Scholar
Yingtong Dou
Google Scholar ID: m5GpWLYAAAAJ
Research Scientist, Visa Inc.
Citations & Impact
Citations
3,079
H-index
17
i10-index
18
Publications
20
Co-authors
10
list available
Publications
Cited
0
Resume (English only)
Academic Achievements
- Multiple papers accepted by EMNLP 2025, TheWebConf 2023, TMLR, KDD 2024, NeurIPS 2024, IJCAI 2023, etc.
- Served as PC member for several international conferences such as TheWebConf 2026, KDD'25, RecSys'24, NeurIPS'24, etc.
- Released PyGOD package and accepted by JMLR MLOSS Track.
- Developed TransNet neural network and released as a defensive publication.
- Ph.D. dissertation: 'Robust Graph Learning for Misbehavior Detection'.
- Received Papers with Code Contributor Award.
- Delivered talks at Wells Fargo, Novartis Data Science Seminar, Machine Learning in Finance Workshop@KDD'22, etc.
- Released a benchmark for node outlier detection and Python library PyGOD.
- A paper was selected as the best paper honorable mention at CIKM 2022.
- TOIS paper became the most-cited TOIS paper in 2022.
Research Experience
- Serving as a research scientist at Visa Research, working on payment foundation models, deep learning for fraud detection, and various LLM applications.
Education
- Received a B.E. from Beijing University of Posts and Telecommunications in 2017; Ph.D. in Computer Science from the University of Illinois Chicago in 2022, advised by Prof. Philip S. Yu.
Background
- Research interests include transaction data modeling, ML trust and safety, and graph mining. Currently working at Visa Research's Foundational AI team, focusing on payment foundation models, deep learning for fraud detection, and various LLM applications.
Miscellany
- Blog about GNN-based anomaly detection featured on TigerGraph Blog.
