🗓️ May 14, 2026 | Dr. Kevin Flores | Hybridizing Data Science and Mechanistic Models for Biological Systems

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May 4, 2026, 7:00:18 AMMay 4

to IMOBIO Community

Dear WG Members,

Announcing our next seminar from Dr. Kevin Flores, happening next Thursday @ 10am ET!

Title: Hybridizing Data Science and Mechanistic Models for Biological Systems

Abstract: Biological systems exhibit complex, multiscale dynamics driven by heterogeneity, stochasticity, and partial observability, thereby posing fundamental challenges for both mechanistic modeling and purely data-driven approaches. In this talk, I present several frameworks for hybrid modeling of biological data that integrate topological data analysis, equation learning, and distributional inverse problems for parameter estimation in dynamical systems. Topological summaries distill complex spatiotemporal structure into geometry-aware features that make agent-based model comparison, parameter estimation, and uncertainty quantification feasible through likelihood-free methods such as Approximate Bayesian Computation. Equation learning methods enable discovery of governing ODE and PDE models from noisy data and stochastic simulations, and I will introduce the concept of multi-experiment equation learning to enforce structural invariance and improve generalization across parameter space. To rigorously quantify biological heterogeneity and uncertainty, I highlight distributional inverse problem formulations based on the Prohorov metric framework, which shifts inference from point estimates to parameter distributions consistent with aggregate data. I will illustrate these different approaches for hybridizing data science into model discovery, selection, and uncertainty quantification through applications to collective cell motion, angiogenesis, reaction-diffusion systems, tumor growth and infectious disease modeling.

🗓️ Please click the links below for further Details, Zoom link, and community updates.

Whether you're a regular or new to our series, we look forward to welcoming many of you to the discussion.