cv

PhD in Computer Science

Institute for Computer Science, Artificial Intelligence and Technology (INSAIT), Sofia, Bulgaria & TU Darmstadt, Germany

• Advisor: Prof. Iryna Gurevych
• Jointly enrolled at INSAIT and TU Darmstadt (UKP Lab).

MSc in Computer Science and Engineering

Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico

• GPA: 9.80/10.00.
• Thesis: Paraphrase identification using Sentence-CROBI, a novel deep neural network architecture based on cross-encoders and bi-encoders.
• Advisor: Dr Gemma Bel-Enguix

Diploma in Mobile App Development for iOS

Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico

• GPA: 9.00/10.00

BEng in Computer Engineering

Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico

• GPA: 8.54/10.00.

Bachelor's Thesis Supervisor

TU Darmstadt, Department of Computer Science

• Supervised Marius Hoch's bachelor thesis, "Enhancing MLLM Chart Question Answering."
• Submitted July 17, 2026.

ARR Reviewer

ACL Rolling Review (ARR)

• Reviewed 4 papers.
• One review selected as a Great Review.

ARR Reviewer

ACL Rolling Review (ARR)

• Reviewed 4 papers.

ARR Reviewer

ACL Rolling Review (ARR)

• Reviewed 4 papers.

Graduate Teaching Assistant, Text Mining

Posgrado en Ciencia e Ingeniería de la Computación, UNAM

Teaching, Natural Language Processing

Colegio Científico de Datos (COCID)

Reviewer

21st Mexican International Conference on Artificial Intelligence (MICAI)

Teaching, Introduction to Machine Learning

Instituto de Ingeniería, UNAM

Research Assistant

Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI): Natural Language Processing Department

• Worked on parameter-efficient fine-tuning techniques for Large Language Models (LLMs).
• Contributed to CVQA, a multicultural, multilingual question-answering benchmark, by collecting, labelling, and validating image-question pairs in Mexican Spanish and English.
• Mentor at the MBZUAI Undergraduate Research Internship Program (UGRIP).

Grupo de Ingeniería Lingüística

UNAM research group focusing on computational linguistics and natural language processing

• Shared task organiser.
  • Participated in organising the PAR-MEX 2022 shared task: Paraphrase detection in Mexican Spanish at IberLEF 2022.
  • Designed baseline experiments using a Spanish BERT-based model and Keras and Transformers libraries.
  • Coordinated the codalab competition page and GitHub repository for the shared task.
  • Analysed the results using the F1-score as a performance metric and the Maximum Possible Accuracy and the Coincident Failure Diversity as complementariness metrics.
• Job offers classification.
  • Developed system performs multi-class classification of job offers using a recurrent neural network.
  • Financed by the Mexican government, its purpose is to reduce information asymmetries between job seekers and employers.
  • Model building using Keras library. It consists of a Long-short term memory layer followed by a multilayer perceptron.
  • Used SMOTE, Geometric-SMOTE and ADASYN algorithms to solve the high-imbalance-class problem.
• Course instructor.
  • Semester course to explain the basics of machine learning with a theoretical-practical approach.
  • An eight-student group took it with different academic backgrounds from UNAM and the private sector.
  • Prepared lessons using the book Artificial Intelligence with an introduction to machine learning by Richard E. Neapolitan and Xia Jiang; Kaggle datasets, the sci-kit learn library and python scripts.
• Aggressiveness detection on Twitter.
  • App that classifies Mexican Spanish tweets in aggressive or non-aggressive classes using machine learning and python.
  • Uses multiple types of n-grams such as character n-grams, word n-grams, and aggressive words n-grams as features.
  • Implements a support vector machine as a classifier with SciKit-learn and microTC framework for parameter optimization.
  • Achieved an F1-score of 0.4549, 5th place of 26 competitors at MEX-A3T 2019 aggressiveness identification task.

José Negrete Award — Best master's thesis in an AI-related field

Mexican Society for Artificial Intelligence (SMIA)