Page 30 - Hormel Report 2023

David Guinovart-Sanjuan, PhD
“We are passionate about using math and computing to solve biomedical problems. Our lab believes these tools are essential for
progress in this field.”
David Guinovart-Sanjuan
30 | THE HORMEL INSTITUTE // UNIVERSITY OF MINNESOTA Mathematical, Computational and
Statistical Modeling
ASSISTANT PROFESSOR
Our laboratory is dedicated to developing and applying mathematical, statistical, and computational models that can
address various problems in biomedicine, epide- miology, and engineering. We employ multiple methods, such as data science, deterministic models, machine learning, and biostatistics models, to model, predict, understand, and
solve these problems. We also create software tools and virtual laboratories that allow the visualization and testing of hypotheses through mathematical models that are accessible and easy to use for non-experts in mathematics and computing techniques. In addition, our laboratory is committed to fostering a culture of interdis- ciplinary collaboration among various experts
in biological science, engineering, mathematics, and computer science. We work closely with PIs from The Hormel Institute, the University of Minnesota, and other scientific and educational institutions to address complex biological and engineering problems. Our laboratory aims
to advance several branches of science by developing and applying novel models, software, and techniques that can handle large-scale and high-dimensional data.
Developing and Applying a Novel Mathematical and Computational Framework for Modeling and Analyzing the Dynamics and Control of Infectious Diseases in Heterogeneous Populations.
This work aims to create more advanced
and realistic mathematical models to capture infectious diseases’ complexity, diversity, and transmission dynamics. The project will contribute to the understanding and forecasting of epidemics such as COVID-19, HIV, Dengue fever, and information diffusion.
Developing a Web-based Platform that Simplifies and Streamlines the Use of SIR Models for Any Scientific Domain.
With our project, you can easily upload your data, select the most suitable SIR model, customize the parameters, and run the model in minutes. You can then analyze the results in an interactive dashboard, where you can see how well the model fits your data, how the model predicts the future behavior of your system, and how sensitive the model is to different parameter values.