HMNTL Master Calendar

Electrical and Computer Engineering Faculty Candidate Seminar

Dr. Olawale (Wale) Salaudeen

Postdoctoral Researcher, Massachusetts Institute of Technology

Monday, April 27, 2026, 11:00 am-12:00 pm

B02 CSL Auditorium or Online via Zoom

Title: Measurement and Intervention: Reliable AI in Dynamic Environments

Abstract: AI systems that perform well in one environment often fail in another — across tasks, populations, and contexts — and we rarely know in advance where, why, or by how much. Reliable AI deployment in safety-critical settings not only demands forecasting these gaps; it also requires explaining their causes and actively mitigating them.

This talk presents a research program that characterizes and forecasts how performance generalizes across environments, diagnoses the spurious correlations and environment-dependent behaviors that drive failures, and develops methods for invariance and adaptation that sustain reliability as deployment conditions evolve. Together, this work advances a broader agenda that treats reliability as a predictive and controllable property of AI systems, not merely a retrospective metric.

Olawale (Wale) Salaudeen is a postdoctoral researcher at MIT and the Broad Institute. He received his PhD in Computer Science from the University of Illinois at Urbana-Champaign and held a visiting PhD student appointment at Stanford University.

His research advances a unified agenda of Reliable AI through Measurement and Intervention. He develops valid measurements of AI capabilities and risks and designs interventions that address the mechanisms driving system failures, particularly under distribution shift. His work connects statistical foundations, algorithm design, and high-stakes applications such as healthcare to ensure that AI systems perform reliably across changing populations and settings.

His work has appeared in leading venues including NeurIPS, AISTATS, and TMLR, and has received spotlight and oral presentations as well as a best paper award at the NeurIPS workshop on LLM Evaluation. He has also been recognized through competitive research fellowships, including the Alfred P. Sloan scholarship and AI Center Fellowship at Schmidt Sciences.