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.
Call for Journal Article Participation: I am a co-Topic Editor for the Research Topic "Computational Behavioral Modeling for Big User Data" (click me!) in Big Data Networks, Frontiers in Big Data. Keywords: Recommender Systems, Misbehavior Detection, Social Network Analysis, Graph Learning, Deep Learning. Please submit your abstract if your research falls in the topic!
Our 44-pages Survey on Knowledge-Enhanced Text Generation is released on arXiv. Here is the long reading list! (This GitHub page has over 200+ stars.)
Our KDD 2020 Tutorial on Scientific Text Mining and Knowledge Graphs is released. Please click to find slides and videos!
I am directing the Data Mining towards Decision Making (DM2) Laboratory. My research has been supported by National Science Foundation, Condé Nast Inc., Snap Inc. Research, and Notre Dame Global Gateway.
I am recruiting PhD students and visiting researchers. Drop me an e-mail (mjiang2 [at] nd.edu) if you are interested! Stay healthy, safe, and happy!
What's New
Latest Publications
- TCN: Table Convolutional Network for Web Table Interpretation,
TheWebConf, 2021.
- Few-shot Molecular Property Prediction,
TheWebConf, 2021.
- Traceability Transformed: Generating More Accurate Links with Pre-Trained BERT Models,
ICSE, 2021.
- Data Augmentation for Graph Neural Networks,
AAAI, 2021.
- A Survey of Knowledge-Enhanced Text Generation,
Preprint: arXiv: 2010.04389, 2020. (Long reading list) Led by Wenhao Yu and collaborated with Dr. Chenguang Zhu (Microsoft Research), Dr. Zhiting Hu (UCSD), and Dr. Heng Ji (UIUC).
- Structural and Textual Information Fusion for Symptom and Disease Representation Learning,
IEEE Transactions on Knowledge and Data Engineering, 2020. (In press, IF=4.935)
- Leverage Electron Properties to Predict Phonon Properties via Transfer Learning for Semiconductors,
Science Advances, 2020. (IF=12.530)
- Biomedical Knowledge Graphs Construction from Conditional Statements,
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020.
- Precise Temporal Slot Filling via Truth Finding with Data-Driven Commonsense,
Knowledge and Information Systems, 2020.
- Phrase-level Pairwise Topic Modeling to Uncover Helpful Peer Responses to Online Suicidal Crises,
Nature Humanities and Social Sciences Communications, 2020.
- A Technical Question Answering System with Transfer Learning,
EMNLP, 2020. (demo) [github] [video]
- Tri-Train: Automatic Pre-fine Tuning between Pre-training and Fine-tune Training for SciNER,
EMNLP-Findings, 2020.
- Error-bounded Graph Anomaly Loss for GNNs,
CIKM, 2020.
- GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction,
CIKM, 2020.
- Learning Attribute-Structure Co-Evolutions in Dynamic Graphs,
KDD-DLG, 2020. (best paper award)
- Early Fraud Detection with Augmented Graph Learning,
KDD-DLG, 2020.
- GNN-based Graph Anomaly Detection with Graph Anomaly Loss,
KDD-DLG, 2020.
- Scientific Text Mining and Knowledge Graphs,
KDD, 2020. (tutorial)
- Multi-modal Network Representation Learning: Methods and Applications,
KDD, 2020. (tutorial)
- Calendar Graph Neural Networks for Modeling Time Structures in Spatiotemporal User Behaviors,
KDD, 2020.
- Crossing Variational Autoencoders for Answer Retrieval,
ACL, 2020.
- Identifying Referential Intention with Heterogeneous Contexts,
TheWebConf, 2020.
- Experimental Evidence Extraction in Data Science with Hybrid Table Features and Ensemble Learning,
TheWebConf, 2020.
- Few-Shot Knowledge Base Completion,
AAAI, 2020.
- Graph Few-shot Learning via Knowledge Transfer,
AAAI, 2020.
Completed Projects
Last updated on January 15, 2021.