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 advancing the technology of graph data mining, applied machine learning, and structured information systems, as well as their applications in biomedical informatics, knowledge bases, social networks and recommender systems.
[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.
Empowered GraphSage for web-scale contextualized recommendation through context-aware aggregation and Hadoop-based stream training on heterogeneous pin-board networks.
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.
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.
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.
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.
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.