Olawale (Wale) Salaudeen is a postdoctoral associate at MIT in the Healthy ML Lab. He earned a PhD in Computer Science from the University of Illinois at Urbana-Champaign and was affiliated with the Stanford Trustworthy AI Research (STAIR) Lab. He is broadly interested in the principles and practices of reliable and trustworthy AI for social and societal good. His research primarily focuses on the robustness of artificial intelligence (AI) in real-world decision-making. His prior work has explored improving AI robustness under distribution shift, including generalization, adaptation, and evaluation, as well as advancing the understanding of effective AI/ML evaluation practices. His research spans various application areas, including biological imaging, algorithmic fairness, healthcare, and AI policy.
Wale has received a Sloan Scholarship, Beckman Graduate Research Fellowship, GEM Associate Fellowship, and an NSF Miniature Brain Machinery Traineeship. Throughout his doctoral studies, he further expanded his expertise through research internships at Sandia National Laboratories, Google Brain Causality, and the Max Planck Institute for Intelligent Systems’ Social Foundations of Computation department. Additionally, he gained practical experience in machine learning through an internship at Cruise LLC.
Before pursuing his PhD, Wale obtained a Bachelor of Science in Mechanical Engineering from Texas A&M University, with minors in Computer Science and Mathematics.