Hi ! Welcome to my personal webpage

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  "la Caixa" Foundation Postdoctoral Junior Leader Fellowship, I am currently working at the Medical Physics and Biomathematics Group of the Health Research Institute of Santiago de Compostela in Spain, but I am also a postdoctoral 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.


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

Integrating multiscale data and mechanistic models to predict breast cancer response to neoadjuvant therapies

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


A Pilot Study on Patient-specific Computational Forecasting of Prostate Cancer Growth during Active Surveillance Using an Imaging-informed Biomechanistic Model

Guillermo Lorenzo, Jon S Heiselman, Michael A Liss, Michael I Miga, Hector Gomez, Thomas E Yankeelov, Alessandro Reali, Thomas JR Hughes

Cancer Research Communications, vol. 4, 2024, pp. 617--633

A mathematical model for predicting the spatiotemporal response of breast cancer cells treated with doxorubicin

Hugo JM Miniere, Ernesto ABF Lima, Guillermo Lorenzo, David A Hormuth, Sophia Ty, Amy Brock, Thomas E Yankeelov

Cancer Biology & Therapy, vol. 25, 2024, p. 2321769

Designing clinical trials for patients who are not average

Thomas E Yankeelov, David A Hormuth, Ernesto ABF Lima, Guillermo Lorenzo, Chengyue Wu, Lois C Okereke, Gaiane M Rauch, Aradhana M Venkatesan, Caroline Chung

Iscience, vol. 27, 2024, p. 108589

Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas

Anirban Chaudhuri, Graham Pash, David A Hormuth, Guillermo Lorenzo, Michael Kapteyn, Chengyue Wu, Ernesto ABF Lima, Thomas E Yankeelov, Karen Willcox

Frontiers in Artificial Intelligence, vol. 6, 2023, p. 1222612

Dynamic parameterization of a modified SEIRD model to analyze and forecast the dynamics of COVID-19 outbreaks in the United States

Orhun O Davarci, Emily Y Yang, Alexander Viguerie, Thomas E Yankeelov, Guillermo Lorenzo

Engineering with Computers, 2023, pp. 1--25

View all


Academic biography

A brief summary of my education and research experience


Main honors, awards, and competitive grants that I have received during my career


List of my experience in teaching university courses and supervising students


Guillermo Lorenzo, PhD

"la Caixa" Foundation Postdoctoral Junior Leader Fellow


Medical Physics and Biomathematics Group

Health Research Institute of Santiago de Compostela

Hospital Clínico de Santiago de Compostela
Travesía da Choupana S/N
15706 Santiago de Compostela


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