Caio Lins Peixoto

Master's student in Applied Mathematics at FGV EMAp.
Rio de Janeiro, Brazil.

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Hi! I am a second year master’s student in Applied Mathematics at FGV’s School of Applied Mathematics. I am fortunate to be advised by Prof. Yuri Saporito.

My research interestes lie broadly in areas of Probability and Statistics with a functional flavor as well as compelling applications. These include Stochastic Control, Nonparametric Statistics and Stochastic Optimization over high/infinite dimensional spaces, motivated by problems in Finance, Operations Research and Machine Learning.

I am currently funded by the PICME/CAPES scholarship, awarded anually to fifteen incoming master’s students in Mathematics throughout Brazil. Previously, I completed my bachelor’s degree in Applied Mathematics at FGV EMAp, sponsored by CDMC as a participant of their talent scouting program.

My non-academic interests include guitar playing and photography.

news

Sep 15, 2025 The 44th Nacional Congress of Applied and Computational Mathematics is starting today, at my institution FGV EMAp. Feel free to reach out to me during the poster sessions, when I will present the poster Functional Gradient Descent through Directional Derivatives. This is joint work with Profs. Yuri Saporito and Bernardo da Costa, and postdoc Daniel Csillag.
Dec 10, 2024 Today is the start of NeurIPS 2024. I’ll be presenting my paper Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients, which is joint work with Profs. Yuri Saporito and Yuri Fonseca. Pass by so we can have a chat!
Sep 25, 2024 Our paper has been accepted at NeurIPS 2024! In this work, we develop a novel algorithm for nonparametric instrumental variable regression based on functional gradient descent.

selected publications

  1. open review link
    Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients
    Yuri Fonseca, Caio Peixoto, and Yuri Saporito
    In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024
    Code
  2. arXiv link
    Random Gradient-Free Optimization in Infinite Dimensional Spaces
    Caio Lins Peixoto, Daniel Csillag, Bernardo F. P. Costa, and 1 more author
    2025