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, weakly supervised, and scalable techniques for knowledge discovery over massive, complex, and noisy network (graph) data. My interests span graph data mining, network data science, and applied machine learning, with a focus on designing novel graph analysis and deep learning frameworks for the effective construction, modeling, and application of real-world network data, towards tasks like conditional stucture generation, contextualized network embedding, and graph-aided recommendations.

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 students interested in machine learning and data mining are welcome to get in touch for brainstorms and discussions :)


Latest News!

[2020.05] Our work in collaboration with researchers in Pinterest and Stanford on web-scale contextualized graph neural networks has been accepted by KDD 2020 ADS track (oral 5.8%).

[2020.05] Our work in collaboration with researchers in UIUC and POSTECH (South Korea) on differentiable multi-aspect network embedding has been accepted by KDD 2020 Research track.

[2020.05] I am honored to receive the UIUC 2020 Doctoral Dissertation Completion Fellowship ($20,000), which is awarded to 20 candidates (from 20 departments) out from 74 nominations (from 48 departments) across the whole university.

[2020.05] I will be joining Emory University Dept. of Computer Science as a tenure-track Assistant Professor in September this year. Cor prudentis possidebit scientiam!

[2020.04] I am visiting University of Oxford and collaborating with Prof. Thomas Lukasiewicz and his team on structured information extraction from multi-media data this summer.

[2020.04] Our pioneering work on neural end-to-end text-to-graph generation has been accepted by SIGIR 2020.

[2020.04] My collaboration with researchers in Sun Yat-sen University on adversarial perturbation in discrete data has led to a full paper accepted by SIGIR 2020.

[2020.04] My work with students in UIUC on GNN aggregation mechanisms has been accepted by IJCAI 2020. Congratulations to the authors!

[2020.03] Our survey and benchmark project towards heterogeneous network representation learning has been released on Arxiv and GitHub.

[2020.02] I will deliver research talks in Emory University, University of Florida and University of Sydney.

[2020.01] I am visiting my alma mater, Zhejiang University, for the first time after my graduation five years ago.

[2019.11] I will deliver research talks in Northwestern University, Simon Fraser University, and University of British Columbia.

[2019.10] Our collaboration with LinkedIn Economic Graph Research has led to another paper accepted by WSDM 2020 (after CIKM 2019).

[2019.09] I am invited to attend and give a talk in the Great Lakes Workshop on Data Science.

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

[2019.08] My two new leading research papers on context-rich network construction have been accepted by CIKM 2019 and ICDM 2019.

[2019.07] The Han Family will get together in San Francisco. Happy birthday Prof Han!

[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.

Leading Projects
Close Mentees

Selected Publications

Services and Activities

  • [2020.04] PC member for the 2020 ECML-PKDD Conference.
  • [2020.03] PC member for the 2020 KDD Conference.
  • [2019.10] PC member for the 2020 WWW Conference.
  • [2019.09] PC member for the 2020 AAAI Conference.
  • [2019.05] PC member for the 2019 WISE Conference.
  • [2019.02] PC member for the 2019 KDD Conference.
  • [2018.11] PC member for the 2019 WWW Conference.
  • [2019.06] Reviewer for the 2019 NeurIPS Conference.
  • [2019.06] Reviewer for the 2019 ICDM Conference.
  • [2019.02] Reviewer for the 2019 ICML Conference.
  • [2018.09] Reviewer for the 2019 WSDM Conference.
  • [2018.06] Reviewer for the 2018 CIKM Conference.
  • [2017.12] Started to serve as a reviewer for the TNNLS journal.
  • [2017.08] Started to serve as a reviewer for the TKDE journal.
  • [2020.03] Research Seminar in University of Sydney (virtual), Sydney, Australia.
  • [2020.03] Research Seminar in University of Florida, Atlanta, USA.
  • [2020.03] Research Seminar in University of North Texas, Denton, USA.
  • [2020.02] Research Seminar in University of Simon Fraser University, Burnaby, Canada.
  • [2020.02] Research Seminar in Emory University, Atlanta, USA.
  • [2020.01] Research Seminars in Zhejiang University, Hangzhou, China.
  • [2019.12] Research Seminar in University of British Columbia, Vancouver, Canada.
  • [2019.11] Research Seminar in Northwestern University, Chicago, USA.
  • [2019.09] Invited talk at the Great Lakes Workshop on Data Science in University of Notre Dame, Portage, USA.
  • [2018.11] Research Seminars 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.
  • [2018.03] Invited Talk at Snap Inc., Los Angeles, USA.
  • [2017.06] Research Seminars in Tsinghua University and University of Science and Technology, Beijing, China.


  • [Spring 2020] TA CS412 (Coursera): Introduction to Data Mining.
  • [Spring 2019] Lead TA CS512 (UIUC): Data Mining: Principles and Algorithms.
  • [Spring 2018] Lead TA CS512 (UIUC): Data Mining: Principles and Algorithms.
  • [Spring 2017] TA CS412 (UIUC): Introduction to Data Mining.
  • [Spring 2016] TA CS511 (UIUC): Advanced Data Management.
  • [Fall 2015] TA CS412 (UIUC): Introduction to Data Mining.

Students Mentored

  • [2018-current] Jieyu Zhang. PhD student in UW, Seattle.
  • [2018-current] Haonan Wang. PhD student in UIUC, Urbana.
  • [2018-current] Yuxin Xiao. Master student in CMU, Pittsburg.
  • [2019] Peiye Zhuang. PhD student in UIUC, Urbana.
  • [2019] Wenhan Shi. SDE in LinkedIn, Sunnyvale.
  • [2018-2019] Siyang Liu. SDE in ServiceNow, Santa Clara.
  • [2018-2019] Dai Teng. SDE in Amazon, Seattle.
  • [2018] Sayantani Basu. PhD student in UIUC, Urbana.
  • [2018] Xikun Zhang. PhD student in Stanford, Stanford.
  • [2018] Yichen Feng. Founder of QuestionBank LLC, Shanghai.
  • [2017-2018] Mengxiong Liu. Master student in CMU, Pittsburg.
  • [2017-2018] Zongyi Wang. SDE in Google, Mountain View.
  • [2017-2018] Aravind Sankar. PhD student in UIUC, Urbana.
  • [2017] Lanxiao Bai. SDE in Cerner, Kansas City.
  • [2016-2017] Hanqing Lu. Applied scientist in Amazon, Mountain View.


University of Illinois, Urbana Champaign, 2014-2020
Advisor: Prof. Jiawei Han
GPA 3.92/4.0; Research interests: data mining, graph analysis, neural networks
  • Thesis: Multi-Facet Contextualized graph mining with Cube Networks.
  • 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 program with US Army Research Lab (ARL) under Cooperative Agreement No. W911NF-09-2-0053.
  • Collaborated on the Multi-Dimensional Structuring, Summarizing and Mining of Social Media Data research program with US National Science Foundation (NSF) under grant No. IIS 16-18481.
  • 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%).
NOI Coach: 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 contextualized recommendation through context-aware aggregation and Hadoop-based stream training on heterogeneous pin-board networks.

Research Intern, Places Data & AI Research, Facebook Inc., New York
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
Supervisors: Prof. Xuewen Chen, Prof. Jieping Ye, Summer 2017

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

Research Intern, Research Lab, Snap Inc., Los Angeles
Supervisors: Dr. Jie Luo, Dr. Li-Jia Li, Summer 2016

Developed a joint learning framework of user links and attributes for friend recommendation and interest targeting. Implemented a Spark pipeline and scaled it to networks with 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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