About Me


My name is Olawale (Wale) Salaudeen, and I am an postdoctoral associate at MIT in the Healthy ML Lab, led by Professor Marzyeh Ghassemi. Prior to my postdoc, I earned a PhD in Computer Science at the University of Illinois at Urbana-Champaign and the Stanford Trustworthy AI Research (STAIR) Lab at Stanford University, advised by Sanmi Koyejo. I am honored to have received a Sloan Scholarship, Beckman Graduate Research Fellowship, GEM Associate Fellowship, and an NSF Miniature Brain Machinery Traineeship. Additionally, I am fortunate to have interned at Sandia National Laboratories, Google Brain, Cruise LLC, and the Max Planck Institute for Intelligent Systems.

Before Illinois, I received a Bachelors of Science in Mechanical Engineering with minors in Computer Science and Mathematics from the Texas A&M University.

Research Interests

I am broadly interested in reliable and trustworthy machine learning. My research goal is to improve the robustness of machine learning models for real-world decision-making. Particularly, I aim to develop the principles and practices of robust generalization, adaptation, and evaluation in machine learning. Additionally, I am interested in diverse applications, including neuroscience/neuroimaging, healthcare, and algorithmic fairness. My experience and interests span generative AI, statistical machine learning, multi-modal deep learning, domain adaptation/generalization, causality-inspired machine learning, and probabilistic graphical models.

I am very happy to discuss new research directions; please reach out if there is shared interest!

Mentorship

I am happy to mentor students with overlapping research interests. Particularly for undergrads at MIT, programs like UROP are a great mechanism for mentorship. More generally, I am very happy and available to give advice and feedback on applying to and navigating both undergraduate and graduate programs in computer science and related disciplines – especially for those to whom this type of feedback and guidance would be otherwise unavailable.

You can reach me at olawale [at] mit [dot] edu.

Selected Recent News

  • Fall 2024. Our paper titled “On Domain Generalization Datasets as Proxy Benchmarks for Causal Representation Learning” will appear at the Neurips 2024 workshop on causal reprsentation learning as an Oral Presentation.
  • Fall 2024. I joined the Healthy ML Lab, led by Professor Marzyeh Ghassemi, at MIT as a postdoctoral associate!
  • Summer 2024. I successfully defended my PhD dissertation titled “Towards External Valid Machine Learning: A Spurious Correlations Perspective”!
  • Spring 2024. I gave a talk on AI for critical systems at the MobiliT.AI forum (May 28-29)!
  • Spring 2024. I gave a talk at UIUC Machine Learning Seminar on the external validity of ImageNet; artifacts here!
  • Spring 2024. Recent work demonstrating the external validity of ImageNet model/architecture rankings – ImageNot: A contrast with ImageNet preserves model ranking – is now available on arXiv!
  • Winter 2024. Two papers on machine learning under distribution shift will appear at AISTATS 2024 (see Publications)!
  • Winter 2024. I have returned to Stanford from MPI!
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Previous Mentees