David is an accomplished Assistant Professor at The Hormel Institute, leveraging his extensive background in mathematics and computer science to pioneer advancements in bioscience research. Originating from Cuba, David attained his Bachelor's in Mathematics from the University of Havana before pursuing his passion further at the University of Central Florida, where he earned his Ph.D. in Applied Mathematics. David's academic journey has been marked by a profound dedication to mathematics and its intersection with various scientific disciplines. His research is centered on the intricate mathematical modeling of critical areas within bioscience, notably focusing on epidemiology, cell proliferation, and material science. Having shared his expertise as a mathematics professor at esteemed institutions like the University of Havana, the University of Central Florida (UCF), and the University of Delaware, David's true zeal lies in groundbreaking research. The unique opportunity at the Hormel Institute has allowed David to synergize his mathematical prowess with cutting-edge resources, including state-of-the-art datasets and insights into cancer research. His role not only involves spearheading personal projects but also extends to supporting fellow faculty members, thereby contributing significantly to the institute's overarching mission. Beyond his academic pursuits, David finds solace and rejuvenation by the seaside, drawing inspiration from his Cuban roots and cherishing moments spent by the ocean. An avid traveler, he and his family have explored numerous states across the US and ventured into Europe, driven by the desire to share the richness of diverse cultures with his child. Witnessing different ways of life and embracing cultural diversity is a priority, as it fosters a deep appreciation for global unity and understanding. Positions, Scientific Appointments, and Honors 2023 - Assistant Professor, Hormel Institute, University of Minnesota, MN, USA. 2022 - 2023 Assistant Professor, Department of Mathematics, University of Delaware, DE, USA. 2021 - 2022 Postdoctoral Fellow, Department of Mathematics, University of Central Florida, FL, USA 2016 - 2021 Ph.D. Student, Department of Mathematics, University of Central Florida, FL, USA 2015 - 2016 Adjunct professor, Departamento de Matemática, Universidad de La Habana, La Habana,
2013 – 2015 M.Sc. Student, Departamento de Matemática, Universidad de La Habana, La Habana, Cuba Fellowships, Awards and Honors (selected)
2021 TROY MathFest 2021 scholarship. April. Troy University
2021 Student Scholar Symposium winner scholarship. UCF
2020 AIM Summer School on Dynamics, Data and the COVID 19 Pandemic, American Institute of Mathematics, San Jose, California.
2019 College of Sciences General Scholarship. UCF
2019 Yvette Kanouff Industrial Mathematics Scholarship. UCF
2018 Award Dr. Ed Norman Award for Excellence In Math, UCF
2016 Award of the Facultad de Matemática y Computación to the Distinguished Investigation Group, Universidad de La Habana
Other Experience and Professional Memberships
2020 Research Stay Universidad Autónoma de México, CDMX, Mexico, July
2020 Research Stay Universidad de La Habana, La Habana, Cuba, August
2015 Research Stay Aix-Marseille Université, Marseille, France, June
2018 – Member, Society for Industrial and Applied Mathematics (SIAM)
2018 – Member, American Mathematical Society (AMS)
2018-2020 Member, Math Alliance
2019-2020 Member, Math Association of America
Contributions to Science
- Dynamical systems models to analyze disease propagation, cell proliferation, and dietary habits. Part of my research interest is the field of mathematical epidemiology, where I develop and apply mathematical models and dynamical systems to study the transmission and control of infectious diseases. My research interests include COVID-19, HIV, Dengue, and other emerging and re-emerging infections. I use analytical and computational methods to explore the effects of various factors, such as contact patterns, interventions, immunity, and evolution, on the dynamics and outcomes of epidemics. I aim to provide insights and guidance for public health decision-making and disease prevention. Some of my recent projects include modeling the impact of vaccination and social distancing on COVID-19 epidemics in different countries , analyzing the optimal allocation of antiretroviral therapy for HIV patients in resource-limited settings, and investigating the role of cross-immunity and vector control in Dengue transmission. I collaborate with experts from different disciplines, such as epidemiologists, biologists, statisticians, and clinicians, to ensure the relevance and validity of my models.  Guinovart-Sanjuán, D., Guinovart-Díaz, R., Vajravelu, K., Morales-Lezca, W., & Abelló-Ugalde, I. (2021)
- Multi-population analysis of the Cuban SARS-CoV-2 epidemic transmission before and during the vaccination process. Physics of Fluids (Woodbury, N.Y.: 1994), 33(10), 107107. Mathematical and computational modeling of piezoelectric and flexoelectric composite materials Piezoelectric and flexoelectric effects are essential for the design and optimization of composite materials that can harvest and store energy from mechanical sources. These effects are influenced by the microstructure of the composite, which consists of different phases with distinct properties, such as piezoelectric ceramics and non-piezoelectric polymers, and the geometrical structure (e.g., waviness, thickness variation, layers orientation), . To understand and control these effects, one needs to develop a multiscale modeling and simulation framework that can capture the behavior of the composite at various length scales, from the macroscopic to the microscopic level. I have developed a novel multiscale approach to investigate piezoelectric  and flexoelectric  composite materials using homogenization and finite element methods and to compute the effective electromechanical properties. By relating the microstructure to the macroscopic performance and functionality of the composite, we aimed to improve its energy conversion efficiency and reliability. Properties such as piezoelectric and flexoelectric coefficients were linked to microscopic parameters such as phase volume fraction and orientation. Local electric potential and polarization distributions revealed possible electromechanical coupling mechanisms.  Guinovart-Sanjuán, D., Vajravelu, K., Rodríguez-Ramos, R., Guinovart-Díaz, R., Bravo-Castillero, J., Lebon, F., Merodio, J. (2020). Effective predictions of heterogeneous flexoelectric multilayered composite with generalized periodicity. International Journal of Mechanical Sciences, 181(105755).  Guinovart-Sanjuan, D., Rodríguez-Ramos, R., Vajravelu, K., Mohapatra, R., Guinovart-Díaz, R., Brito-Santana, H., … Sabina, F. J. (2022). Prediction of effective properties for multilayered laminated composite with delamination: A multiscale methodology proposal. Composite Structures, 297(115910), 115910.  Guinovart-Sanjuán, D., Mohapatra, R., Rodríguez-Ramos, R., Espinosa-Almeyda, Y., & Rodríguez-Bermúdez, P. (2023). Influence of nonlocal elasticity tensor and flexoelectricity in a rod: An asymptotic homogenization approach. International Journal of Engineering Science, 193(103960), 103960.
- Mathematical and computational modeling of elastic composite materials Elastic composite materials are widely used in engineering applications. The microstructure and the interactions between different phases, such as fibers and matrix, often influence these materials’ mechanical properties (and failures). To design and optimize these materials, one needs to be able to model and simulate the behavior of the composite at different spatial scales, from the macroscopic to the microscopic level. This is a complex task, as it requires integrating and coupling multiple techniques. I have led a team to develop a novel multiscale approach to study elastic composite materials using homogenization and finite element methods. This approach combined data from three numerical methods: microstructure generation and characterization, homogenization theory, and finite element analysis, . Understanding the effects of microstructure on the overall performance and failure of the composite is the first step toward improving its functionality and durability. This multiscale approach revealed insights at different spatial scales. Macroscopic properties such as stiffness and strength were related to microscopic parameters such as fiber volume fraction and orientation . Local stress and strain distributions indicated potential damage initiation and propagation mechanisms. I also found that homogenization techniques provided accurate and efficient predictions of the composite’s effective properties and reduced the simulations’ computational cost.  Guinovart-Sanjuán, D., Rizzoni, R., Rodríguez-Ramos, R., Guinovart-Díaz, R., Bravo-Castillero, J., Alfonso-Rodríguez, R., … Sabina, F. J. (2017). Behavior of laminated shell composite with imperfect contact between the layers. Composite Structures, 176, 539–546.  Guinovart-Sanjuán, D., Rizzoni, R., Rodríguez-Ramos, R., Guinovart-Díaz, R., Bravo-Castillero, J., Alfonso-Rodríguez, R., … Sabina, F. J. (2018). Assessment of models and methods for pressurized spherical composites. Mathematics and Mechanics of Solids: MMS, 23(2), 136–147.