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 Computational Behavior Modeling for applications such as behavior prediction, recommendation, fraud detection, event detection, planning, and decision making. It is at the intersection of network science, text mining, information extraction, machine learning, and artificial intelligence.

I am directing the Data Mining towards Decision Making (DM2) Laboratory. My research has been supported by National Science Foundation, Condé Nast Inc., and Global Gateway.

• NSF CRII: III: Complementarity Learning for Contextual Behavior Modeling. (10/01/2019 - 09/30/2021)
• NSF SHF: Medium: Collaborative Research: Semantically-Enhanced Software Traceability for Supporting Human-Centric Tasks. (08/15/2019 - 08/14/2023)
• Global Gateway: Digital Empires: Structured Biographical and Social Network Analysis of Early Chinese Empires. (05/01/2019 - 08/31/2020)
• Condé Nast: Representation Learning for Modeling and Predicting User Engagement and Propensity for Conversion Through the Engagement Funnel. (01/21/2019 - 05/20/2020)

I am recruiting Ph.D. students and visiting researchers. DM2 Lab has at least three openings. Drop me an e-mail (mjiang2@nd.edu) if you are interested!

What's New

• January 2020: Two full papers with oral presentation were accepted to TheWebConf 2020. Congratulations to Wenhao!
• November 2019: Three papers were accepted to AAAI 2020 on representation learning.
• October 2019: One regular paper was accepted to IEEE BIBM on scientific literature search, with acceptance rate of 18%.
• August 2019: One paper was accepted to EMNLP on scientific text mining.
• July 2019: One paper was accepted to MICCAI.
• May 2019: I am thrilled to receive the Global Gateway Faculty Research Award with Prof. Liang Cai from the Department of History.
• April 2019: Two paper were accepted to ACM SIGKDD 2019 Research Track: TUBE and MIMO.
• March 18, 2019: Congratulations to Ms. Xueying Wang for passing Master Thesis Defense: "Improving Information Extraction via Truth Finding with Data-Driven Commonsense"
• February 2019: One research paper and one demo paper were accepted to TheWebConf 2019.

Latest Publications

• Identifying Referential Intention with Heterogeneous Contexts, TheWebConf, 2020.
• Experimental Evidence Extraction in Data Science with Hybrid Table Features and Ensemble Learning, TheWebConf, 2020.
• Multi-label Patent Categorization with Non-local Attention-based Graph Convolutional Network, AAAI, 2020.
• Few-Shot Knowledge Base Completion, AAAI, 2020.
• Graph Few-shot Learning via Knowledge Transfer, AAAI, 2020.
• CTGA: Graph-based Biomedical Literature Search, IEEE BIBM, 2019.
• Multi-input Multi-output Sequence Labeling for Joint Extraction of Fact and Condition Tuples from Scientific Text, EMNLP, 2019.
• MSU-Net: Multiscale Statistical U-Net forReal-time 3D Cardiac MRI Video Segmentation, MICCAI, 2019.
• TUBE: Embedding Behavior Outcomes for Predicting Success, KDD, 2019. (Oral)
• The Role of 'Condition': A Novel Scientific Knowledge Graph Representation and Construction Model, KDD, 2019.
• Tablepedia: Automating PDF Table Reading in an Experimental Evidence Exploration and Analytic System, TheWebConf, 2019. (Demo)
• A Novel Unsupervised Approach for Precise Temporal Slot Filling from Incomplete and Noisy Temporal Contexts, TheWebConf, 2019.
• Graph Few-shot Learning via Knowledge Transfer Graph Representation Learning Workshop (GRL) at NeurIPS, 2019.
• Faceted Hierarchy: A New Graph Type to Organize Scientific Concepts and a Construction Method Workshop on Graph-Based Natural Language Processing (TextGraphs) at EMNLP, 2019.
• A Study of Person Entity Extraction and Profiling from Classical Chinese Historiography International Workshop on EntitY REtrieval (EYRE) at CIKM, 2019.
• Constructing Information-Lossless Biological Knowledge Graphs from Conditional Statements International Workshop on Data Mining in Bioinformatics (BioKDD) at KDD, 2019.

Last updated on January 19, 2020.