering, HKUST in March 2012. My supervisor is Prof. Ke Yi. I received my B.Sc. Degree in the School of Mathematical Sciences at Peking University in June 2008.

Research Interests

I lead The ALGO Lab, where our research focuses on developing simple, elegant, and theoretically sound algorithms to tackle critical challenges in Artificial Intelligence and Big Data processing. Our specific areas of interest include:

  • Graph Algorithms and Graph Machine Learning
    Designing efficient algorithms to process and learn from massive graph structures.
  • Streaming Algorithms and Stream Machine Learning
    Developing algorithms capable of handling and learning from continuous, real-time data streams.
  • AI for Science
    Applying graph machine learning to solve complex problems in biology, pharmaceuticals, and other scientific disciplines.
  • AI for Social Science
    Utilizing large language model (LLM)-based multi-agent systems to model intricate human social networks.
  • AI for Databases
    Leveraging machine learning techniques to optimize database systems for enhanced performance and efficiency.

News

Feb 11, 2025 One paper “Scalable and Certifiable Graph Unlearning: Overcoming the Approximation Error Barrier” has been selected to be presented as a Spotlight at ICLR 2025.
Feb 01, 2025 One paper “Simple and Optimal Algorithms for Heavy Hitters and Frequency Moments in Distributed Models” has been accepted by STOC 2025!
Jan 23, 2025 The ALGO Lab is pleased to announce the release of the graph machine learning library Jittor Geometric, which provides detailed optimizations in graph storage, graph computation, and graph learning. It integrates and accelerates various existing graph neural network models, improving model runtime by 10% to 50% across multiple graph learning tasks compared to similar frameworks like Pytorch Geometric (PyG) and Deep Graph Library (DGL). Everyone is welcome to try it out!
Jan 23, 2025 Two paper “Scalable and Certifiable Graph Unlearning: Overcoming the Approximation Error Barrier” and “TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics” has been accepted by ICLR 2025.
Nov 29, 2024 One paper “A Survey of Estimating Number of Distinct Values” has been accepted by FCS 2025.

Awards

  • Best Research Paper Nomination, VLDB 2024
  • Young Outstanding Paper Nomination Award, World Artificial Intelligence Conference 2023
  • Test of Time Award, PODS 2022
  • Young Scientist, Pazhou Laboratory (Huangpu)
  • Teaching Model Nomination Award, Renmin University of China, 2019
  • "Outstanding Scholar" Young Scholar, Renmin University of China

Services

  • Proceedings Chair: SIGMOD/PODS 2020, ICDT 2021
  • Area Chair: ICML 2022/2023/2024, NeurIPS 2022/2023, ICLR 2023/2024, TheWebConf 2023
  • PC Member: NeurIPS 2021, ICML 2021, KDD 2021, VLDB 2020, ICDE 2021, SIGMETRICS 2020, ICBK 2019, NDBC 2018, ICLR 2023, ICDE 2023
  • Conference Reviewer: SODA, ISAAC, VLDB, ICDE, CIKM, PODS, SIGMOD, KDD
  • Journal Reviewer: TKDE, TODS, VLDBJ, TOIS, SICOMP, TALG, GEOINFORMATICA, TNNLS, TPAMI
  • Member of Journal Editorial Board: IEEE TPAMI Associate Editor, FCS Young Editor
  • Members: 中国计算机学会数据库专委会专委，中国计算机学会学术工作委员会委员，人工智能与数字经济广东省实验室（琶洲实验室）青年科学家

Talks

  • AI TIME, Matrix Sketching and Streaming Machine Learning (矩阵略图与流数据机器学习), Oct 2024 [video] [slides]
  • Academy of Mathematics and System Science, CAS, Graph Convolutional Networks: Theory and Fundamentals, Aug 2024 [slides]
  • CCF Young Computer Scientists & Engineers Forum (YOCSEF), AI4DB Algorithm with Theoretical Guarantee (有理论保证的 AI4DB 算法), Aug 2024 [slides]
  • Classical Talk@QuACT, Sublinear-Time Algorithms for Random-Walk Probability Estimation, May 2024 [slides]
  • VALSE 2023, Graph Representation Learning (图表示学习), June 2023 [slides]
  • VALSE 2021, Theoretical Basis of Graph Neural Networks (图神经网络理论基础), Oct 2021 [slides]

Teaching

  • Lecturer for Algorithm Design and Analysis (算法设计与分析): Fall 2016, Fall 2017, Fall 2018, Fall 2019, Spring 2020, Fall 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024
  • Lecturer for Graph Machine Learning (图机器学习): Fall 2021, Fall 2022, Fall 2023, Fall 2024
  • Lecturer for Seminar for Freshmen (新生研讨课): Fall 2021, Fall 2022, Fall 2023
  • Lecturer for ACM-ICPC Algorithms Design: Spring 2019
  • Lecturer for ACM-ICPC Algorithms Design: Spring 2018
  • Lecturer for Massive Data Algorithms (海量数据算法): Spring 2016, Spring 2017, Spring 2018
  • Lecturer for Operational Research (运筹学): Spring 2016
  • Lecturer for Calculus: Fall 2015
  • Lecturer for Streaming Algorithms and Related Topics: Spring 2014