Joan T. Matamalas

Researcher on complex systems

Research Associate at Harvard Medical School
Research Scientist at Brigham and Women's Hospital

I’ve always been fascinated by the intricate dynamics of complex systems, especially in the realm of health sciences. My research journey has led me to explore the spread of infectious diseases, the fascinating interplay of the immune system, and the delicate interactions between cellular components. With a background in computer science and a passion for artificial intelligence, I enjoy diving into the realms of network science, machine learning, and statistical physics to unravel these complex puzzles.

Teaching has also played a significant role in my life. I’ve had the pleasure of guiding students through a wide array of courses, from introductory programming to advanced data science and the foundational concepts of AI. Advising master’s theses has been a rewarding experience, allowing me to support students as they explore their own research interests and practical applications. I believe in the power of education to inspire and equip future innovators. That’s why I’m dedicated to creating innovative, open-source teaching materials that not only reflect real-world situations but also enrich my students' learning experiences.

Publications

Cross-species proteomics quantification pipeline distinguishes donor versus host extracellular matrix in explanted biomaterials. Cahalane, R. M., Meuris, B., Matamalas, J. T., Blaser, M. C., Billaud, M., Kasai, T., Hendrickx, A., Goeminne, L. J., Muehlschlegel, J., Rega, F., Aikawa, M., McNamara, L., Singh, S. A., Clift, C. L. & Aikawa, E. Biorxiv 2025–06 (2025).
Integrating pharmacogenomics and cheminformatics with diverse disease phenotypes for cell type-guided drug discovery. Halu, A., Chelvanambi, S., Decano, J. L., Matamalas, J. T., Whelan, M., Asano, T., Kalicharran, N., Singh, S. A., Loscalzo, J. & Aikawa, M. Genome medicine 17, 7 (2025).
Obesity and age are transmission risk factors for SARS-CoV-2 infection among exposed individuals. Matamalas, J. T., Chelvanambi, S., Decano, J. L., França, R. F., Halu, A., Santinelli-Pestana, D. V., Aikawa, E., Malhotra, R. & Aikawa, M. Pnas nexus 3, pgae294 (2024).
Cellular Heterogeneity of Activated Primary Human Macrophages and Associated Drug–Gene Networks: From Biology to Precision Therapeutics. Decano, J. L., Maiorino, E., Matamalas, J. T., Chelvanambi, S., Tiemeijer, B. M., Yanagihara, Y., Mukai, S., Jha, P. K., Pestana, D. V., D’Souza, E., Whelan, M., Ge, R., Asano, T., Sharma, A., Libby, P., Singh, S. A., Aikawa, E. & Aikawa, M. Circulation 148, 1459–1478 (2023).
Editorial: Artificial intelligence applied to coronary artery diseases: from pathophysiology to precision medicine. Vinci, R., d’Aiello, A., Costantino, S., Capocchiano, N. D., Matamalas, J. T. & Pedicino, D. Frontiers in cardiovascular medicine 10, (2023).
Joint Analysis of the Epidemic Evolution and Human Mobility During the First Wave of COVID-19 in Spain: Retrospective Study. Steinegger, B., Granell, C., Rapisardi, G., Gómez, S., Matamalas, J., Soriano-Paños, D., Gómez-Gardeñes, J. & Arenas, A. Jmir public health and surveillance 9, e40514 (2023).
A disease-driver population within interstitial cells of human calcific aortic valves identified via single-cell and proteomic profiling. Decano, J. L. et al. Cell reports 39, (2022).
Highly Selective PPARα Agonist Pemafibrate Inhibits Stent Inflammation and Restenosis Assessed by Multimodality Molecular‐Microstructural Imaging. Iwata, H., Osborn, E. A., Ughi, G. J., Murakami, K., Goettsch, C., Hutcheson, J. D., Mauskapf, A., Mattson, P. C., Libby, P., Singh, S. A., Matamalas, J., Aikawa, E., Tearney, G. J., Aikawa, M. & Jaffer, F. A. Journal of the american heart association 10, e020834 (2021).
Systems Approach to Discovery of Therapeutic Targets for Vein Graft Disease: PPARα Pivotally Regulates Metabolism, Activation, and Heterogeneity of Macrophages and Lesion Development. Decano, J. L., Singh, S. A., Gasparotto Bueno, C., Ho Lee, L., Halu, A., Chelvanambi, S., Matamalas, J. T., Zhang, H., Mlynarchik, A. K., Qiao, J., Sharma, A., Mukai, S., Wang, J., Anderson, D. G., Ozaki, C. K., Libby, P., Aikawa, E. & Aikawa, M. Circulation 143, 2454–2470 (2021).
Network clique cover approximation to analyze complex contagions through group interactions. Burgio, G., Arenas, A., Gómez, S. & Matamalas, J. T. Communications physics 4, 111 (2021).
Virus spread versus contact tracing: Two competing contagion processes. Reyna-Lara, A., Soriano-Paños, D., Gómez, S., Granell, C., Matamalas, J. T., Steinegger, B., Arenas, A. & Gómez-Gardeñes, J. Physical review research 3, 013163 (2021).
Modeling the Spatiotemporal Epidemic Spreading of COVID-19 and the Impact of Mobility and Social Distancing Interventions. Arenas, A., Cota, W., Gómez-Gardeñes, J., Gómez, S., Granell, C., Matamalas, J. T., Soriano-Paños, D. & Steinegger, B. Physical review x 10, 041055 (2020).
Evolution of Cooperation in the Presence of Higher-Order Interactions: From Networks to Hypergraphs. Burgio, G., Matamalas, J. T., Gómez, S. & Arenas, A. Entropy 22, 744 (2020).
Experts’ request to the Spanish Government: move Spain towards complete lockdown. Mitjà, O., Arenas, À., Rodó, X., Tobias, A., Brew, J. & Benlloch, J. M. The lancet 395, 1193–1194 (2020).
Abrupt phase transition of epidemic spreading in simplicial complexes. Matamalas, J. T., Gómez, S. & Arenas, A. Physical review research 2, 012049 (2020).
Effective approach to epidemic containment using link equations in complex networks. Matamalas, J. T., Arenas, A. & Gómez, S. Science advances 4, eaau4212 (2018).
Revealing Cause-Effect Relations in Comorbidities Analysis Using Process Mining and Tensor Network Decomposition. Matamalas, J. T., Arenas, A., Martínez-Ballesté, A., Solanas, A., Alonso-Villaverde, C. & Gómez, S. in 2018 9Th International Conference on Information, Intelligence, Systems and Applications (IISA) 1–5 (2018).
Assessing reliable human mobility patterns from higher order memory in mobile communications. Matamalas, J. T., De Domenico, M. & Arenas, A. Journal of the royal society interface 13, 20160203 (2016).
Strategical incoherence regulates cooperation in social dilemmas on multiplex networks. Matamalas, J. T., Poncela-Casasnovas, J., Gómez, S. & Arenas, A. Scientific reports 5, 9519 (2015).

DSPA INSIGHTS, 2020
Computational epidemics: from theory to policy
Online
Google Tech Week, 2020
Computational epidemics: A gentle introduction to epidemic modeling
Online
International Conference on Information, Intelligence, 2018
Revealing cause-effect relations in comorbidites analysis using process mining and tensor network decomposition
Zakynthos, Greece
Gamenet, NetSci Satellite, 2018
Coherent and incoherent strategists: Evolutionary dynamics on multiplex networks
Paris, France
Complenet, 2018
Epidemic extinction driven by link epidemic importance
Boston, MA, USA
LANet, Latin American Conference on Complex Networks, 2017
Coherent and incoherent strategists: Evolutionary dynamics on multiplex networks
Puebla, Mexico
CCS, 2017
Epidemic Conductance in Complex Networks
Cancun, Mexico
Conferen on Complex Networks and their Applications, 2017
Epidemic Conductance in Complex Networks
Lyon, France
Contagion on Networks, NetSci Satellite, 2017
Epidemic conductance in complex networks
Indianapolis, IN, USA
Complenet, 2017
Adaptive Memory Model: Assessing reliable human mobility patterns from higher-order memory in mobile communications
Dubrovnik, Croatia
CCS, 2016
Assessing reliable human mobility patterns from higher-order memory in mobile communications
Amsterdam, The Netherlands
CCS, 2016
Coherent and incoherent strategists: Evolutionary dynamics on multiplex networks
Amsterdam, The Netherlands
NetSci, 2015
Interplay Between Human Mobility and Telecomunications
Zaragoza, Spain

Joan T. Matamalas

Researcher on complex systems

Research Associate at Harvard Medical School
Research Scientist at Brigham and Women's Hospital

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