Hello, welcome to my homepage! I am currently a research scientist at Facebook. I obtained my PhD degree from Computer Science Department at University of Illinois at Urbana-Champaign. I was fortunate to have Prof. Jiawei Han as my PhD adviser. Before that, I received my bachelor degrees from Peking University.
My research interest mainly lies in applied machine learning, including information network analysis, distribution representation learning, and matrix estimation.
- University of Illinois at Urbana-Champaign, Aug 2012 - May 2017 Department of Computer Science Doctor of Philosophy in Computer Science
- Peking University, Aug 2008 - May 2012 School of Electronics Engineering and Computer Science Bachelor of Science in Computer Science
- Peking University, Aug 2009 - May 2012 National School of Development in Economics Bachelor of Science in Economics (Double Major)
Publications(* indicates equal contribution.)
- Liyuan Liu, Jingbo Sahng, Frank Xu, Xiang Ren, Huan Gui , Jian Peng and Jiawei Han, Empower Sequence Labeling with Task-Aware Neural Language Model, in Proc. of 2018 AAAI Conf. on Artificial Intelligence (AAAI'18), New Orleans, LA, 2018.
- Yu Shi, Po-Wei Chan, Honglei Zhuang, Huan Gui and Jiawei Han, PReP: Path-Based Relevance from a Probabilistic Perspective in Heterogeneous Information Networks, in Proc. of 2017 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'17), Halifax, Nova Scotia, Canada, 2017.
- Liyuan Liu, Xiang Ren, Qi Zhu, Shi Zhi, Huan Gui, Heng Ji and Jiawei Han, Heterogeneous Supervision for Relation Extraction: A Representation Learning Approach, in Proc. of 2017 Conf. on Empirical Methods in Natural Language Processing (EMNLP'17), Copenhagen, Denmark, 2017.
- Huan Gui*, Jialu Liu*, Fangbo Tao, Meng Jiang, Brandon Norick, Lance Kaplan and Jiawei Han, Embedding Learning with Events in Heterogeneous Information Networks, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2017.
- Huan Gui, Jiawei Han, Quanquan Gu, Towards Faster Rates and Oracle Property for Low-Rank Matrix Estimation, in Proc. of 2016 Int. Conf. on Machine Learning (ICML'16), New York City, NY, 2016. [paper] [supp]
- Huan Gui*, Jialu Liu*, Fangbo Tao, Meng Jiang, Brandon Norick, Jiawei Han, Large-Scale Embedding Learning in Heterogeneous Event Data, in Proc. of 2016 Int. Conf. on Data Mining (ICDM'16), Barcelona, Spain, 2016. [paper]
- Huan Gui, Haishan Liu, Xiangrui Meng, Anmol Bhasin, Jiawei Han, Downside Management in Recommender Systems , in Proc. of 2016 IEEE/ACM Int. Conf. on Advances in Social Networks Analysis and Mining (ASONAM'16), San Francisco, CA, 2016.
- Huan Gui, Ya Xu, Anmol Bhasin, Jiawei Han, Network A/B Testing: From Sampling to Estimation, in Proc. of 2015 Int. Conf. on World-Wide Web (WWW'15), Florence, Italy, 2015. [paper]
- Huan Gui*, Quanquan Gu*, and Jiawei Han, Robust Tensor Decomposition with Gross Corruption, in Proc. of 2014 Conf. on Advances in Neural Information Processing Systems (NIPS'14), Montreal, Quebec, Canada, 2014. [paper]
- Huan Gui, Yizhou Sun, Jiawei Han, and George Brova, Modeling Topic Diffusion in Multi-Relational Bibliographic Information Networks, in Proc. of 2014 ACM Int. Conf. on Information and Knowledge Management (CIKM'14), Shanghai, China, 2014. [paper]
Honors and Awards
- The 3rd place of Vandalism Detection Task, WSDM Cup’17.
- The 3rd place of Triple Scoring Task, WSDM Cup’17.
- Outstanding Teaching Assistant, University of Illinois at Urbana-Champaign, Fall 2016.
- ICML'16 Travel Award.
- NIPS’14 Travel Award.
- The Miaozhen Scholarship for the academic year of 2012, Peking University.
- The 3rd Prize of Samsung International Scholarship for the academic year of 2010.
- The 1st Prize of 2011 Computer Aided Design Contest of integrated Circuits, R. O. China.
- May 2016 - Aug 2016, Google Research NYC, Intern
- May 2015 - Aug 2015, Google NYC, Intern
- May 2014 - Aug 2014, LinkedIn MTV, Intern
- May 2013 - Aug 2013, LinkedIn MTV, Intern
- Dec 2012 - June 2012, Microsoft Research Asia, Intern
- PC member of WSDM’18, CIKM’17
- Journal reviewer of TKDE, TIST, PLOS ONE, Neurocomputing, SMC
- Fall 2016, Fall 2014, Fall 2013, An Introduction to Data Mining (CS 412), Teaching Assistant
- Spring 2016, Data Mining: Principles and Algorithms (CS 512), Teaching Assistant
- Fall 2015, Artificial Intelligence (CS 440), Teaching Assistant
- Spring 2017, Spring 2014, Pattern Discovery in Data Mining (Coursera), Teaching Assistant
- Spring 2017, Spring 2014, Clustering in Data Mining (Coursera), Teaching Assistant