The primary goal of my lab is to use quantitative modeling techniques to understand how biological systems organize to perform various functions. More specifically, my work investigates how biological structures at the scale of individual cells, collections of cells, or tissues self organize. Within this program, most of my time is dedicated to two primary lines of research. I) The first and most long-standing aspect of my work is understanding how the regulatory and biophysical machinery within a cell functions. On this front, I am particularly interested in how cells can use the same underlying molecular machinery to give rise to a range of heterogeneous responses (motility, spreading, wave like behaviors) under different conditions. II) My second primary interest is in determining how mechano-chemical signaling between cells, which is a form of local communication, can give rise to robust and reproducible organization on considerably larger length scales in the developing mammalian embryo. The main focus of this work is to understand how local cell-cell interactions along with stochastic elements of cellular processes lead to robust and reproducible formation of early embryonic structures that later form the placenta and the embryo itself.

In addition to these two main lines of research, I have a number of other projects of active interest. Over the recent few years, I have become increasingly interested in how structures in the Central Nervous System (CNS) develop and how they regenerate (or why they fail to do so) after injury. Additionally, I recently began a collaboration to develop and test computational models of human decision making, with the goal of understanding how people process information that changes during the course of making a decision. Despite the fact that these investigations occur over a range of biological scales, they do have a common theme. That theme is that all of this work involves direct collaboration with experimental labs along with the development of novel models and methods for encoding and testing verbal hypotheses for how systems function.


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