Email: yuz9 [AT] illinois [DOT] edu
Office: home Room 1117, Siebel Center for Computer Science, 201 N. Goodwin Ave, Urbana, IL 61801

About Me

I am a Ph.D. student in the Data Mining Group at University of Illinois at Urbana-Champaign, advised by Prof. Jiawei Han. I finished my M.Sc. study in the same group in 2019. My research interests are text mining and text-rich network mining.

Prior to UIUC, I received my B.Sc. degree in Computer Science from Peking University in 2017, advised by Prof. Yan Zhang.

In summer 2021, I interned at Microsoft Research Redmond (virtually), working with Dr. Iris Shen.

In summer 2020, I interned at Microsoft Research Redmond (virtually), working with Dr. Iris Shen and Dr. Yuxiao Dong.

In summer 2016, I visited Carnegie Mellon University, working with Prof. Kathleen M. Carley.

For further information, please see my CV.

What’s New [What’s Not New…]

2021-07 to 2021-12 Invited to be a PC member of AAAI 2022 and WWW 2022.

2021-10-11 Our work on Motif-Enhanced Text Classification was accepted by WSDM 2021! The acceptance rate is 20.2% (159/786).

2021-08-26 Our paper on Distantly Supervised NER was accepted by EMNLP 2021 main conference!

2021-08-14 Attended KDD 2021 virtually to give a tutorial.

2021-01 to 2021-06 Invited to be a PC member of ACL 2021, NeurIPS 2021, CIKM 2021, and ICLR 2022.

2021-05-17 Started my (second) summer internship at Microsoft Research Redmond, working with Dr. Iris Shen.

2021-05-15 Our tutorial proposal on Text Embeddings and Pre-Trained Language Models was accepted by KDD 2021 tutorial track!

Selected Publications [Google Scholar]

(* indicates equal contribution. Unless otherwise specified, the paper is accepted as a research track long/regular paper.)


MotifClass: Weakly Supervised Text Classification with Higher-order Metadata Information [arXiv] [code]
Yu Zhang*, Shweta Garg*, Yu Meng, Xiusi Chen, and Jiawei Han.
WSDM 2022. Tempe, AZ, USA.


MATCH: Metadata-Aware Text Classification in A Large Hierarchy [PDF] [arXiv] [code]
Yu Zhang, Zhihong Shen, Yuxiao Dong, Kuansan Wang, and Jiawei Han.
WWW 2021. Ljubljana, Slovenia.

Hierarchical Metadata-Aware Document Categorization under Weak Supervision [PDF] [arXiv] [code]
Yu Zhang, Xiusi Chen, Yu Meng, and Jiawei Han.
WSDM 2021. Jerusalem, Israel.

Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training [PDF] [arXiv] [code]
Y. Meng, Y. Zhang, J. Huang, X. Wang, Y. Zhang, H. Ji, and J. Han.
EMNLP 2021. Punta Cana, Dominican Republic.

On the Power of Pre-Trained Text Representations: Models and Applications in Text Mining [PDF] [website]
Yu Meng, Jiaxin Huang, Yu Zhang, and Jiawei Han.
KDD 2021. Singapore. (Tutorial)


Minimally Supervised Categorization of Text with Metadata [PDF] [arXiv] [code]
Yu Zhang*, Yu Meng*, Jiaxin Huang, Frank F. Xu, Xuan Wang, and Jiawei Han.
SIGIR 2020. Xi’an, China.

Heterogeneous Network Representation Learning: A Unified Framework with Survey and Benchmark [PDF] [arXiv] [code]
Carl Yang*, Yuxin Xiao*, Yu Zhang*, Yizhou Sun, and Jiawei Han.
IEEE TKDE. Accepted.

Hierarchical Topic Mining via Joint Spherical Tree and Text Embedding [PDF] [arXiv] [code]
Y. Meng, Y. Zhang, J. Huang, Y. Zhang, C. Zhang, and J. Han.
KDD 2020. San Diego, CA, USA.

Discriminative Topic Mining via Category-Name Guided Text Embedding [PDF] [arXiv] [code]
Y. Meng, J. Huang, G. Wang, Z. Wang, C. Zhang, Y. Zhang, and J. Han.
WWW 2020. Taipei.


HiGitClass: Keyword-Driven Hierarchical Classification of GitHub Repositories [PDF] [arXiv] [code]
Yu Zhang, Frank F. Xu, Sha Li, Yu Meng, Xuan Wang, Qi Li, and Jiawei Han.
ICDM 2019. Beijing, China.

Cross-type Biomedical Named Entity Recognition with Deep Multi-Task Learning [PDF] [arXiv] [bioRxiv] [code]
Xuan Wang, Yu Zhang, Xiang Ren, Yuhao Zhang, Marinka Zitnik, Jingbo Shang, Curtis Langlotz, and Jiawei Han.
Bioinformatics. Oxford Academic. Volume 35, Issue 10.

Integrating Local Context and Global Cohesiveness for Open Information Extraction [PDF] [arXiv] [code]
Q. Zhu, X. Ren, J. Shang, Y. Zhang, A. El-Kishky, and J. Han.
WSDM 2019. Melbourne, VIC, Australia.


Weakly-supervised Relation Extraction by Pattern-enhanced Embedding Learning [PDF] [arXiv] [code]
Meng Qu, Xiang Ren, Yu Zhang, and Jiawei Han.
WWW 2018. Lyon, France.

Open Information Extraction with Global Structure Constraints [PDF] [code]
Q. Zhu, X. Ren, J. Shang, Y. Zhang, F. F. Xu, and J. Han.
WWW 2018. Lyon, France. (Poster, Best Poster Award Runner-up)


RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation [PDF] [arXiv] [code]
Yu Zhang, Wei Wei, Binxuan Huang, Kathleen M. Carley, and Yan Zhang.
CIKM 2017. Singapore. (Short)

Top-K Influential Nodes in Social Networks: A Game Perspective [PDF] [arXiv] [code]
Yu Zhang and Yan Zhang.
SIGIR 2017. Shinjuku, Tokyo, Japan. (Short)

Honors and Awards

2021 WWW 2021 Student Scholarship
2021 WSDM 2021 Student Travel Grant
2020 SIGIR 2020 Student Travel Grant
2018 WWW 2018 Best Poster Award Runner-up
2017 Best Undergraduate Thesis Award, School of EECS, Peking University (10/310+)
2017 Outstanding Graduates, Peking University
2017 SIGIR 2017 Student Travel Grant
2016 Kwang-Hua Scholarship
2015 May 4th Scholarship
2014 National Scholarship (Top 1%)
2011/2012 First Prize, National Olympiad in Informatics in Provinces

Professional Services

Conference Program Committee
WWW 2022; CIKM 2021
NeurIPS 2021; ICLR 2021-2022; AAAI 2022
ACL 2021; EMNLP 2020; NAACL-HLT 2021; Reviewer of ACL Rolling Review

Journal Reviewer
IEEE Transactions on Knowledge and Data Engineering (TKDE)
ACM Transactions on Knowledge Discovery from Data (TKDD)
IEEE Transactions on Big Data (TBD)

Student Volunteer
SIGIR 2020


I was born and raised in Shanghai.

I like taking MOOCs when I intend to learn something as a beginner. Some MOOCs I have finished: Networks (2015-04), Model Thinking (2015-05), Probability (2015-05), Economics (2018-08).

I played bridge during my high school and undergraduate time.