Sainyam Galhotra
Assistant Professor, Computer Science, Cornell University
My research develops data science tools that make analytics more effective, reliable, and responsible, drawing on data management, causal inference, machine learning, robustness, explainability, and fairness.
Before joining Cornell, I was a Computing Innovation Fellow at the University of Chicago. I received my Ph.D. from the University of Massachusetts Amherst and my undergraduate degree from IIT Delhi.
Recent Highlights
Research Areas
All publications →Reliable Agentic Data Science
Building dependable agentic systems and data pipelines for post-training LLM workflows.
- Multi-agent reliability and self-improvement
- Data selection for fine-tuning and post-training
- Reinforcement learning for data-centric AI
- Scientific claim verification
Data Management for Analytics
Finding, preparing, joining, and explaining data for downstream analytical tasks.
- Goal-oriented data discovery
- Joinable data search
- Dataset and view discovery
Fairness, Robustness, and Explanations
Designing reliable systems that can be audited, explained, and stress-tested.
- Fair predictive modeling
- Machine unlearning tests
- Counterfactual explanations
Recent Publications
Full list →Lab & Teaching
Students
Current and former students working on data management, responsible AI, and data science systems.
View students →Teaching
Courses and materials related to databases, data science, and responsible analytics.
View teaching →Service
Program committees, reviewing, workshop organization, and broader research community service.
View service →