Ricardo Baptista

von Kármán Instructor, California Institute of Technology


I am an instructor in Computing + Mathematical Sciences at Caltech hosted by Andrew Stuart and Houman Owhadi. My research is on probabilistic modeling and inference for problems in science and engineering. Most recently, I have been developing scalable generative models for solving inverse problems based on computational measure transport.

I completed my PhD in the Center for Computational Science and Engineering at MIT where I was fortunate to be advised by Youssef Marzouk. A copy of my PhD thesis can be found here. Before MIT, I received my BASc in Engineering Science from the University of Toronto.

Contact: rsb (at) caltech (dot) edu
Follow: Google Scholar arXiv GitHub LinkedIn


Nov 2023 Gave the USNCCM Large-Scale TTA early-career colloquium on dimension reduction methods for probabilistic modeling. Thank you Shelly and Patrick for the invitation!
Oct 2023 Our paper on learning monotone triangular transports was accepted for publication in Foundations of Computational Mathematics!
Oct 2023 Our two submissions to NeurIPS 2023: Debias Coarsely, Sample Conditionally for Statistical Downscaling (spotlight) and Structured Neural Networks (poster) were accepted! Many thanks to my co-authors for the great collaborations.

Selected publications

  1. SIAM Review
    Coupling techniques for nonlinear ensemble filtering
    Alessio Spantini, Ricardo Baptista, and Youssef Marzouk
    SIAM Review, 2022
  2. FoCM
    On the representation and learning of monotone triangular transport maps
    Ricardo Baptista, Youssef Marzouk, and Olivier Zahm
    Foundations of Computational Mathematics, 2023
  3. arXiv
    Conditional Sampling with Monotone GANs: from Generative Models to Likelihood-Free Inference
    Ricardo Baptista, Bamdad Hosseini, Nikola B Kovachki, and Youssef Marzouk
    arXiv:2006.06755, 2023