Romila Pradhan

Assistant Professor

Contact Info

765-496-0793

Knoy 291

West Lafayette

Dr. Pradhan is an Assistant Professor in the School of Applied and Creative Computing at �鶹��Ʒ in West Lafayette, Indiana. Her research interests are in the areas of data management and data science. Her research is driven by the need to build trustworthy and responsible decision-making systems. More recently, Dr. Pradhan has been building systems that facilitate explainability, fairness, and accountability of data-driven decision-making systems.

Previously, Dr. Pradhan held a Postdoctoral Researcher position in the Halıcıoğlu Data Science Institute at the University of California San Diego, and was a Visiting Assistant Professor in the Department of Computer Science at �鶹��Ʒ. She has a Ph.D. in Computer Science from �鶹��Ʒ, and a B.S. and M.S. in Mathematics and Computing from the Indian Institute of Technology (IIT) Kharagpur, India.

Research lab wesbite:

Research Interests

Machine Learning
Responsible data science
Data management

Education History

Ph.D., Computer Science, �鶹��Ʒ, West Lafayette, IN, 2018
M.S., Mathematics and Computing, Indian Institute of Technology (IIT) Kharagpur, India, 2008
B.S., Mathematics and Computing, Indian Institute of Technology (IIT) Kharagpur, India, 2008

Honors and Awards

NSF CAREER Award (2023)
Google Research Scholar Award (2022)

Publications and Presentations

Shashank Thandri, and Romila Pradhan, "Label Flipping for Group Fairness", 14th International Workshop on Quality in Databases (QDB) at the 51st VLDB Conference, 2025
Jahid Hasan, and Romila Pradhan, "Explanations for Machine Learning Pipelines under Data Drift", Workshop on Human-In-the-Loop Data Analytics (HILDA) at the ACM International Conference on Management of Data (SIGMOD), 2025
Tanmay Surve, and Romila Pradhan, "Explaining Fairness Violations using Machine Unlearning", 28th International Conference on Extending Database Technology (EDBT), 2025
Ekta, and Romila Pradhan, "Valuation-based Data Acquisition for Machine Learning Fairness", 13th International Workshop on Quality in Databases (QDB) at the 50th VLDB Conference, 2024
Romila Pradhan and Tianyi Li, "Human-in-the-Loop Bias Mitigation in Data Science", Human-Centered AI Workshop (HCAI), Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS) 2022.
Romila Pradhan, Jiongli Zhu, Boris Glavic and Babak Salimi, "Interpretable Data-Based Explanations for Fairness Debugging", 2022 ACM International Conference on Management of Data (SIGMOD), 2022.
Jiongli Zhu, Romila Pradhan, Boris Glavic and Babak Salimi, "Generating Interpretable Data-Based Explanations for Fairness Debugging using Gopher", 2022 ACM International Conference on Management of Data (SIGMOD), 2022.
Romila Pradhan, Aditya Lahiri, Sainyam Galhotra and Babak Salimi, "Explainable AI: Foundations, Applications, Opportunities for Data Management Research", 2022 ACM International Conference on Management of Data (SIGMOD), 2022. (Tutorial)
Romila Pradhan, Aditya Lahiri, Sainyam Galhotra and Babak Salimi, "Explainable AI: Foundations, Applications, Opportunities for Data Management Research", 38th IEEE International Conference on Data Engineering (ICDE), 2022. (Tutorial)
Sainyam Galhotra*, Romila Pradhan* and Babak Salimi, "Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals", 2021 ACM International Conference on Management of Data (SIGMOD), 2021.
Sainyam Galhotra, Romila Pradhan and Babak Salimi, "Feature Attribution and Recourse via Probabilistic Contrastive Counterfactuals", Algorithmic Recourse Workshop, Thirty-eighth International Conference on Machine Learning (ICML), 2021.
Paul Y. Wang, Sainyam Galhotra, Romila Pradhan and Babak Salimi, "Demonstration of Generating Explanations for Black-Box Algorithms Using Lewis", Proceedings of the Very Large Databases (PVLDB) Endowment, 2021.
Romila Pradhan and Sunil Prabhakar, "AuthIntegrate: Toward Combating False Data on the Internet", 1st Workshop on Truth Discovery and Fact Checking: Theory and Practice, 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2019.
Romila Pradhan, "Guided Data Fusion", �鶹��Ʒ, 2018 (Ph.D. Thesis)
Romila Pradhan, Walid G. Aref and Sunil Prabhakar, "Leveraging Data Relationships to Resolve Conflicts from Disparate Data Sources", 29th International Conference on Database and Expert Systems Applications (DEXA), 2018.
Romila Pradhan, Siarhei Bykau and Sunil Prabhakar, "A Framework to Integrate User Feedback for Rapid Conflict Resolution", 34th IEEE International Conference on Data Engineering (ICDE), 2018. (Demonstration)
Romila Pradhan, Siarhei Bykau and Sunil Prabhakar, "Staging User Feedback toward Rapid Conflict Resolution in Data Fusion", 2017 ACM International Conference on Management of Data (SIGMOD), 2017.