Aishwarya Mandyam

Aishwarya Mandyam is a Computer Science PhD candidate at Stanford University whose research develops machine learning methods for safe, interpretable, and personalized automated clinical decision-making, with work spanning reinforcement learning, off-policy evaluation, conformal prediction, doubly robust estimation, and synthetic or augmented data for healthcare policy evaluation.

AI-for-Science Advances Depend on Evaluation, Not Just Generation

In a Stanford AI+Science lightning-talk session introduced by Surya Ganguli, four young researchers made a common case: AI-for-science is useful only when paired with rigorous evaluation. Aishwarya Mandyam, Amar Venugopal, Steven Dillmann and Alda Elfarsdóttir each treated AI systems or outputs as claims to be tested — through uncertainty estimates for clinical policies, causal checks on generated text, executable benchmarks for scientific agents, and empirical links between corporate climate language and later emissions.

Stanford HAIMay 15, 20267 min read