Michelson Postdoctoral Prize Lectureship

Congratulations to Chapin Korosec, PhD, Awarded 2024 Michelson Postdoctoral Prize

Chapin Korosec, PhD, York University, 2024 MPPL Winner

CHAPIN KOROSEC, PhD, York University, Toronto, Canada, has been named the winner of this year’s MICHELSON POSTDOCTORAL PRIZE, is spending one week in residence during the week of April 7, 2025, on the Case Western Reserve University campus. This year marks the 26th annual MICHELSON POSTDOCTORAL PRIZE LECTURESHIP, awarded each year to a junior scholar active in any field of physics. As part of his residency, Dr. Korosec is delivering two (2) technical lectures and a colloquium. The lectureship also awards an honorarium of $3,000 plus travel expenses.

Dr. Korosec is a physicist with a research background in theoretical and experimental biophysics, with a particular focus on the motility of molecular machines. Details on the lectureship, including lecture and colloquium topics, locations, and times are as follows:

MPPL Lecture #1 (Monday, April 7, 12:45-2pm, Rockefeller 221)
A Physicist’s Toolbox for Particle Trajectory Analysis: From Motion to Mechanism
Abstract: This technical talk presents a foundational toolbox for analyzing the motion of particles in complex systems. It is the talk I wish I had heard at the beginning of my PhD in biophysics. We begin by briefly introducing trajectory acquisition, but quickly shift to the core physical analysis tools that unlock meaning from motion. We derive and compare multiple forms of the mean squared displacement (MSD), discuss how to distinguish normal, anomalous, and superballistic regimes, and explore what MSD scaling reveals about underlying forces, heterogeneities, and energy landscapes. We also highlight the use of higher moments (e.g. kurtosis) to detect non-Gaussianity and ergodicity breaking. We then briefly introduce an approach to passive microrheology, using Laplace and Fourier transforms of MSD to infer viscoelastic moduli, and explain how to reconstruct potential energy landscapes using the Boltzmann inversion formula. This talk is designed to serve as a theoretical and practical starting point for anyone working with particle trajectories, particularly in biological, biophysical, soft matter, or disordered systems.

MPPL Lecture #2 (Tuesday, April 8, 11:30am, Rockefeller 221)
Machine learning and dynamical systems modelling of the human immune response to antigenic perturbations
Abstract: Following a vaccine inoculation or disease exposure an immune response develops in time, where the description of its time evolution poses an interesting problem in dynamical systems. The principal goal of theoretical immunology is to construct models capable of describing long term immunological trends from the properties and interactions of its elementary components. In this talk I will give a brief description of the human immune system and introduce a simplified version of its elementary components. I will then discuss our mathematical and machine learning contributions to the field. I will focus on mechanistic modelling work describing vaccine-generated SARS-CoV-2 immunity and applications of our work towards understanding vaccination responses in people living with HIV. Finally, I will discuss our machine learning public health approach, which we find capable of predicting immune response outcomes from repeated-dose immunological data.

MPPL Physics Colloquium (Thursday, April 10, 4-5;30pm, Rockefeller 301)
Modelling and engineering burnt-bridge ratchet molecular motors
Abstract: Molecular motors are protein-based machines essential for directional transport of cellular components. Nature has evolved many mechanisms for achieving directed motion on the subcellular level. The burnt-bridge ratchet (BBR) is one mechanism used to achieve superdiffusive molecular motion over long distances through the successive cleavage of surface-bound energy-rich substrate sites. The BBR mechanism is utilized throughout Nature: it can be found in bacteria, plants, insects, humans, as well as non-life forms such as influenza. Inspired by biology, we have synthesized and characterized a protein-based microscale motor we dub the lawnmower [1]. We find the lawnmower demonstrates saltatory motion where superdiffusive runs are interspersed with subdiffusive dynamics, with the system reaching average speeds of 80 nm/s. The lawnmower is the first example of an autonomous protein-based synthetic motor purpose-built using nonmotor protein components. In this talk, I will discuss the lawnmower system and its implementation in microfabricated tracks where we demonstrate it is capable of track-guided motion. I will also discuss our Langevin [2] and Gillespie [3] simulation approaches, where we seek to understand how BBR engineering principles alter particle dynamics. Our work provides insights into the mechanistic origin for the observed dynamics found in both synthetic and natural (e.g. Influenza) systems.