Bryan Travis Email & Phone Number

While I was in college (as a National Merit Scholar), I worked in the Chrysler Aerospace Div. Thermodynamics group, and at the Boeing Aerospace Simulation Center, on the exciting NASA Apollo project. Next life event was graduate school. My major focus was applied mathematics, but I took many additional courses in physics, chemistry and biology. Following graduate school, PhD in hand, I was fortunate to hire on at Los Alamos. During my years at Los Alamos National Laboratory, I've worked in various areas of computational physics and mathematics. Areas of experience include multiphase flow and transport in porous media (thermal as well as isothermal), wave propagation in elastic/plastic media, inverse and optimization problems, sensitivity analysis, cellular automata models of porous flow, in situ bioremediation modeling, soil microbial interactions, geochemical modeling of acid mine drainage, multi-scale analysis, planetary dynamics, thermal/chemical convection, permafrost active layer dynamics, natural and controlled source electromagnetic sensing of geologic structures, radiation/hydrodynamics with optical signatures, and recently using ML/NNs to locate methane leaks at oil and gas fields. My experience in porous flow and reactive transport modeling and inverse algorithms led to a long-term association with HydroGeoChem, Inc, an Arizona enviro-science company. In addition to these traditional areas of mathematical physics, I'm fascinated by biological processes. Several years ago, I completed an M.S. program in human physiology at the U. of New Mexico. I've used that knowledge to develop computational models for simulation of vascular networks and computational neurobiology (auditory and visual systems, and first principles calculation of MRI in neural tissue). I was recently part of a team at New Mexico Consortium developing atomic magnetometers for high-resolution measurements of neural activity. I’m now associated with the Planetary Science Institute, a leading research organization in space science. That association brings me back to where I started my career - studying the planets and their moons. This year (2023) I completed an intensive Data Science and Machine Learning program through Great Learning and MIT. I finished with a rank of 4th out of 150+, and 2nd on the team hackathon competition. I’m author/co-author of about 150 refereed papers and technical reports (many are listed at www.ResearchGate.net). I’ve held Adjunct Professor positions and taught courses at the University of New Mexico, New Mexico Tech and Florida State University.

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  Florida State University

  Applied Mathematics/Fluid Dynamics