Diego Martinez Taboada

About Me

I am a second year PhD student in the Department of Statistics and Data Science at Carnegie Mellon University, where I am advised by Prof. Aaditya Ramdas.

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Education

• Carnegie Mellon University, PhD in Statistics and Data Science
  2022 -- present
• University of Oxford, MSc in Statistical Science
  2021 -- 2022
• University of Santiago de Compostela, BSc in Mathematics
  2017 -- 2021

Research

I am broadly interested in developing novel statistical theory that sheds light on important problems. In particular, I have recently been focusing on

• Kernel methods
• Causal inference
• Sequential statistics

Related topics such as general nonparametric statistics, bandits, reinforcement learning, NTK or distributional metrics (f-divergences, IPMs, Wasserstein distances) will catch my eye!

Preprints

1. Mean Estimation in Banach Spaces Under Infinite Variance and Martingale Dependence
   Justin Whitehouse, Ben Chugg, Diego Martinez-Taboada, Aaditya Ramdas
   Under review.
2. Empirical Bernstein in smooth Banach spaces
   Diego Martinez-Taboada, Aaditya Ramdas
   Under review.
3. Sharp empirical Bernstein bounds for the variance of bounded random variables
   Diego Martinez-Taboada, Aaditya Ramdas
   Under review.

Publications

1. Sequential Kernelized Stein Discrepancy
   Diego Martinez-Taboada, Aaditya Ramdas
   International Conference on Artificial Intelligence and Statistics (AISTATS), 2025.
2. Counterfactual Density Estimation using Kernel Stein Discrepancies
   Diego Martinez-Taboada, Edward H. Kennedy
   International Conference on Learning Representations (ICLR), 2024.
3. En Efficient Doubly-Robust Test for the Kernel Treatment Effect
   Diego Martinez-Taboada, Aaditya Ramdas, Edward H. Kennedy
   Neural Information Processing Systems (NeurIPS), 2023.

Contact Information

diegomar AT andrew DOT cmu FULLSTOP edu