Principal Investigator

Ryan P. Adams

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Postdoctoral Fellows

Eder Medina

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Mehran Mirramezani

I am an NSF Computing Innovation Postdoctoral Scholar under the direction of Professor Ryan P. Adams in Computer Science at Princeton University. My postdoctoral research focuses on introducing novel computational modeling paradigms integrating computational mechanics, machine learning architectures, and advanced optimization techniques to develop innovative data-driven and learning-based modeling approaches for modern engineering problem-solving. Prior to Princeton, I completed my Ph.D. in Mechanical Engineering at University of California Berkeley.

Jenny (Ni) Zhan

Personal Website

I am a postdoctoral researcher in the lab, currently working on machine learning and simulation for atomic scale materials. I completed my BS from UT Austin, and PhD in chemical engineering and MS in machine learning (ML) at Carnegie Mellon University, where I worked on physical phenomena of liquid alloys using molecular dynamics simulation, neural network potentials, and uncertainty quantification methods for ML.

Graduate Students

Joshua Aduol

Samuel Barnett

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Samuel Barnett is a Ph.D. candidate in Computer Science at Princeton University, advised by Ryan Adams and Tom Griffiths. His research interests include cooperative AI, reinforcement learning, social cognition, and scalable methods for Bayesian machine learning. He was previously the Daniel M. Sachs Scholar at Princeton, and received a Master’s in Mathematics and Philosophy at the University of Oxford, where his dissertation on convergence problems in generative adversarial nets was supervised by Varun Kanade.

Alex Guerra

Deniz Oktay

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Nick Richardson

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Geoffrey Roeder

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Olga Solodova

Kathryn Wantlin

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My research interests center around the design of algorithms for machine learning and multi-agent systems that are flexible, robust, and generalizable, with applications in engineering, natural sciences, and the arts. Recently, I’ve been thinking about decentralized morphogenesis and the joint evolution of control and morphology in nature and reproducing these properties in engineered systems. Previously, I received my M.S.E. from Princeton University and my A.B. from Harvard University, both in computer science.

Undergraduate Students

Elle Lazarski

Aditya Palaparthi

Personal Website

Hi, I’m Aditya! I’m an undergraduate student studying computer science at Princeton. Here at LIPS, I work on finding better solutions for common mechanical design problems using deep generative modeling. My research interests are generative modeling, ML-accelerated design/simulation, and deep reinforcement learning, but I am always exploring new research in the AI space. Outside of the lab, I love teaching CS and enjoy designing/building full-stack applications.

Veronica Valera

Alumni and Friends

  • Jordan Ash
  • Elaine Angelino
  • Alex Beatson
  • Diana Cai
  • SueYeon Chung
  • Eyal Dechter
  • Finale Doshi-Velez
  • Bianca Dumitrascu
  • David Duvenaud
  • Michael Gelbart
  • Jonathan Huggins
  • Jose Miguel Hernandez Lobato
  • Matthew Johnson
  • Scott Linderman
  • Sulin Liu
  • Dougal Maclaurin
  • Andrew Miller
  • Shamim Nemati
  • Yaniv Ovadia
  • Jad Rahme
  • Yakir Reshef
  • Oren Rippel
  • Ardavan Saeedi
  • Ari Seff
  • Jasper Snoek
  • Xingyuan Sun
  • Daniel Suo
  • Jose Garrido Torres
  • Alex Wiltschko
  • Tianju Xue
  • Wenda Zhou