Daniel S. Fisher
My primary research focus in recent years has been the statistical dynamics of evolutionary processes. This includes theoretical work on general issues and models in evolutionary dynamics, especially quantitative aspects, collaborations with experimental groups on laboratory evolution of microbes and on field studies of microbial diversity, and now exploring the interplay of microbial evolution and ecology. For humans, active collaborations are on the repertoire and dynamics of the immune system, and on the evolution of cancers, and I am starting to actively pursue a long-standing interest in neuroscience.
My biological research also includes projects on the dynamics of cellular processes. Before diving into biology, I worked in various areas of condensed matter and statistical physics including ultralow temperature phases of helium, superconductivity, physics of disordered materials, fracture mechanics, and earthquakes.Website
I’m a PhD student in the physics department. My primary interest is in studying models of epistasis, and understanding how the statistics of “fitness landscapes” contribute to the dynamics of evolution. I’m particularly interested in questions about the speed and predictability of long term evolution.
More recently, I’ve been working at the intersection of evolution and ecology, specifically on trying to understand the generation and maintenance of diversity at a variety of scales. In addition I’m interested in theoretical machine learning, trying to understand learning dynamics in neural networks using ideas from statistical physics.
I’ve also worked on designing fitness assays using DNA barcoding technology in yeast, in collaboration with the Sherlock and Petrov labs at Stanford. We can use these fitness measurements to quantitatively understand the of evolution, and to try to tease out the reasons why some variants succeed while others fail.Website
I’m a postdoc co-advised by Profs. Daniel Fisher and Surya Ganguli studying grid cells and animal navigation in collaboration with the Giocomo lab. I work on a combination of theory and data analysis developing neural models of how an animal navigates and learns about its environment from a combination of step-counting and landmarks. I’m also interested in the statistics of ensembles of trained neural networks. During my Ph.D., I studied the physics of termite mound ventilation. Find out more on my website.Website
I am a physics PhD student studying models of evolution and ecology. I’m broadly interested in how the interplay of various factors–from mutation and recombination to epistasis and spatial structure–determine the pace of evolution and the diversity observable in sequencing data.
Some species are capable of both sexual and asexual reproduction and my work has focused on how the asexual evolutionary dynamics are altered by very low frequencies of sexual mating. In ecology, I am interested in how microbial interactions lead to high levels of coexistence and am exploring models with spatial structure and environmental feedback.Website
I’m a postdoctoral fellow interested in combining theoretical physics and interpretable machine learning to better understand complex dynamical systems in biology. Now, I’m modeling the internal neural dynamics of the retina with a convolutional neural network and trying to build a minimalistic mathematical model out of it. Before, I completed my Ph.D. with Profs. David Nelson and Michael Brenner at Harvard University where I developed and applied methods of statistical physics to solve problems in soft matter physics, population genetics, and neuroscience.Website
I am a PhD student in Applied Physics working on population dynamics in the context of cancer biology. How do mutations arise, propagate, and accumulate, and what are the most pragmatic methods for monitoring, early detection, and intervention? To begin to address these questions we consider mutations in the blood, as this provides a well-mixed population with accessible data. I have worked on a basic model of clonal dynamics which, excitingly, compares favorably to recent blood sequencing data. The model has been generalized to include aspects of biological richness.
I am also interested in the dynamics of ice sheets and glaciers, particularly the fast-flowing ice streams of West Antarctica. The physical mechanisms controlling the location and spatial extent of these ice streams are not well constrained, and the dynamics of these ice streams on timescales as short as decadal provide some of the greatest uncertainty in sea level rise predictions. I am attempting to theoretically model how conditions at the base of an ice stream impact its motion, understand feedback mechanisms between flowing ice and the underlying bed, and ultimately evaluate the stability or collapse of sheets in West Antarctica.Website
Former PhD student in Biophysics, currently a postdoc at the Broad Institute/MIT.Website
Former PhD student in Physics (at Harvard), currently lecturer in the Department of Statistics at University of Chicago.Website