Biography

I am an Assistant Professor in Computer Science at Emory University. Before that, I received my Ph.D. in Computer Science at University of Illinois, Urbana Champaign, where I was working in the Data Mining Group led by Prof. Jiawei Han. Further before, I received my B.Eng. in Computer Science in 2014, from the Chu Kochen Honors College, Zhejiang University, where I was working in the State Key Lab of CAD&CG under Prof. Xiaofei He.

My research interests lie in graph data mining, applied machine learning, and structured information systems, as well as their applications in knowledge bases, recommender systems, healthcare networks and biomedical informatics.

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

Contact

Latest News!

[2021.09] Our four papers got accepted by NeurIPS 2021. Three of them were under my supervision-- FedSage (subgraph-level federated learning), GCFL (graph-level federated learning) and EGI (GNN transferability). FedSage was selected for a spotlight presentation (3%). Great work, team!

[2021.04] Our three papers on graph neural networks (secure graph generation, embedding dimension selection and robust neighborhood aggregation) have been accepted by IJCAI 2021.

[2021.01] Haonan Wang got a paper on gradient item retrieval accepted by WWW 2021 during his internship in Alibaba. Congratulations!

[2020.12] Our survey and benchmark paper on heterogeneous network representation learning has been accepted by IEEE TKDE. All code and data are available at https://github.com/yangji9181/HNE.

[2020.10] We are honored to receive the Best Paper Award from ICDM 2020! (1 out from 930 submissions and 91 acceptances)

[2020.10] Congratulations to Wenjie and Yuanzhen for getting our two papers on evolutionary graph prediction and dynamic network embedding accepted by WSDM 2021 (AR 18.6%).

[2020.10] Congratulations to Yanchao for getting our work on multi-facet recommendation with spherical embedding accepted by ICDE 2021 (full paper research track first round).

[2020.08] Two regular long papers on taxonomy-aware network embedding and text-rich network community detection have been accepted by ICDM 2020 (9.8%). One step closer towards PhD graduation :).

[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.

Citations
Selected Publications
Close Mentees
Countries

Selected Publications

Since 2021


Before 2021 (Ph.D. graduation)

Services and Activities

Journal Editing, Conference Organizing and Proposal Reviewing

  • [2022 (to be)] Workshop Chair, CIKM 2022.
  • [2022 (to be)] Web Chair, KDD 2022.
  • [2021-date] Associate Editor, IEEE Transactions on Big Data.
  • [2021-date] Associate Editor, Big Data Journal, Mary Ann Liebert, Inc..
  • [2021-date] Guest Editor, Frontiers in Big Data and Artificial Intelligence.
  • [2021] Session Chair, Graph Algorithms, kDD 2021, Virtual Event.
  • [2021] Session Chair, Special Networks and Dynamics, WWW 2021, Virtual Event.
  • [2021] Session Chair, Recommender Systems, ICDE 2021, Virtual Event.
  • [2018] Session Chair, Embedding and Learning, ASONAM 2018, Barcelona, Spain.
  • [2021] Panelist, NSF.

Peer Reviewing

  • [2019-date] The International Conference on Machine Learning (ICML).
  • [2019-date] The Conference on Neural Information Processing Systems (NeurIPS).
  • [2019-date] The AAAI Conference on Artificial Intelligence (AAAI).
  • [2019-date] The International Joint Conference on Artificial Intelligence (IJCAI).
  • [2018-date] The ACM Conference on Knowledge Discovery and Data Mining (KDD).
  • [2018-date] The International World Wide Web Conference (WWW).
  • [2018-date] The IEEE International Conference on Data Mining (ICDM).
  • [2018-date] The ACM International Conference on Web Search and Data Mining (WSDM).
  • [2018-date] The SIAM International Conference on Data Mining (SDM).
  • [2017-date] The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD).
  • [2017-date] The ACM International Conference on Information and Knowledge Management (CIKM).
  • [2017-date] The International Conference on Web Information Systems Engineering (WISE).

  • [2019-date] The IEEE Transactions on Big Data (TBD).
  • [2019-date] The ACM Transactions on Information Systems (TOIS).
  • [2019-date] The ACM Transactions on Intelligent Systems and Technology (TIST).
  • [2018-date] The IEEE Multidisciplinary Open Access Journal (Access).
  • [2018-date] The IEEE Transactions on Knowledge and Data Engineering (TKDE).
  • [2017-date] The IEEE Transactions on Neural Networks and Learning Systems (TNNLS).

Research Seminars

  • [2021.10] Amazon (ML Tech Talk), Seattle, USA.
  • [2021.07] University of South California (virtual), Los Angeles, USA.
  • [2020.03] University of Sydney (virtual), Sydney, Australia.
  • [2020.03] University of Florida, Gainesville, USA.
  • [2020.02] University of Simon Fraser University, Burnaby, Canada.
  • [2020.02] Emory University, Atlanta, USA.
  • [2020.01] Zhejiang University, Hangzhou, China.
  • [2019.12] University of British Columbia, Vancouver, Canada.
  • [2019.11] Northwestern University, Chicago, USA.
  • [2019.09] Great Lakes Workshop on Data Science in University of Notre Dame, Portage, USA.
  • [2018.11] Fudan University and Shanghai Jiao Tong University, Shanghai, China.
  • [2018.03] Snap Inc., Los Angeles, USA.
  • [2017.06] Tsinghua University and University of Science and Technology, Beijing, China.

Teaching

  • [Fall 2020] Instructor, CS 253: Data Structures and Algorithms, Emory University.
  • [Spring 2020] Instructor, CS 253: Data Structures and Algorithms, Emory University.
  • [Fall 2020] Instructor, CS 584: Graph Data Mining, Emory University.
  • [Spring 2020] TA, CS 412: Introduction to Data Mining, UIUC/Coursera
  • [Spring 2019] Lead TA, CS 512: Data Mining: Principles and Algorithms, UIUC.
  • [Spring 2018] Lead TA, CS 512: Data Mining: Principles and Algorithms, UIUC.
  • [Spring 2017] TA, CS 412: Introduction to Data Mining, UIUC.
  • [Spring 2016] TA, CS 511: Advanced Data Management, UIUC.
  • [Fall 2015] TA, CS 412: Introduction to Data Mining, UIUC.

Student Mentoring

Current Students

  • [2020-current] Jiaying Lu. PhD student in Emory, Atlanta.
  • [2020-current] Hejie Cui. PhD student in Emory, Atlanta.
  • [2020-current] Han Xie. PhD student in Emory, Atlanta.
  • [2020-current] Xuan Kan. PhD student in Emory, Atlanta.
  • [2021-current] Ran Xu. PhD student in Emory, Atlanta.
  • [2020-current] Yanchao Tan. Visiting PhD student from Zhejiang University, Hangzhou, China.
  • [2020-current] Ke Zhang. Visiting PhD student from Hong Kong University, Hong Kong, China.
  • [2021-current] Olivia Song. Honors undergraduate student in Emory, Atlanta.
  • [2021-current] David Wei. Honors undergraduate student in Emory, Atlanta.
  • [2020-current] Celia Hu. Undergraduate student in Emory, Atlanta.
  • [2020-current] Oliver Li. Undergraduate student in Emory, Atlanta.
  • [2021-current] Sophy Huang. Undergraduate student in Emory, Atlanta.
  • [2021-current] Leisheng Yu. Undergraduate student in Emory, Atlanta.

Previous Students

  • [2020-2021] Mingyue Tang, PhD student in UVA, Virginia.
  • [2020-2021] Ramraj Chandradevan, PhD student in Emory, Georgia.
  • [2020-2021] Xiangjue Dong. PhD student in TAMU, Texas.
  • [2020-2021] Yidan Xu. PhD student in UMich, Michigan.
  • [2018-2020] Jieyu Zhang. PhD student in UW, Washington.
  • [2018-2020] Haonan Wang. PhD student in UIUC, Illinois.
  • [2018-2020] Yuxin Xiao. Master student in CMU, Philadelphia.
  • [2019] Peiye Zhuang. PhD student in UIUC, Illinois.
  • [2019] Wenhan Shi. SDE in LinkedIn, California.
  • [2018-2019] Siyang Liu. SDE in ServiceNow, California.
  • [2018-2019] Dai Teng. SDE in Amazon, Washington.
  • [2018] Sayantani Basu. PhD student in UIUC, Illinois.
  • [2018] Xikun Zhang. PhD student in Stanford, California.
  • [2018] Yichen Feng. Founder of QuestionBank LLC, Shanghai.
  • [2017-2018] Mengxiong Liu. Master student in CMU, Philadelphia.
  • [2017-2018] Zongyi Wang. SDE in Google, California.
  • [2017-2018] Aravind Sankar. PhD student in UIUC, Illinois.
  • [2017] Lanxiao Bai. SDE in Cerner, Kansas.
  • [2016-2017] Hanqing Lu. Applied scientist in Amazon, California.

Education

University of Illinois, Urbana Champaign, 2014-2020
Advisor: Prof. Jiawei Han
GPA 3.95/4.0; Research interests: graph data mining, network data science, applied machine learning
  • Thesis: Multi-Facet Graph Mining with Contextualized Projections.
  • 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.
  • Contributed to the revision of Prof. Han’s popular textbook Data Mining: Concepts and Techniques for the 4th Edition.
  • Won the Yunni & Maxine Pao Memorial Fellowship for research accomplishments and leadership activities.
  • Received the Best Paper Award from ICDM 2020 (1 out from 930 submissions across the world).
  • Received the UIUC 2020 Doctoral Dissertation Completion Fellowship (awarded to 20 candidates from 20 departments out from 74 nominations from 48 departments across the whole university).
  • Received the KDD Dissertation Award Nomination (11 in total world-wide).
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.

Remote Research Contractor, Economics Graph Research, LinkedIn Co., Sunnyvale
Supervisors: Dr. Myungwan Kim, Dr. Shipeng Yu, 2018-2019

Developed a relation profiling algorithm based on multiple signals including user attributes, link structures and diffusive messages in the social network with novel multi-modal graph autoencoders.

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 LLC, 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.

Traveling

China

Keywords:
home, family, best food

USA

Keywords:
Alaska, road trip, national parks, corn fields

Canada

Keywords:
cold and vast, magnificent mountains and lakes

Mexico

Keywords:
tequila, hearty people, colorful and vivid towns

Caribbean

Keywords:
peaceful, adventurous, aow, kite surf, island hopping, 7 countries

Chile

Keywords:
Easter island, moai, peaseful, diverse views, volcano, gobi, glacier

Peru

Keywords:
Amazon jungles, Machu Picchu, Inca trail, black beach

Ecuador

Keywords:
Galapagos, equatorial, overnight buses, lack of order

Bolivia

Keywords:
Uyuni, altitude, salt laguna, flamingo, geyser, dead sea

Cuba

Keywords:
nostalgia, no internet, vintage car, carriage, cigar, rum, chill

Australia

Keywords:
magnificent ocean view, seafood, beef, mines, kangaroo

Malaysia

Keywords:
Semporna, scuba diving, jalan alor night food, massage

France

Keywords:
Mont Saint-Michel, Eiffel, Musee du Louvre, Notre Dame, Loire valley castles, Eze

UK

Keywords:
great cocktails, speakeasy, gin, rain, Oxford, Edinburgh, Scotch whiskey

Spain

Keywords:
Antoni Gaudi, paella, tapas, Sangria

Ireland

Keywords:
green, Guinness, windy, lively night life

Greece

Keywords:
Acropolis of Athens, white and blue, expensive and inefficient

Turkey

Keywords:
kebab, sheesha, Rome, Muslim, everyone knows Chinese, balloon

Nepal

Keywords:
namaste, temples, buddha, harshish

Thailand

Keywords:
college graduation trip, vikings, motorcycle, rain, lovely old times