Prof. Oleg Kogan
I applly methods of statistical physics to solve problems in biophysics - with the focus on intracellular transport, population dynamics, and collective biological dynamics.
Statistical properties of cargo transport in biological cells.
Cells are complex systems in which multiple functions take place simultaneously. Production, transport, and delivery of cargo between different organelles is an important part of the proper cell function. Cargo is transported by special molecules called molecular motors that walk on cytoskeletal filaments. The morphologies of these filaments can take on many forms, with varying degree of disorder. In addition, cells are noisy environments, so motors tend to fall off the filaments, diffuse in the cytoplasm and rejoin other filaments. Because of all the disorder and noise, questions concerning transport of cargo (time for delivery, time for getting stuck in local traffic jams, etc.) are naturally statistical. This work intersects the subject of stochastic transport in disorderly environments, since microtubule morphologies tend to be disordered (possibly with applicaitons with bio-inspired materials). Finally - organelles interact with each other by exchanging material. This is called interactome. It is of great interest to understand how the disturbance of this network affects transport functionality of the cell.
If you're a student interested in using physics and math to understand biological world, please inquire. I have many projects of various levels of difficulty and abstraction - starting from simple "exercises" that can lead to results quickly, to in-depth projects that would form PhD thesis.
Collective dynamics of swarmalators.
I also study collective dynamics of a specific type of active particles called "swarmalators", with relevance to biological systems. Swarmalators have an internal cycle (represented by a periodic variable), and these cycles can synchronize with each other - that is, oscillators that swarm. The motion of each particle depends on the level of synchronization with other particles, and synchronization depends on the physical proximity of particles to each other. This double-feedback produces complex collective states. The goal is to understand collective behavior of swarmalators and connect with applications. Swarmalators have been implemented in condensed matter physics and in robotics. There’s also a strong evidence that some animals – such as Japanese tree frogs and some microorganisms (sperm cells and some bacteria) may act as swarmalators. Recently, colleagues and I studied the role of time delay in swarmalators, and found the existence of delay-induced phase phase transitions.
If you're a new student and find this intruiguing, there are many tantalizing projects that are waiting to be addressed: connection of swarmalation with glass physics and frustration (we have some exciting results); dynamics of externally-forced swarmalators; applications to molecular robotics; using microtubules and molecular motors to form active swarms; nanorobots in complex environments. Swarmalators are also a good test-bed for the study of nonequilibrium fluctuations.