James V. Roggeveen

For as long as I can remember I have been compelled by a desire to better understand the complex physical processes happening around me and a desire to use that understanding in the pursuit of innovation. These twin pursuits have formed the core of my journey as both a mechanical engineer and an applied mathematician. In the process, I have studied fluid mechanics, a field deeply enriched by the techniques of applied mathematics, the fundamental understanding of physics, and applicability of engineering.

I am currently a Postdoctoral Fellow at Harvard University working in the lab of Professor Michael Brenner. Here, I am developing differentiable simulations of fluid mechanics with JAX, leveraging its automatic differentiation capabilities. This approach enables the creation of ODE and PDE solvers that directly compute exact gradients of solutions with respect to input parameters, such as boundary values and forcing terms. By defining a loss function on the solution or its components (e.g., stress integrals over boundaries), these solvers facilitate gradient-descent optimization. This importantly offers greater flexibility than traditional adjoint methods and retains gradient-based optimization benefits of modern machine learning approaches without sacrificing physical interpretability. My current projects are focused on applying these methods to problems in rheology and ice sheet dynamics.

As a researcher and an engineer, my core competencies are in the development of data-driven mathematical models to predict, control, and optimize complex systems. My training has given me effective verbal, written, and visual communication skills, including conveying complex mathematical systems through animation. I am experienced with cross–discipline collaboration with diverse teams to implement engineering solutions in fast-paced environments and automation of data validation and analysis pipelines to improve efficiency in dealing with experimental data. I am competent with Python, Mathematica, Git, and Solidworks.

During my PhD in Mechanical and Aerospace Engineering at Princeton, my research focused on modeling particle motion in fluid flows, and specifically the impact of particle shape on single-particle dynamics. I explored how asymmetric particle shapes cause consistent cross-stream motion in 2D simple shear flows. I identified specific geometric conditions that determine cross-flow drift and developed a toy model of two linked slender particles forming an asymmetric hinge, which I analyzed to identify drift-inducing configurations. In shear flows with oscillating shear rates, rigid particles experience no net displacement over each oscillation period. However, many natural particles deform elastically under stress. By incorporating elastic joints into the hinge model, I showed that elasticity leads to drift during oscillations. By adjusting body geometry and oscillation frequency, the drift velocity and direction can be controlled.

In addition to this work, I developed a hydrodynamic model for micropipette aspiration of biological condensates. Biological condensates, formed by liquid-liquid phase separation of protein-rich compounds in the cytoplasm, are vital for cellular function and regulation, with their material properties linked to degenerative diseases. The model I developed incorporates a non-linear relationship between time and aspiration length and corrects for dissipation due to the flow geometry. This approach, validated with a standard oil of known fluid properties, allows one to obtain accurate universal material properties for condensates with a single experiment. This is in contrast to traditional methods, which have a number of limitations, including only returning a ratio of critical material parameters or altering the material state of the condensate through photobleaching. Additionally, I built an analysis pipeline to automatically process raw experimental data and output the relevant material parameters.

Before Princeton, I completed a Master’s degree in Applied Mathematics at the University of Cambridge, where I was a member of Trinity College and received a final mark of distinction for my performance. Prior to my stint across the ocean I graduated from MIT with a degree in Mechanical Engineering, having gained a number of skills in both engineering theory and practice. I look back fondly on my time at the Institute, but most especially remember the enduring friendships I built there that continue to flourish to the present day.

In summary, I am an experienced researcher with background in applying computational and mathematical modeling techniques to challenges in mechanical engineering, fluid mechanics, and applied mathematics. Interested in applying my skills to solve challenging problems in fast-paced industry environments as part of a committed team effort.