Our New Postdoctoral Researchers

Submitted by Arts & Sciences Web Team on

Travis AshkamTravis Askham is a Research Associate of Applied Mathematics at the University of Washington. As part of the Kutz research group, he works on numerical methods for data analysis and dynamical systems. As a continuation of his dissertation research, he also works on fast methods for partial differential equations.

Travis received his Ph.D. (2016) in Mathematics from the Courant Institute at New York University, under the supervision of Leslie Greengard. Before that, he received his M.A. (2010) in Mathematics and B.S. (2010) in Applied Mathematics from the University of California, Los Angeles.


Gabrielle GutierrezGabrielle Gutierrez works in collaboration with Eric Shea-Brown in Applied Mathematics and Fred Rieke in Physiology and Biophysics. Her research is aimed at understanding how neural circuits implement functional computations using the rich assortment of biophysical mechanisms available to them. These studies are based in the retina; a profoundly complex circuit that may hold the key to understanding how local neuron properties contribute to global circuit function. Gabrielle seeks to address these issues using a combination of experimental electrophysiology techniques, and normative theories and computational modeling. This work will provide insight into the multiple solutions that allow neural circuits to adapt to the immensely complex stimuli encountered in nature.

Gabrielle has a doctoral degree in Neuroscience from Brandeis University where she was advised by Dr. Eve Marder. As a graduate student at Brandeis, Gabrielle was awarded an IGERT Training Fellowship for interdisciplinary research. She received her bachelor’s degree from Barnard College, Columbia University, where she majored in Physics and minored in Applied Math.


Niall ManganNiall Mangan is an Acting Assistant Professor in the Department of Applied Mathematics at University of Washington and Research Associate Consultant for Global Good’s Institute for Disease Modeling. She develops data-driven methods for identifying underlying nonlinear dynamic models of complex systems including metabolic, regulatory, and epidemiological networks. The goal of these methods is to discover and control underlying mechanisms and behavior in these systems, thereby advancing bio-engineering, drug discovery, and disease response.

Niall received her Ph.D. in Systems Biology from Harvard University, where she worked with Michael Brenner on modeling the spatial organization of biochemical reactions in bacteria and material processing using femtosecond lasers. Prior to joining University of Washington, she was a Postdoctoral Associate in the Photovoltaics Research Laboratory at Massachusetts Institute of Technology and a Visiting Lecturer at Brown University School of Engineering.