Our group is fortunate to collaborate with other incredible scientists. An incomplete list of recent past and present collaborator includes:

theory collaborators

experimental collaborators


Understanding particle movement data in cells

Rapid advancements in imaging have led to an abundance of trajectory data of stuff moving around inside cells. However, what to do with this data isn't totally clear.

Our work in this realm has been adapting statistics & data science tools to connect mechanistic models of movement with particle data, especially in mitosis and intracellular transport.

Stochastic models of the cytoskeleton & motors

Cells rely on teams of motor proteins to perform vital tasks including carrying cargo enormous distances and coordinating mitosis. These motors behave randomly as individuals yet unite harmoniously.

A central theme of my research pursues the question: how does the randomness of individual motors affect their ability to function collectively?

Information flow in ligand/receptor signaling

Cells transmit signals by releasing particles (ligands) that diffuse around in search of targets (receptors), an inherently random process that can be studied mathematically using PDEs and singular perturbationtheory.

We are interested in understanding how spatial organization (e.g. movement, clustering) affects the cell's ability extract information from this noisy communication procedure.