I study problems at the intersection of data management and machine learning. My research is driven by the need to build trustworthy and responsible decision-making systems.
Recently, I have been working in the area of responsible data science, developing systems aimed at enabling explainability, fairness, and accountability of data-driven decision-making systems.
In the past, I have worked on problems in data integration, focusing on resolving conflicts in data integrated from disparate data sources and ensuring end-users can trust the quality of the integrated data.
I am always looking for PhD students to collaborate with. If you are interested in data management or responsible data analytics, feel free to contact me with your CV/resume and a couple of sentences describing your research interests, and consider applying to Purdue CIT!
I am teaching a graduate course on Responsible Data Management in Spring 2023-- check out the course webpage for more details.
NEWS
11/22 Delighted to receive funding from the Center for Advancing Safety of Machine Intelligence (CASMI) for building safe, equitable, and beneficial AI systems 10/22 Position paper with Tianyi Li on human-in-the-loop bias mitigation in data science accepted to the Human-Centered AI Workshop at NeurIPS 2022 6/22 Presented our paper on debugging fairness of machine learning models (Gopher) at SIGMOD 22 6/22 & 5/22 Gave tutorial on Explainable AI and Opportunities for Data Management Research at SIGMOD 22 and ICDE 22 4/22 Honored to receive a Google Research Scholar Award! Thanks, Google! 3/22 Chaired the research talk session on "Data Quality and Curation" at EDBT 22 3/22 Serving on the PC of CIKM 22 (Short paper track) 2/22 Demonstration paper of Gopher accepted to SIGMOD 22 2/22 Tutorial on Explainable AI and Opportunities for Data Management Research accepted to SIGMOD 22 ... more
12/21 Tutorial on Explainable AI and Opportunities for Data Management Research accepted to ICDE 22 12/21 Paper on generating interpretable, data-based explanations for debugging fairness in ML models (Gopher) accepted to SIGMOD 22 12/21 Serving on the PC of SIGKDD 22 11/21 Gave a talk about Lewis at MIT CSAIL's Semantic Data Management reading group 9/21 Serving on the PC of SIGMOD 22 8/21 Started as a tenure-track assistant professor in the Department of Computer and Information Technology at Purdue University 7/21 Paper on feature attribution and recourse via probabilistic contrastive counterfactuals accepted to ICML Algorithmic Recourse workshop 5/21 Presented Lewis at SIGMOD 21 5/21 Demonstration paper of Lewis accepted to VLDB 21 4/21 Serving on the PC of EDBT 22 4/21 Joining the Department of Computer and Information Technology as an Assistant Professor 3/21 Paper on probabilistic contrastive counterfactuals to explain black-box algorithms (Lewis) accepted to SIGMOD 21
Shashank Thandri (MS, Purdue CIT, Spring 2023--)
Sathvika Kotha (MS, Purdue CIT, Fall 2022--)
Ekta (MS, Purdue CIT, Fall 2022--)
Tanmay Surve (MS, Purdue CIT, Spring 2022--)
Ahana Bhattacharyya (BS, SUNY Buffalo CS, Spring 2023)
Anusha Sarraf (BS, Purdue CS, Spring 2023)
Manas Paranjape (BS, Purdue CS, Fall 2022)
TEACHING
CNIT 58100-RDM: Responsible Data Management. Spring 23, Fall 22
CNIT 48700: Database Administration. Fall 22, Fall 21
CNIT 39200: Enterprise Data Management. Spring 22
SERVICE
Program Committee Member 24 EDBT 23 SIGKDD, ICDE PhD Symposium, FAccT, SSS 22 SIGMOD, SIGKDD, EDBT, CIKM (Short Paper Track)