TILOS is a U.S. National Science Foundation (NSF) Institute for Learning-enabled Optimization at Scale, funded by NSF with additional support from Intel Corporation. Our mission is to become the nexus of learning, optimization, and the leading edge of practice for three high-stage areas: chips, networks, and robotics. A partnership of faculty from University of California, San Diego, Massachusetts Institute of Technology, National University, University of Pennsylvania, University of Texas at Austin, and Yale University, NSF TILOS use-domain research pioneers learning-enabled optimizations that transform chip design, robotics, communication networks, and other use domains that are vital to our nation’s health, prosperity and welfare. Our foundational research pursues five main pillars:

  • Bridging discrete and continuous optimization.
  • Distributed, parallel, and federated optimization.
  • Optimization on manifolds.
  • Dynamic decisions under uncertainty.
  • Nonconvex optimization in deep learning.
A diagram representing the interconnectedness of the various components of TILOS mission
FEATURED PRESENTATION
Big Data, Better Answers: Optimization at Scale with Courtney Paquette

Recordings of past TILOS Seminars and other presentations are available at tilos.ai/recorded_talks.
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Congratulations to Nisheeth Vishnoi for his election to the 2026 Class of IEEE Fellows!

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