Luis Felipe Giraldo

Bio

He is an Associate Professor in the Department of Biomedical Engineering at Universidad de los Andes, Colombia. His research integrates engineering and artificial intelligence to advance human health and well-being, spanning biomedical data analysis, AI-based clinical decision support, and cooperative AI focused on collective well-being. He earned his Ph.D. in Electrical and Computer Engineering from The Ohio State University, USA, in 2016.

lf.giraldo404[at]uniandes[dot]edu[dot]co

Links:

CV - Minciencias, Linkedin, ORCID, Google Scholar, Researchgate

Teaching

My active courses are:

IBIO 2340 – Fundamentos del Machine Learning (Undergraduate level)
IBIO 4711 – Machine Learning para Ingeniería (Graduate level)
MAIA 4201 – Técnicas de Deep Learning (Graduate level, online version available on Coursera)
MAIA 4111 – Matemáticas para Machine Learning (Graduate level, online version available on Coursera)
MOOC on Coursera (freely available): Introducción al Deep Learning Contemporáneo

Anonymous comments and ratings by the students on these courses and the instructor can be seen at losestudiantes.co .

Research areas and publications

There are opportunities for students at undergraduate, master, and PhD levels to do relevant research. If you are interested in getting involved in any project, please, feel free to contact me at lf.giraldo404[at]uniandes[dot]edu[dot]co.

Our work is organized into three interconnected research areas, each described below. Click on each area to view its representative publications.

Artificial Intelligence for Collective Well-being: We develop cooperative artificial intelligence approaches aimed at promoting human well-being and collective resilience. This research explores how intelligent systems can support coordination, adaptation, and decision-making across individuals, communities, and healthcare-related ecosystems. By integrating AI approaches such as reinforcement learning, preference-based learning, and large language models, we aim to develop socio-technical tools that support resilience and collaboration in collective well-being..

Clic to view representative publications.

Fonseca, Y., Ríos, M. S., Quijano, N., & Giraldo, L. F. (2025). World Models Unlock Optimal Foraging Strategies in Reinforcement Learning Agents. IEEE Transactions on Artificial Intelligence. Manuscript under review.
Ríos, M.S., Manrique, R., Quijano, N., Giraldo, L.F. The Illusion of Rationality: Tacit Bias and Strategic Dominance in Frontier LLM Negotiation Games. IEEE Transactions on Artificial Intelligence. Manuscript under review.
Chacon-Chamorro, M., Pinzón, J. S., Manrique, R., Giraldo, L. F., & Quijano, N. Evaluating Cooperative Resilience in Multiagent Systems: A Comparison Between Humans and LLMs. IEEE Transactions on Artificial Intelligence. Manuscript under review.
Vargas-Panesso, V., Quijano, N., Giraldo, L. F., & Barreiro-Gomez, J. (2026). A strategic connections model for evolutionary games in strategically linked communities. IEEE Transactions on Cybernetics. Manuscript Accepted for publication.
Smith, C., ..., Chacón-Chamorro, M., Ríos, M., Manrique, R., Quijano, N., Giraldo, LF. Evaluating generalization capabilities of LLM-based agents in mixed-motive scenarios using concordia (2025, december). In The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track.
Mosquera, M., Pinzon, J. S., Fonseca, Y., Ríos, M., Quijano, N., Giraldo, L. F., & Manrique, R. (2025). Can LLM-augmented autonomous agents cooperate? An evaluation of their cooperative capabilities through melting pot. IEEE Transactions on Artificial Intelligence.
Chacon-Chamorro, M., Giraldo, L. F., Quijano, N., Vargas-Panesso, V., González, C., Pinzón, J. S., ... & Perdomo-Pérez, M. (2025). Cooperative resilience in artificial intelligence multiagent systems. IEEE Transactions on Artificial Intelligence.
Rios, M., Quijano, N., & Giraldo, L. F. (2023). Understanding the world to solve social dilemmas using multi-agent reinforcement learning. ICLR Workshop on Artificial Intelligence for Agent-Based Modelling.
Melendez, A., Caballero-Russi, D., Gutierrez Soto, M., & Giraldo, L. F. (2022). Computational models of community resilience. Natural Hazards, 111(2), 1121-1152.

Artificial Intelligence for Biomedical Data Analysis: We leverage artificial intelligence to explore complex biomedical data, ranging from physiological signals and biomechanics to statistical shape modeling, in order to identify meaningful patterns and biomarkers that advance the understanding of health and disease. In doing so, we also generate high-quality datasets that enable deeper analyses and support open, collaborative research. Ultimately, this line aims to produce new knowledge that inspires future healthcare innovations.

Clic to view representative publications.

Jiménez-Ocaña, A. A., Pantoja, A., Armañac, P., Ballón, R., Laguna, P., & Giraldo, L. F. Stress detection using heart rate variability and respiratory signals derived from a single-lead ECG. IEEE Transactions on Biomedical Engineering. Manuscript under review.
Perez-Cuatian, C. E., Casallas-Gutierrez, I., Guerrero-Chalela, C. E., Navarro-Rueda, J., Briceño, J. C., & Giraldo, L. F. (2025). Identifying Shape Biomarkers of Pulmonary Valve Dysfunction through Discriminant Analysis in Statistical Shape Modeling. Medical and Biological Engineering and Computing. Manuscript under review.
Landinez, D., Bayod, J., Giraldo, LF., Cifuentes-De La Portilla, Christian. (2025) Integration of Energy-Based Stability and Morphological Features for Predicting the Progression of Adolescent Idiopathic Scoliosis. Computer Methods in Applied Mechanics and Engineering. Manuscript under review.
Perez, C., Prada-Caicedo, A., Rodriguez, B., Navarro-Rueda, J., Cifuentes De-la-portilla, C., Guerrero-Chalela, C., Briceño, J., & Giraldo, L. F. (2025). PULSE: Dataset for studying deformation in 3D patient-specific pulmonary artery anatomies. Nature Scientific Data. Manuscript under review.
Bittar, A., Botia, C., Martínez, S., Bernal, D., Aparicio, N., Giraldo, L. F., Akle, V., & Bloch, N. I. (2025). Spatiotemporal patterns of gene expression associated with mating stimuli in the brain of female guppies. Genes, Brain and Behavior, 24(6), e70035.
Solórzano, B. D., Chavez, S., Giraldo, L. F., & De la Portilla, C. C. (2025). Machine learning-based gait cycle segmentation using instantaneous knee and hip-extension angles for biomechanical analysis. Neural Computing and Applications, 37(8), 6009-6019.
Cordoba-Silva, J., Maya, R., Valderrama, M., Giraldo, L. F., Betancourt-Zapata, W., Salgado-Vasco, A., ... & Ettenberger, M. (2024). Music therapy with adult burn patients in the intensive care unit: short-term analysis of electrophysiological signals during music-assisted relaxation. Nature Scientific reports, 14(1), 23592.
Jiménez-Ocaña, A. A., Pantoja, A., Bailón, R., & Giraldo, L. F. (2024, November). Real-Time Stress Detection Using Single-Lead ECG Signal Analysis. In The 3rd International Congress of Biomedical Engineering and Bioengineering (CIIBBI) (pp. 1-6). IEEE.
Felipe Flórez-Sierra, A., David Solórzano, B., Segura-Quijano, F., Cortés-Bello, Y. M., Cubillos, L., Giraldo, L. F., & Cifuentes-De la Portilla, C. (2024). LSC50: Colombian Sign Language video and inertial measurement dataset. Nature Scientific Data, 11(1), 1347.
Ríos, M. S., Molina-Rodriguez, M. A., Londoño, D., Guillén, C. A., Sierra, S., Zapata, F., & Giraldo, L. F. (2023). Cholec80-cvs: An open dataset with an evaluation of strasberg’s critical view of safety for AI. Nature Scientific Data, 10(1), 194.
Jimenez-Ocana, A. A., Pantoja, A., Valderrama, M. A., & Giraldo, L. F. (2023). A systematic review of technology-aided stress management systems: Automatic measurement, detection and control. IEEE Access, 11, 116109-116126.

Artificial Intelligence for Clinical Decision Support: We build AI systems that integrate diverse clinical data, including medical images, physiological signals, and electronic health records, to assist healthcare professionals in diagnosis, prognosis, and treatment planning. These tools provide reliable and interpretable insights that support data-driven decision-making and personalized patient care.

Clic to view representative publications.

Pérez-Cualtán, C. E., Guerrero-Chalela, C. E., Navarro-Rueda, J., Giraldo, L. F., & Briceño, J. C. (2025, October). Assessing valve design in repaired Tetralogy of Fallot patients. Abstract presented at the BMES Biomedical Engineering Society Annual Meeting 2025, Baltimore, MD, United States.
Plata, M., Azuero, G., Daza, F., Gutierrez, A., Garcia, V., Rojas-Rivillas, M., Gomez, S., Rodriguez, T., Cañar, S., Avila, P., Gonzalez, S., Florez, S., & Giraldo, L. (2025, September). Improving uroflowmetry interpretation: Effects of standardization sessions on interobserver agreement and AI model consistency. Abstract presented at the ICS-EUS Special Joint Annual Meeting of the International Continence Society and the Emirates Urological Society, Abu Dhabi, UAE.
Plata, M., Azuero, J., Daza, F., Rojas-Rivillas, M., Garcia, V., Gutierrez, A., Cañar, S., Rodriguez, T., Gomez, S., & Giraldo, L. (2025, September). AI-based platform for automated uroflowmetry curve morphology classification. Abstract presented at the ICS-EUS Special Joint Annual Meeting of the International Continence Society and the Emirates Urological Society, Abu Dhabi, UAE.

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