J. Roberto Tello Ayala

J. Roberto Tello Ayala

PhD Candidate in Applied Mathematics - Machine Learning

Data to Actionable Knowledge Lab

Harvard University

My name is (Jose) Roberto Tello Ayala (he/him/his), I am a third year (G3) PhD candidate advised by Professor Finale Doshi-Velez. I am part of the Data to Actionable Knowledge Lab at Harvard John A. Paulson School of Engineering and Applied Sciences as well as the FahedLad at the Cardiovascular Disease Initiative (CVDi) of the Broad Institute of Harvard and MIT and the Mass General Hospital (MGH). My research focuses on improving the interpretability of computer vision models, particularly in healthcare applications, with an emphasis on enhancing clinical decision-making and extracting relevant phenotypes from cardiac imaging data in the context of Cardiovascular Disease.

Education

 
 
 
 
 
Harvard University
PhD student
Harvard University
August 2022 – Present Cambridge MA, USA
 
 
 
 
 
Instituto Tecnológico Autónomo de México
B.S. in Applied Mathematics
Instituto Tecnológico Autónomo de México
August 2015 – December 2019 Mexico City, Mexico
Graduated with honors by acquiring a special mention thanks to my thesis titled “A study concerning the Chebyshev Center problem in finite-dimensional normed vector spaces” under the supervision of Dr. Cesar Garcia-Garcia.

Recent Publications

(2023). Signature Activation: A Sparse Signal View for Holistic Saliency. In ICML 3rd Workshop on Interpretable Machine Learning in Healthcare (IMLH).

PDF Cite Project Slides

(2021). Optimal Testing and Containment Strategies for Universities in Mexico amid COVID-19. EAAMO ‘21: Equity and Access in Algorithms, Mechanisms, and Optimization.

PDF Cite Code Slides

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Contact

  • jtelloayala [at] g [dot] harvard [dot] edu