Tutorials

• [T12] Knowledge-Augmented Methods for Natural Language Processing with Zhang, Xu, Jiang, Yu, Ren, Lin, at the Annual Meeting of the Association for Computational Linguistics (ACL), May 2022.
• [T11] Knowledge-Enriched Natural Language Generation with Yu, Hu, Wang, Ji, Rajani, at the Conference on Empirical Methods in Natural Language Processing (EMNLP), November 2021.
• [T10] Data Efficient Learning on Graphs with Zhang, Li, at the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), August 2021.
• [T9] Scientific Text Mining and Knowledge Graphs with Jingbo Shang at the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), August 2020.
• [T8] Multi-modal Network Representation Learning: Methods and Applications with Chuxu Zhang, Xiangliang Zhang, Yanfang Ye, and Nitesh Chawla at the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), August 2020.
• [T7] Multi-modal Network Representation Learning: Methods and Applications with Chuxu Zhang, Xiangliang Zhang and Nitesh Chawla at the SIAM International Conference on Data Mining (SDM), May 2020. (accepted but cancelled due to coronavirus pandemic)
• [T6] Data-Driven Approaches towards Malicious Behavior Modeling with Srijan Kumar, VS Subrahmanian and Christos Faloutsos at the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Halifax, Nova Scotia, Canada, August 2017. [Description]
• [T5] Mining Entity-Relation-Attribute Structures from Massive Text Data with Jingbo Shang, Xiang Ren and Jiawei Han at the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Halifax, Nova Scotia, Canada, August 2017.
• [T4] Building Structured Databases of Factual Knowledge from Massive Text Data with Xiang Ren, Jingbo Shang and Jiawei Han at the ACM SIGMOD International Conference on Management of Data (SIGMOD), Chicago, U.S., May 2017.
• [T3] Constructing Structured Information Networks from Massive Text Corpora with Xiang Ren, Jingbo Shang and Jiawei Han at the International World Wide Web Conference (WWW), Perth, Australia, April 2017.
• [T2] Data-Driven Behavioral Analytics: Observations, Representations and Models with Peng Cui and Jiawei Han at the ACM International Conference on Information and Knowledge Management (CIKM), Indianapolis, U.S., October 2016.
• [T1] Behavior Modeling in Social Networks: From Micro to Macro with Peng Cui at the IEEE International Conference on Data Mining (ICDM), Atlantic City, U.S., November 2015.

Teaching

• Fall 2016: UIUC CS412: Introduction to Data Warehousing and Data Mining. Substitute instructor. Taught Chapter 4 (data warehousing, OLAP, and data cube). [slides]
• Fall 2016: UIUC CS412: Introduction to Data Warehousing and Data Mining. Course project advisor. Supervised WSDM Cup 2017 Triple Scoring projects. [slides] [freebase features of person entities]
• Fall 2016: UIUC CS598: Advanced Topics in Information Retrieval. Guest lecturer. Talked about Automatic Attribute Discovey. [slides]
• Spring 2017: UIUC CS512: Data Mining: Principles and Algorithms. Guest lecturer. Talked about Data-Driven Behavioral Analytics with Networks. [I2CS Echo 360] [references]
• Summer 2017: UIUC CS412: Introduction to Data Warehousing and Data Mining. Instructor.
• Fall 2017: Notre Dame CSE 40647/60647: Data Science. Instructor.
• Spring 2018: Notre Dame CSE 40647/60647: Data Science. Instructor.
• Fall 2018: Notre Dame CSE 40647/60647: Data Science. Instructor.
• Fall 2019: Notre Dame CSE 40647/60647: Data Science. Instructor.
• Spring 2020: Notre Dame CSE 60236: Computational Behavior Modeling. Instructor.
• Fall 2020: Notre Dame CSE 40647/60647: Data Science. Instructor.
• Spring 2021: Notre Dame CSE 60236: Computational Behavior Modeling. Instructor.
• Fall 2021: Notre Dame CSE 40647/60647: Data Science. Instructor.
• Spring 2022: Notre Dame CSE 60236: Computational Behavior Modeling. Instructor.
• Fall 2022: Notre Dame CSE 40647/60647: Data Science. Instructor.