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 Marie Skłodowska-Curie global fellowship, I am currently working at the Center for Computational Oncology at the Oden Institute in The University of Texas at Austin, but I am also a postdoctoral fellow at Computational Mechanics & Advanced Materials Group at the University of Pavia in Italy.

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


Simulating the spread of COVID-19 via a spatially-resolved susceptible–exposed–infected–recovered–deceased (SEIRD) model with heterogeneous diffusion

Alex Viguerie, Guillermo Lorenzo, Ferdinando Auricchio, Davide Baroli, Thomas J.R. Hughes, Alessia Patton, Alessandro Reali, Thomas E. Yankeelov, Alessandro Veneziani

Applied Mathematics Letters, 2021, p. 106617

Math, magnets, and medicine: enabling personalized oncology

David A. Hormuth, Angela M. Jarrett, Guillermo Lorenzo, Ernesto A. B. F. Lima, Chengyue Wu, Caroline Chung, Debra Patt, Thomas E. Yankeelov

Expert Review of Precision Medicine and Drug Development, vol. 6(2), 2021, pp. 79-81

Quantitative in vivo imaging to enable tumor forecasting and treatment optimization

Guillermo Lorenzo, David A. Hormuth, Angela M. Jarrett, Ernesto A. B. F. Lima, Shashank Subramanian, George Biros, J. Tinsley Oden, Thomas J. R. Hughes, Thomas E. Yankeelov

arXiv: Tissues and Organs, 2021

Optimal control of cytotoxic and antiangiogenic therapies on prostate cancer growth

Pierluigi Colli, Hector Gomez, Guillermo Lorenzo, Gabriela Marinoschi, Alessandro Reali, Elisabetta Rocca

Mathematical Models and Methods in Applied Sciences, vol. 31(7), 2021, pp. 1419-1468

Biologically-Based Mathematical Modeling of Tumor Vasculature and Angiogenesis via Time-Resolved Imaging Data

David A. Hormuth, Caleb M. Phillips, Chengyue Wu, Ernesto A. B. F. Lima, Guillermo Lorenzo, Prashant K. Jha, Angela M. Jarrett, J. Tinsley Oden, Thomas E. Yankeelov

Cancers, vol. 13(12), 2021 May 16

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

Marie Skłodowska-Curie global fellow

[email protected]

Oden Institute

The University of Texas at Austin

201 E. 24th Street, POB 2.128
1 University Station (C0200)
Austin, Texas 78712-1229