Dr. Hugo Jair Escalante

Professor · Department of Computer Science · University of Texas at El Paso

I joined the Department of Computer Science at UTEP as Distinguished Regents Professor. I am affiliated to the Institute for Applied AI Innovation. Previous appointments include: INAOE, Mexico, Professor (since 2012); ChaLearn, USA, Director, (since 2011); CINVESTAV, Mexico, visiting (2019-2020); FIME UANL, Mexico, Associate professor (2010-2011)

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News and updates

For a complete list of updates see my News and updates page..

September 28
Paper

MIRROR@IberLEF2026: results presented at IberLEF and overview paper published!

Luis J. Arellano, Carlos Olachea, John D. Piette, Hugo Jair Escalante, Luis Villaseñor-Pineda, Manuel Montes-y-Gómez, Delia Irazú Hernández-Farías. Overview of MIRROR at IberLEF 2026: Motivational Interviewing Response Rating via synthetic cOnversational tuRns. Procesamiento del Lenguaje Natural, Revista Vol. 77:605--617 (2026), September,2026

August 20
Paper

Two papers accepted for oral presentation at CIARP 2026

Itzel Tlelo-Coyotecatl and Hugo Jair Escalante. MexHat: A Dataset for Hate Speech Detection in Mexican Spanish Videos. CIARP 2026: 29th Iberoamerican Congress on Pattern Recognition, 2026

Rey Sánchez-López, Eduardo Morales, Hugo Jair Escalante. Task-Oriented Rank Adaptation for Continual Learning in Text Classification. CIARP 2026: 29th Iberoamerican Congress on Pattern Recognition, 2026

May 14
Paper

Paper accepted at DMLR

Hugo Jair Escalante, Aleksandra Kruchinina. Academic Competitions. Journal of Data-centric Machine Learning Research, 2026

April 20
Paper

Paper accepted at the LatinXinAI@CVPR2026 workshop

Estela Monserrat Arriaga Santana, Julian Rosas Scull, Hugo Jair Escalante, Ibeth P. Alarcón, Bibiana Montoya, Aylin Sosa Mejía. Towards benchmarking Western Bluebird detection in the wild. CVPR-LatinXinAI workshop, Oral presentation, non-archival, 2026

March 30
Paper

Paper accepted at MCPR2026: Mexican Conference on Pattern Recognition

Fabiola Muñoz Vera, Juan Manuel Pérez Ortega, Eduardo F. Morales, Hugo Jair Escalante. Ensembles of manifold learners for supervised and unsupervised learning. MCPR, 2026

Research Interests

Language and Vision

Effective integration of visual, textual and speech information.

Multimodal Machine Learning

Learning to jointly represent, align and reason over information from heterogeneous sources.

AutoML

Automating the design of ML pipelines, reducing human intervention as much as possible.

Challenge organization

With emphasis on evaluation protocols and platforms, as well as supporting the organization of competitions in ML, CV, and NLP.

Recent & Selected Publications

For a complete list, see my Google Scholar profile.

For a complete list, see my Google Scholar profile.

Teaching

Curriculum Vitae

Download my full CV for a complete record of publications, grants, service, and academic history.

Download CV (PDF)