Research

Conference and Journal Publications

1. Varun Babbar*, Stark Guo*, Cynthia Rudin
   “What is Different Between These Datasets?” A Framework for Explaining Data Distribution Shifts
   Journal of Machine Learning Research (JMLR), 2025.
   Paper

2. Varun Babbar*, Hayden McTavish*, Cynthia Rudin, Margo Seltzer
   Near-Optimal Decision Trees in a SPLIT Second
   International Conference on Machine Learning (ICML), 2025. (Oral, ~Top 1% of submissions)
   Paper Code

3. Varun Babbar*, Zachery Boner*, Margo Seltzer, Cynthia Rudin
   Falling Trees: A Model Class for Interpretable Risk Prioritisation
   International Conference on Machine Learning (ICML), 2026. (Spotlight, ~Top 2% of submissions)
   Paper

4. Yixiao Wang*, Hayden McTavish*, Varun Babbar*, Margo Seltzer, Cynthia Rudin
   CLARITree: Cholesky and Lookahead Accelerations for Regression with Interpretable Piecewise Linear Trees
   International Conference on Machine Learning (ICML), 2026.
   Paper

5. Zakk Heile*, Hayden McTavish*, Varun Babbar, Margo Seltzer, Cynthia Rudin
   From Rashomon Theory to PRAXIS: Efficient Decision Tree Rashomon Sets
   International Conference on Machine Learning (ICML), 2026.
   Paper Code

6. Varun Babbar, Umang Bhatt, Adrian Weller
   On the Utility of Prediction Sets in Human-AI Teams
   International Joint Conference on Artificial Intelligence (IJCAI), 2022. (Oral, Top 3% of submissions)
   Paper Poster

7. Antonios Georgiadis*, Varun Babbar*, Fran Silavong, Sean Moran, Rob Otter
   ST-FL: Style Transfer Preprocessing in Federated Learning for COVID-19 segmentation
   SPIE Medical Imaging 2022: Imaging Informatics for Healthcare, Research, and Applications
   Paper Poster

8. Aamir Mustafa, Aliaksei Mikhailiuk, Dan Andrei Iliescu, Varun Babbar, Rafal K Mantiuk
   Training a Task-Specific Image Reconstruction Loss
   Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022
   Paper Code

Workshop Publications

1. Zakk Heile, Varun Babbar, Hayden McTavish, Cynthia Rudin
   Efficient Rashomon Set Approximation for Decision Tree Models
   NeurIPS 2025, ML x OR Workshop: Mathematical Foundations and Operational Integration of Machine Learning for Uncertainty-Aware Decision-Making
   Paper

2. Varun Babbar, Umang Bhatt, Miri Zilka, Adrian Weller
   Conformal Prediction for Resource Prioritisation in Predicting Rare and Dangerous Outcomes
   NeurIPS Workshop on Human in the Loop Learning, 2022
   Paper Poster

3. Agathe Lherondelle, Varun Babbar, Yash Satsangi, Fran Silavong, Shaltiel Eloul, Sean Moran
   Topical: Learning Repository Embeddings from Source Code using Attention
   In The 1st Workshop on Software Engineering Challenges in Financial Firms, International Conference on Software Engineering (ICSE) 2024
   Paper

Patents

1. Antonios Georgiadis, Fanny Silavong, Sean Moran, Rob Otter, Varun Babbar
   Systems and Methods For Noise Agnostic Federated Learning, 2023
   Patent

2. Peter Maciver, Varun Babbar, Sean Moran
   Systems and Methods for Automated Application and Platform Generation, 2025
   Patent

Thesis

1. Varun Babbar
   Set Valued Predictions for Human-AI Teams
   MEng Thesis - University of Cambridge (Prize for outstanding thesis)
   Thesis