Nic Fishman

Causal Inference · Machine Learning · Multiscale Modeling

  1. Generative modeling on the space of empirical measures
    Boston Diffusion Day, Cambridge, MA, 2025
  2. Generative modeling on the space of empirical measures
    Harvard Statistics Seminar, Cambridge, MA, 2025
  3. False Promises and False Premises of Fair Machine Learning
    Columbia Algorithms and Society Seminar, New York, NY, 2025
    Outlining the history of the field of fair machine learning and arguing that ``theoretical fairness'' is a doomed project.
  4. Predicting perturbations at single-cell resolution
    Cell Circuits and Epigenomics Seminar, Cambridge, MA, 2025
    An overview of the problem of single-cell perturbation prediction, presentation of results from benchmarking existing methods, and our novel approach for in silico experimentation.
  5. Constrained Riemannian Diffusion Modeling
    Thesis Defense, Oxford, UK, 2023
  6. Should attention be all we need?
    Stanford Human Centered Artificial Intelligence, Stanford, CA, 2022
  7. Should attention be all we need?
    DeepMind Sociotechnical Systems, London, England, 2022