Multiscale modeling of ocular and cardiovascular systems
September 29 to October 3, 2025
at the
American Institute of Mathematics,
Pasadena, California
organized by
Virginia Huxley,
Sergey Lapin,
Lorenzo Sala,
Marcela Szopos,
and Mohamed Zaid
Original Announcement
This workshop will bring together experts in mathematical modeling, biomedical engineering, and clinical research to advance multiscale modeling approaches that bridge ocular, cardiovascular, and systemic dynamics. The non-invasive nature of ocular measurements, such as retinal blood flow and intraocular pressure, provides a unique opportunity for early diagnosis and monitoring of conditions such as diabetes, hypertension, heart failure, and neurological disorders. However, translating these insights into clinical practice requires a strong collaboration between clinicians and modelers to design interpretable and actionable approaches.
A key focus of the workshop will be integrating mechanistic models with data-driven approaches, balancing interpretability with predictive power. Participants will work on developing coupled models using ordinary and partial differential equations, numerical methods, and stochastic approaches to better capture physiological processes across different scales. The workshop will also address challenges in integrating clinical data into these models, exploring techniques like uncertainty quantification, data assimilation, and machine learning to improve model reliability and predictive accuracy.
Through interdisciplinary discussions, the workshop aims to ensure that mathematical models are biologically relevant and clinically useful. By combining biophysical principles with clinical data, participants will explore new ways to refine and validate diagnostic models, bridging the gap between theoretical research and real-world medical applications. Practical sessions will focus on solving computational challenges, refining existing models, and identifying key open questions in the field, with the goal of establishing new research collaborations and improving the mathematical foundation of biomedical modeling.
The main topics for the workshop are:
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Multiscale mathematical modeling: developing models that integrate ocular hemodynamics, cardiovascular function, and systemic regulation with direct relevance for non-invasive diagnostics;
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Stochastic models and uncertainty quantification: addressing biological variability using stochastic differential equations, inverse problems, and data assimilation to improve reliability in clinical predictions;
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Integrating data-driven and mechanistic approaches: exploring how statistical methods, machine learning, and hybrid modeling frameworks can enhance model calibration, improve disease prognosis, and support clinical decision-making.
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Clinically relevant modeling questions and medical impact: identifying key challenges in non-invasive diagnostics and exploring how mathematical models can improve clinical decision-making. The focus will be on developing models that provide actionable insights, enhance diagnostic accuracy, and support personalized medicine.
By fostering discussions between clinicians, mathematicians, and engineers, this workshop aims to create clinically meaningful models that can drive discoveries and improve patient outcomes.
Material from the workshop
A list of participants.
The workshop schedule.
A report on the workshop activities.
Workshop videos
Talk slides
