Welcome!

I am currently a 5th-year Ph.D. candidate in the Department of Mathematics at the University of Notre Dame. My advisors are Dr. Daren Wang and Dr. Lizhen Lin. 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.

News

Beginning July 1, 2024, I will be an Assistant Professor (Tenure-track) in the Department of Statistics and Data Science at Washington University in St. Louis.

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. To appear in 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, O.H. Madrid-Padilla, D. Wang. Temporal-spatial model via Trend Filtering. PDF Under Review.

Carlos-Misael Madrid-Padilla and O.H. Madrid-Padilla. Distributional regression via Neural Networks. In Progress. 2023+.

Carlos-Misael Madrid-Padilla, Oscar Hernan Madrid Padilla and Sabyasachi Chatterjee. Distributional regression: Trend Filtering and beyond. In Progress. 2023+.

Ke Xu, Carlos-Misael Madrid-Padilla, Daren Wang and Oscar Hernan Madrid Padilla. Dense neural networks for temporal spatial model on Manifolds. In Progress. 2023+.

Carlos-Misael Madrid-Padilla, Shitao Fan and Lizhen Lin. Robust and Scalable Variational Bayes. In Progress. 2023+.