I am a final-year PhD student in Computer Science at University of Illinois, Urbana Champaign. I am working in the Data Mining Group under Prof. Jiawei Han.

In my research, I develop data-driven techniques and neural architectures for learning with massive, complex and noisy graph data. My interests span data mining, machine learning and statistics, with a focus on leveraging graph analysis and deep learning techniques, to a wide range of questions including information network construction, entity/relation profiling, contextualized network embedding and so on.

Before joining UIUC, I received my Bachelor of Engineering Degree in Computer Science in 2014, from the Chu Kochen Honors College, Zhejiang University. I was working in the State Key Lab of CAD&CG on machine learning with Prof. Xiaofei He.

Motivated researchers/students with strong backgrounds and interests in machine learning and network data mining are welcome to get in touch for brainstorms and discussions :)

Currently I am actively looking for tenure-track faculty positions!

Anything Exciting?

Latest News!

[2019.09] My work with students on conditional graph generation has been accepted by Neurips 2019.

[2019.08] My two new leading research papers have been accepted by CIKM 2019 and ICDM 2019, consecutively!

[2019.06] Our demo about Cube Networks has been accepted by KDD 2019.

[2019.05] I am working in Pinterest Lab this summer with the Applied Science team led by Prof. Jure Leskovec.

[2019.04] The first paper written by my students has been accepted by IJCNN 2019. Congratulations to the authors!

First-Author Papers
What do I do?

Selected Publications

Services and Activities

  • [2019.09] PC member for the 2020 AAAI Conference.
  • [2019.07] Sub-reviwer for the 2019 Neurips Conference.
  • [2019.05] PC member for the 2019 WISE Conference.
  • [2019.02] Sub-reviwer for the 2019 KDD Conference.
  • [2018.12] Sub-reviwer for the 2019 WWW Conference.
  • [2018.11] Invited Seminar Talks in Fudan University and Shanghai Jiao Tong University, Shanghai, China.
  • [2018.08] Session Chair for Embeddings and Learning for the 2018 ASONAM Conference, Barcelona, Spain.
  • [2017.10] Started to serve as a reviewer for the TKDE and TNNLS journals.
  • [2017.06] Invited Seminar Talks in Tsinghua University and University of Science and Technology of China, Beijing, China.


  • [Spring 2019] CS512: Data Mining: Principles and Algorithms.
  • [Spring 2018] CS512: Data Mining: Principles and Algorithms.
  • [Spring 2017] CS412: Introduction to Data Mining.
  • [Spring 2016] CS511: Advanced Data Management.
  • [Fall 2015] CS412: Introduction to Data Mining.

Students Mentored

  • [2019] Peiye Zhuang. Now a PhD student in UIUC, Urbana.
  • [2019] Yuxin Xiao. PhD applicant, Urbana.
  • [2018-2019] Jieyu Zhang. PhD applicant, Urbana.
  • [2018-2019] Haonan Wang. PhD applicant, Urbana.
  • [2018-2019] Dai Teng. Now a master student in UIUC, Urbana.
  • [2018-2019] Siyang Liu. Now a master student in UIUC, Urbana.
  • [2018] Xikun Zhang. Now an AI resident in Google research, New York.
  • [2018] Yichen Feng. Now a master student in UIUC, Urbana.
  • [2017-2018] Zongyi Wang. Now an SDE in Google, MTV.
  • [2017-2018] Mengxiong Liu. Now a master student in CMU, Pittsburg.
  • [2017-2018] Aravind Sankar. Now a Phd Student in UIUC, Urbana.
  • [2017] Lanxiao Bai. Now an SDE in Cerner, Kansas.
  • [2016-2017] Hanqing Lu. Now an applied scientist in Amazon, MTV.


University of Illinois, Urbana Champaign, 2014-2020
Advisor: Prof. Jiawei Han
GPA 3.92/4.0; Research interests: data mining, graph analysis, neural networks
  • Developed novel deep learning algorithms for network data mining.
  • Coordinated the SocialCube research project with DARPA under Agreement No. W911NF-17-C-0099.
  • Collaborated on the Intelligent Social Media and Sensor Stream Summarization and Situation Analysis research project with US Army Research Lab under Cooperative Agreement No. W911NF-09-2-0053.
  • Revised Prof Han’s popular textbook Data Mining: Concepts and Techniques for the 4th Edition
  • Won course project champion (CS412 Data Mining 2014 Fall UIUC) for fraud detection on Kaggle.
  • Won Yunni & Maxine Pao Memorial Fellowship for research accomplishments and leadership activities.
Chu Kochen Honors College, Zhejiang University, 2010-2014
Advisor: Prof. Xiaofei He
GPA: Major: 3.97/4.0, Overall: 3.86/4.0; Ranking: Top 2% of 201 students
  • Developed novel manifold learning algorithms for dimension reduction and image retrieval.
  • Won Chinese National Scholarship for Outstanding Merits, Zhejiang University (Top 1%).
  • Won Chinese National Fellowship for Excellent Intellects in Research, Zhejiang University (Top 1%).
Advisor: Mr. Zhongyou Wen
  • Won Yu Shouzhi scholarship (Top 1 among 800+).
  • Won First Prize in National Olympic in Informatics in Provinces.

Industry Experiences

Research Intern, Research Lab, Pinterest Inc., San Francisco
Supervisors: Dr. Aditya Pal, Prof. Jure Leskovec, Summer 2019

Empowered GraphSage for web-scale Pinterest graph embedding through efficient graph down-sampling and context-aware conditional aggregation on heterogeneous pin-board networks.

Research Intern, Places Data & AI Research, Facebook Inc., New York City
Supervisors: Dr. Do Huy Hoang, Dr. Tomas Mikolov, Summer 2018

Developed a two-step data-driven pipeline of feature generation and metric learning for place embedding to leverage ad-hoc place attributes and noisy training data towards efficient place deduplication.

Research Intern, Big Data Research, Didichuxing Inc., Beijing
Supervisor: Prof. Jieping Ye, Summer 2017

Constructed the transportation HIN (heterogeneous information network) based on DiDi's unique travel data and developed a pattern-aware HIN embedding algorithm for passenger experience prediction.

Research Intern, Research, Snapchat Inc., Los Angeles
Supervisor: Dr. Jie Luo, Summer 2016

Developed a joint learning framework of user links and attributes for friend recommendation and interest targeting. Implemented a Spark pipeline and scaled up to millions of nodes and billions of edges.

Software Engineer Intern, Demographics ads serving, Google Inc., Seattle
Supervisor: Dr. Tianyi Wu, Summer 2015

Implemented data extraction and inventory analysis pipeline using flume C++. Implemented an online simulation of ads serving and an offline optimal algorithm based on max flow to analyze the inventory.



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