Mert Kosan

Staff Research Scientist

Research areas:   Graph Machine Learning, Explainability, Anomaly Detection, Human-in-the-loop


Mert joined Visa Research as a Staff Research Scientist in June 2023, right after completing his Ph.D. in Computer Science from University of California, Santa Barbara (UCSB). Mert also received B.Sc. in Computer Science from Sabanci University (Istanbul, Turkiye) in 2018. He worked with the same Visa Research team for three summer internships. During his internships, he and the team published one academic paper and filed three patents.

In the period since 2017, Mert has developed research interests in the areas of graph machine learning, explainability of deep black-box models, anomaly detection, and human-in-the-loop systems. Notably, his paper “Global Counterfactual Explainer for Graph Neural Networks” is selected among the 10 best papers in WSDM ’23 and received the best paper award in Machine Learning on Graphs Workshop in WSDM ’23. Mert also contributes to the research community by being reviewer on multiple machine learning journals and conferences. He worked as Registration Chair for KDD ’23.


  1. Mert Kosan, “Transparent Representation Learning for Graphs and Human-AI Collaboration”, Ph.D. Dissertation, 2023.
  2. Mert Kosan, Zexi Huang, Sourav Medya, Sayan Ranu, Ambuj Singh. “Global Counterfactual Explainer for Graph Neural Networks.” Web Search and Data Mining (WSDM), 2023. 
  3. Mert Kosan, Arlei Silva, Sourav Medya, Brian Uzzi, Ambuj Singh. “Event Detection on Dynamic Graphs”. Association for the Advancement of Artificial Intelligence, Deep Learning on Graphs (DLG-AAAI) 2023. 
  4. Mert Kosan, Linyun He, Shubham Agrawal, Hongyi Liu, Chiranjeet Chetia. "AI Decision Systems with Feedback Loop Active Learner". Web Search and Data Mining, Crowd Science (WSDM CANDLE), 2023.
  5. Mert Kosan, Debajyoti Kar, Debmalya Mandal, Sourav Medya, Arlei Silva, Palash Dey, Swagato Sanyal. “Feature-based Individual Fairness in k-Clustering”.  Autonomous Agents and Multiagent Systems (AAMAS), 2023, Extended Abstract. 


  1. Linyun He, Chiranjeet Chetia, Jianhua Huang, Shubham Agrawal, Mert Kosan. “Method, system, and computer program product for auto-profiling anomalies”, 2023.