These are the slides behind my major presentations and posters. They are all released with a CC-BY license. The source code for this website (built with Jekyll) is available in this repo.

  1. 2025 On meta prompt optimization and coding agents
  2. 2025 On transport, flows, and physics
  3. 2025 Demystifying language models
  4. 2025 On prompt and text improvement with DSPy & TextGrad
  5. 2025 AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs
  6. 2025 On amortized optimization for RL, Bayesian optimization, and biology
  7. 2024 Transport and flows between distributions over distributions
  8. 2024 Lecture on dimensionality reduction with MDS and TSNE
  9. 2024 Lecture on LLMs
  10. 2024 On LLM prompt optimization and amortization
  11. 2024 Differentiable optimization and robotics
  12. 2024 Amortized optimization for OT and LLMs
  13. 2024 Amortized optimization and AI
  14. 2024 Lagrangian OT Poster
  15. 2024 End-to-end learning geometries for graphs, dynamical systems, and regression
  16. 2023 On amortizing convex conjugates for optimal transport
  17. 2023 TaskMet Poster
  18. 2023 Meta Optimal Transport
  19. 2023 Learning with differentiable and amortized optimization
  20. 2023 On optimal control and machine learning
  21. 2023 Continuous optimal transport
  22. 2023 Amortized optimization
  23. 2023 Amortized optimization for optimal transport
  24. 2022 Differentiable optimization
  25. 2022 Differentiable control
  26. 2022 Amortized optimization
  27. 2022 Amortized optimization for computing optimal transport maps
  28. 2021 On the model-based stochastic value gradient for continuous RL
  29. 2021 Riemannian Convex Potential Maps
  30. 2020 The differentiable cross-entropy method
  31. 2019 Differentiable optimization-based modeling for machine learning (PhD Thesis)
  32. 2018 PyTorch libraries for linear algebra, optimization, and control
  33. 2018 OptNet, end-to-end task-based learning, and control (ISMP)
  34. 2018 Differentiable MPC
  35. 2018 Differentiable MPC Poster
  36. 2017 OptNet: Differentiable Optimization as a Layer in Neural Networks
  37. 2017 Input Convex Neural Networks