I am a researcher in computational oncology.
The focus of my investigations is to build personalized mathematical models of the biophysical mechanisms underlying cancer growth and therapeutic response, with which I can make patient-specific forecasts of tumor prognosis using computer simulations. I believe that this predictive approach can dramatically contribute to advance clinical practice in oncology by delivering personalized solutions aiming at optimizing clinical outcomes for each patient.
I also work in modeling the mechanisms of development, treatment, and spread of other pathologies. Additionally, I am interested in constructing robust computational methods to efficiently and accurately solve my models in clinically-relevant times.
Thanks to a Ramón y Cajal Fellowship from the Spanish Ministry of Science, Innovation, and Universities, I am currently working at the Group of Numerical Methods in Engineering in the Department of Mathematics of the University of A Coruña in Spain. Additionally, I am a research affiliate at the Center for Computational Oncology at the Oden Institute in The University of Texas at Austin.
Check out my research below and feel free to contact me if you are interested in discussing my work or any of the topics in this webpage. I am always open to new collaborations, delivering academic and popular science talks, or having a drink to talk science and else.
The focus of my investigations is to build personalized mathematical models of the biophysical mechanisms underlying cancer growth and therapeutic response, with which I can make patient-specific forecasts of tumor prognosis using computer simulations. I believe that this predictive approach can dramatically contribute to advance clinical practice in oncology by delivering personalized solutions aiming at optimizing clinical outcomes for each patient.
I also work in modeling the mechanisms of development, treatment, and spread of other pathologies. Additionally, I am interested in constructing robust computational methods to efficiently and accurately solve my models in clinically-relevant times.
Thanks to a Ramón y Cajal Fellowship from the Spanish Ministry of Science, Innovation, and Universities, I am currently working at the Group of Numerical Methods in Engineering in the Department of Mathematics of the University of A Coruña in Spain. Additionally, I am a research affiliate at the Center for Computational Oncology at the Oden Institute in The University of Texas at Austin.
Check out my research below and feel free to contact me if you are interested in discussing my work or any of the topics in this webpage. I am always open to new collaborations, delivering academic and popular science talks, or having a drink to talk science and else.
Research
Patient-specific, imaging-based forecasting of prostate cancer growth
This research aims at integrating standard clinical and imaging data from individual patients into mathematical models to enable the prediction of tumor growth using computer simulations
Personalized prediction of PSA dynamics after external radiotherapy of prostate cancer
Exploring the biophysical mechanisms underlying PSA dynamics after external radiotherapy to define new biomarkers for the early identification of relapse
Optimal control of therapeutic regimens for advanced prostate cancer
This work aims at finding optimal combinations of cytotoxic and antiangiogenic therapies to treat advanced prostatic tumors by combining mathematical analysis and computer simulations
Personalized prediction of breast cancer response to neoadjuvant therapies by using biophysical models parameterized with patient-specific imaging data and constrained by comprehensive pharmacodynamic experimental data
Data-driven mechanistic models to forecast COVID-19 outbreaks
Constructing mathematical models to understand and predict the dynamics of COVID-19 infectious spread based on longitudinal epidemiological data series
Publications
An MRI-informed poromechanical model for organ-scale prediction of glioma growth
Meryem Abbad Andaloussi, Stéphane Urcun, David A. Hormuth, Guillermo Lorenzo, Giuseppe Sciumè, Chengyue Wu, Thomas E. Yankeelov, Stéphane P. A. Bordas
Computer Methods in Applied Mechanics and Engineering, vol. 462, 2026, p. 119305
Iterative algorithms for the reconstruction of early stages of prostate cancer growth
Elena Beretta, Cecilia Cavaterra, Matteo Fornoni, Guillermo Lorenzo, Elisabetta Rocca
Journal of Nonlinear Science, vol. 36, 2026, p. 5
Integrating imaging and mathematical modeling to predict and optimize patient outcomes in oncology
Reshmi J. S. Patel, Ayesha Das, Aliya Anil, Gauri Patel, Ryan T. Woodall, Chase Christenson, Tarini Thiagarajan, Ernesto A. B. F. Lima, Guillermo Lorenzo, David A. Hormuth, Russell C. Rockne, Vikram Adhikarla, Chengyue Wu, Thomas E. Yankeelov
npj Systems Biology and Applications, 2026
The future of mathematical oncology in the age of AI
Russell C. Rockne, Morten Andersen, Alexander R. A. Anderson, David Basanta, Angela Bentivegna, Sebastien Benzekry, Sergio Branciamore, Sarah C. Brüningk, Martina Conte, Farnoush Farahpour, Aleksandra Karolak, Alvaro Köhn-Luque, Guillermo Lorenzo, Babgen Manookian, Andrei S. Rodin, Lara Schmalenstroer, Juan Soler, Cristian Tomasetti, Konstancja Urbaniak
npj Systems Biology and Applications, vol. 12, 2026, p. 22
Casey E. Stowers, Chengyue Wu, Guillermo Lorenzo, David A. Hormuth, Clinton Yam, Jingfei Ma, Gaiane M. Rauch, Thomas E. Yankeelov
Annals of Biomedical Engineering, 2026
View all
Contact
Guillermo Lorenzo, PhD
Ramón y Cajal Research Fellow
Group of Numerical Methods in Engineering, Department of Mathematics
Grupo de Métodos Numéricos en Enxeñaría
ETSE de Enxeñaría de Camiños, Canais e Portos
Campus de Elviña s/n
15008 A Coruña
Spain