Zhen Wang (王桢)

I am currently an associate professor at Sun Yat-sen University (SYSU). During the years of my Ph.D. (mainly as a research intern at MSRA for more than three years), I have pursued the goal of embedding everything (entity, word, sentence, paragraph, etc.). In my experience as an engineer for Alibaba Cloud, I have been lucky to work with people from RISELab who kindly acknowledge my contributions and let me become a committer of Ray. Before initiating my faculty career, I was a staff of DAMO Academy, with many kind leaders and colleagues.

I have a broad interest in machine learning and data mining. Currently, our team focuses on utilizing HPC+AI to solve challenging scientific problems. If you are also interested in such a direction, don’t hesitate to get in touch with me (joneswong[dot]ml[at]gmail[dot]com)!

Education

Sun Yat-sen University, Guangzhou, Guangdong, China

  • Ph.D., Computer Applied Technology, Sep 2012 - Jun 2017
  • B.E., Software Engineering, Sep 2008 - Jun 2012

Research Experience

Microsoft Research Asia (MSRA), Beijing, China

  • Research Intern, Data Mining and Enterprise Intelligence Group, Mentor: Dr. Jun Yan and Dr. Wei-Ying Ma, Feb 2016 – Apr 2017
    • Data-driven metaphor learning (demo)
  • Research Intern, Machine Learning Group, Mentor: Dr. Jianwen Zhang and Dr. Zheng Chen, Oct 2013 – Jan 2016
    • Fact-based Q&A (demo)
    • Heterogenous data embedding (product)
  • Research Intern, Web Search and Mining Group, Mentor: Dr. Zhongyuan Wang and Dr. Haixun Wang, Oct 2011 – Jun 2012
    • Fact extraction from Web tables (demo)
    • Short text representation (product)

Alibaba group and Tsinghua University joint post-doc, Advisor: Dr. Jingren Zhou and Dr. Minlie Huang, Nov 2018 - 2020

  • Reinforcement learning in E-commerce scenarios

Publications (google scholar)

(*Equal contribution.)

  • Liuyi Yao, Zhen Wang, Yuexiang Xie, Yaliang Li, Weirui Kuang, Daoyuan Chen, Bolin Ding. Is Sharing Neighbor Generator in Federated Graph Learning Safe?. TKDE 2024.
  • Pin Chen, Luoxuan Peng, Rui Jiao, Qing Mo, Zhen Wang, Wenbing Huang, Yang Liu, Yutong Lu. Learning Superconductivity from Ordered and Disordered Material Structures. NeurIPS 2024.
  • Tianchi Liao, Jialong Chen, Lele Fu, zhen Wang, Zibin Zheng, Chuan Chen. A Swiss Army Knife for Heterogeneous Federated Learning: Flexible Coupling via Trace Norm. NeurIPS 2024.
  • Jinjia Feng, Zhen Wang, Zhewei Wei, Hongteng Xu, Yaliang Li and Bolin Ding. Federated Heterogeneous Contrastive Distillation for Molecular Representation Learning. CIKM 2024.
  • Yuedong Yang, Jiahua Rao, Jiancong Xie, Qianmu Yuan, Deqin Liu, Zhen Wang, Yutong Lu, Shuangjia Zheng. A Variational Expectation-Maximization Framework for Balanced Multi-scale Learning of Protein and Drug Interactions. Nature Communications 2024.
  • Weirui Kuang*, Zhen Wang*, Zhewei Wei, Yaliang Li, Bolin Ding. When Transformer Meets Large Graphs: An Expressive and Efficient Two-View Architecture. TKDE 2024.
  • Zhen Wang, Yaliang Li, Bolin Ding, Yule Li, Zhewei Wei. Exploring Neural Scaling Law and Data Pruning Methods for Node Classification on Large-scale Graphs. WWW 2024.
  • Zhen Wang*, Weirui Kuang*, Ce Zhang, Bolin Ding, Yaliang Li. FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization. ICML 2023. pdf
  • Xu Chen, Zhen Wang, Shuncheng Liu, Yaliang Li, Kai Zeng, Bolin Ding, Jingren Zhou, Han Su, Kai Zheng. BASE: Bridging the Gap between Cost and Latency for Query Optimization. VLDB 2023.
  • Yuxiang Xie*, Zhen Wang*, Dawei Gao, Daoyuan Chen, Liuyi Yao, Weirui Kuang, Yaliang Li, Bolin Ding, Jingren Zhou. FederatedScope: A Flexible Federated Learning Platform for Heterogeneity. VLDB 2023. pdf
  • Runlin Lei, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei. EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks. NeurIPS 2022. pdf
  • Jinjia Feng, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei, Hongteng Xu. MGMAE: Molecular Representation Learning by Reconstructing Heterogeneous Graphs with A High Mask Ratio. CIKM 2022. pdf
  • Yaliang Li, Bolin Ding, Zhen Wang, Yuexiang Xie, Dawei Gao, Liuyi Yao, Daoyuan Chen, Weirui Kuang, Hongzhu Shi, Jingren Zhou. A Practical Introduction to Federated Learning. KDD 2022 Tutorial (website)
  • Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou. FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning. KDD 2022. (ADS Track Best Paper Award). pdf
  • Zhen Wang, Yaliang Li, Zhewei Wei, Weirui Kuang, Bolin Ding. Graph Neural Networks with Node-wise Architecture. KDD 2022. pdf code
  • Dawei Gao, Yuexiang Xie, Zimu Zhou, Zhen Wang, Yaliang Li, Bolin Ding. Finding Meta Winning Ticket to Train Your MAML. KDD 2022. pdf
  • Yuexiang Xie, Zhen Wang, Yaliang Li, Ce Zhang, Jingren Zhou, Bolin Ding. iFlood: A Stable and Effective Regularizer. ICLR 2022. pdf
  • Shaoyun Shi, Yuexiang Xie, Zhen Wang, Bolin Ding, Yaliang Li, Min Zhang. Explainable Neural Rule Learning. WWW 2022. pdf
  • Yiqing Xie, Zhen Wang, Carl Yang, Yaliang Li, Bolin Ding, Hongbo Deng, Jiawei Han. KoMen: Domain Knowledge Guided Interaction Recommendation for Emerging Scenarios. WWW 2022. pdf code
  • Yaliang Li, Zhen Wang, Yuexiang Xie, Bolin Ding, Ce Zhang, Kai Zeng, Rong Zhu. AutoML: From Methodology to Application. CIKM 2021 Tutorial (website).
  • Yaliang Li, Zhen Wang, Yuexiang Xie, Bolin Ding, Ce Zhang. AutoML: A Perspective where Industry Meets Academy. KDD 2021 Tutorial (website).
  • Yuexiang Xie*, Zhen Wang*, Yaliang, Li, Bolin Ding, Nezihe Merve Gürel, Ce Zhang, Minlie Huang, Wei Lin, Jingren Zhou. FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data. KDD 2021. pdf
  • Zhao Li, Junshuai Song, Zehong Hu, Zhen Wang, Jun Gao. Constrained Dual-level Bandit for Personalized Impression Regulation in Online Ranking Systems. TKDD 2021. pdf
  • Daoyuan Chen, Yaliang Li, Minghui Qiu, Zhen Wang, Bofang Li, Bolin Ding, Hongbo Deng, Jun Huang, Wei Lin, and Jingren Zhou. AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search. IJCAI 2020. pdf
  • Fei Xiao, Zhen Wang, Haikuan Huang, Jun Huang, Xi Chen, Hongbo Deng, Minghui Qiu. AliISA: Creating an Interactive Search Experience in E-commerce Platforms. SIGIR 2019 Demo. pdf
  • Zehong Hu, Zhen Wang, Zhao Li, Shichang Hu, Shasha Ruan, Jie Zhang. Fraud Regulating Policy for E-Commerce via Constrained Contextual Bandits. AAMAS 2019. pdf
  • Zhen Wang, Xu Hu, Zehong Hu, Minghui Qiu, Jun Huang. Chapter 5 of Artificial Intelligence for Prosthetics-challenge solutions. NurIPS 2018 RL Challenge Tech Report. pdf
  • Huaping Zhong, Jianwen Zhang, Zhen Wang, Hai Wan, Zheng Chen. Aligning Knowledge and Text Embeddings by Entity Descriptions. EMNLP 2015 Short Paper. pdf
  • Zhen Wang, Jianwen Zhang, Jianlin Feng, Zheng Chen. Knowledge Graph and Text Jointly Embedding. EMNLP 2014. pdf
  • Zhen Wang, Jianwen Zhang, Jianlin Feng, Zheng Chen. Knowledge Graph Embedding by Translating on Hyperplanes. AAAI 2014. pdf code

Awards & Scholarships

  • KDD 2022 ADS Track Best Paper Award, Aug 2022
  • KDD Cup, AutoML Track, 4/149, May 2020 (our solution)
  • NeurIPS RL Challenge 5/427, Nov 2018 (our solution)
  • National Scholarship, Sep 2014
  • Silver Medal in ACM/ICPC Asia Regional Contest, Oct 2011
  • National Scholarship, Sep 2009

Working Experience

Sun Yat-sen University, Guangzhou, Guangdong, China

  • Associate Professor, May 2023 - present

Alibaba Group, Hangzhou, Zhejiang, China

  • Senior Algorithm Expert (P8), Data Analytics and Intelligence Lab, Sept 2022 - May 2023

  • Algorithm Expert (P7), Data Analytics and Intelligence Lab, June 2020 - Aug 2022

    • FederatedScope: a federated learning platform with an event-driven programming paradigm.
    • FederatedScope-GNN: a federated graph learning package and benchmark.

  • Algorithm Expert (P7), Deep Learning Algorithm Division, July 2019 - May 2020

    • Neural architecture search utilities: DARTS, ASAP, ProxylessNAS, etc.
    • Auto feature engineering utilities: AutoCross and some RL-based search strategies
    • EasyReinforcementLearning: TensorFlow-based RL package

  • Senior Algorithm Engineer (P6), Large Scale Learning-Innovative Algorithm Division, July 2017 - June 2019

    • Double 11 bundle recommendation business: a model for CTR prediction
    • A3gent: an internal deep reinforcement learning package
    • Ray: I contribute the implementations of several RL algorithms, e.g., DDPG, Rainbow, and MARWIL, to Ray RLLib and become a committer
    • Fraud regularization and flow control: constrained contextual bandit
    • Interactive shopping assistant: hierarchical reinforcement learning

Skills

  • Programming languages: Python
  • Machine leanring libraries: TensorFlow, PyTorch
  • Foreign language: English (CET-6 certification)