Personal Statement

As a scientific trainee, I worked with Dr. Michael A. Savageau (Member, National Academy of Medicine and Distinguished Professor) (PhD thesis work)—on understanding the design principles of genetic regulatory networks—and Dr. Alan S. Perelson (Fellow, American Academy of Arts and Sciences and Senior Laboratory Fellow) (postdoctoral work)—on understanding the within-host tissue dynamics of HIV. I also worked as a postdoc for one year under the supervision of Dr. Byron Goldstein (Laboratory Fellow), who introduced me to the “cell signaling problem,” which I have worked on since.

My primary appointment is in the Theoretical Biology & Biophysics Group of the Theoretical Division at Los Alamos National Laboratory (LANL). I am also affiliated with the Department of Biology at the University of New Mexico (UNM) and the UNM Comprehensive Cancer Center. My research interests include mathematical modeling of cellular regulatory systems, especially cell signaling networks that play a role in immunity and/or cancer, and developing advanced methods and software tools to support modeling work in systems/quantitative biology.

I have >20 years of experience in mathematical modeling of biological systems (e.g., genetic regulatory, metabolic, and cell signaling networks) and >15 years of experience developing methods and software tools that enable systems biology modeling (e.g., the BioNetGen and PyBioNetFit software packages). I have significant experience in ODE (ordinary differential equation) modeling, stochastic processes, rule-based modeling, development of new kinetic Monte Carlo methods, curve fitting, uncertainty quantification, applications of machine learning methods, and open-source software development. The biological systems that I am most familiar with include immunoreceptor signaling networks, receptor tyrosine kinase signaling networks, and the cellular network regulating autophagy.

Research

Scientist: Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratories