Welcome!

I am a Tenure-track Assistant Professor in the Department of Statistics and Data Science at Washington University in St. Louis. I earned a Ph.D. in Mathematics at the Department of Mathematics at the University of Notre Dame under the supervision of Dr. Daren Wang. During the first two years of my Ph.D. I received a Master’s degree in Mathematics under the supervision of Dr. Alex Himonas.

My undergraduate degree was a B.S. in Mathematics completed at CIMAT (in Mexico) in May 2019, advised by Dr. Víctor M. Pérez Abreu C. and Dr. Mario Diaz.

A copy of my CV can be found here.

I was born and raised in Honduras.

Research

My research interests include:

• High-dimensional statistics
• Nonparametric statistics
• Change point detection
• Causal inference
• Bayes methodology

Published/Accepted papers

Carlos-Misael Madrid-Padilla, H. Xu, D. Wang, O.H. Madrid-Padilla, Y. Yu. Change point detection and inference in multivariable nonparametric models under mixing conditions. PDF. NeurIPS 2023.

Carlos-Misael Madrid-Padilla, Daren Wang, Zifeng Zhao, Yi Yu. Change-point detection for sparse and dense functional data in general dimensions. PDF. NeurlPs 2022

Alexandrou Himonas, Carlos-Misael Madrid-Padilla, Fangchi Yan (alphabetical order). The Neumann and Robin problems for the Korteweg-de Vries equation on the half-line. PDF
Journal of Mathematical Physics, 62, 111503. 2021. (selected as Editors’ Pick)

Preprints

Carlos-Misael Madrid-Padilla, Oscar Hernan Madrid-Padilla, Daren Wang. Temporal-spatial model via Trend Filtering. PDF Under Review. 2024.

Zhi Zhang, Carlos-Misael Madrid-Padilla, Oscar Hernan Madrid-Padilla, Xiaokai Luo, Daren Wang. Dense ReLU Neural Networks for Temporal-spatial Mode. PDF Under Review. 2025.

H. Xu, Carlos-Misael Madrid-Padilla, O.H. Madrid-Padilla, D. Wang. Multivariate Poisson intensity estimation via low-rank tensor decomposition. PDF. 2024.

Carlos-Misael Madrid-Padilla, Oscar Hernan Madrid Padilla, Yik Lun Kei, Zhi Zhang, Yanzhen Chen. Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks. PDF Under Review. 2025.

Carlos-Misael Madrid-Padilla, Shitao Fan and Lizhen Lin. Robust and Scalable Variational Bayes. PDF Under review. 2025.

Carlos-Misael Madrid-Padilla, Oscar Hernan Madrid Padilla, and Sabyasachi Chatterjee. Risk Bounds For Distributional Regression. PDF Under review. 2025.