I'm an assistant professor in the Department of Computer Science and Engineering, College of Engineering at the University of Notre Dame. I joined the faculty in August 2017, after completing my Ph.D. in Computer Science and Technology at Tsinghua University in 2015 and two-year postdoctoral training in Computer Science at the University of Illinois at Urbana-Champaign. [C.V.]

My research focuses on data-driven user behavior modeling for applications such as future behavior prediction, social recommendation, fraud detection, event summarization, mission planning, and effective teaching. It is at the intersection of social media analysis, network science, text mining, information extraction, spatiotemporal data mining, machine learning, and artificial intelligence.

What's New

• June 2018: One regular paper was accepted to ACM BCB 2018 with long presentation. Congratulations to all the authors!
• May 2018: Last day of Data Science class. Congratulations to Samuel Alptekin, Jacob Beiter, Samuel Berning, and Benjamin Shadid winning the Best Presentation Award for their project Predicting Outcomes of Week One College Football Games! Congratulations to William Badart, Luke Duane, and Wenhao Yu winning the Best Presentation Honorable Mention for their project Determining Predictors of H-1B Approval!

• May 2018: My first student conference paper Multi-Type Itemset Embedding for Learning Behavior Success got accepted to ACM SIGKDD 2018 with long presentation. Congratulations to the leading author Mr. Daheng Wang! In this work, we propose a novel representation learning method "LearnSuc" to preserve the collective structure of a behavior's success or a plan's effectiveness. It significantly improves predictive models and recommender systems on human behaviors.

• May 2018: Three papers were accepted to ACM SIGKDD 2018 with long presentation. Congratulations to all the authors!
• February 2018: One paper was accepted to Transactions on Knowledge and Data Engineering on Automated Phrase Mining from Massive Text Corpora.
• January 2018: One workshop paper was accepted to HeteroNAM. Congradulations to Mr. Daheng Wang!

Latest Publications

• CausalTriad: Toward Pseudo Causal Relation Discovery and Hypotheses Generation from Medical Text Data, ACM BCB, 2018.
• Multi-Type Itemset Embedding for Learning Behavior Success, KDD, 2018.
• TruePIE: Discovering Reliable Patterns in Pattern-Based Information Extraction, KDD, 2018.
• TaxoGen: Constructing Topical Concept Taxonomy by Adaptive Term Embedding and Clustering, KDD, 2018.
• Automated Phrase Mining from Massive Text Corpora, TKDE, 2018.
• DPPred: An Effective Prediction Framework with Concise Discriminative Patterns, TKDE, 2018.
• MetaPAD: Meta Patten Discovery from Massive Text Corpora, KDD, 2017.
• Estimating Treatment Effect in the Wild via Differentiated Confounder Balancing, KDD, 2017.
• ContextCare: Incorporating Contextual Information Networks to Representation Learning in Medical Forum Data, IJCAI, 2017.
• Treatment Effect Estimation with Data-Driven Variable Decomposition, AAAI, 2017.
• Embedding Learning with Events in Heterogeneous Information Networks, TKDE, 2017.
• Effective Promotional Strategies Selection in Social Media: A Data-Driven Approach, TBD, 2017.

Last updated on June 12, 2018.