Biography
Blagoy Rangelov received a B.S. degree in Physics from Sofia University, Bulgaria, where, a year later, he graduated with an M.S. degree in Astronomy and Astrophysics. In 2006 he joined the Ph.D. program of the Department of Physics and Astronomy at the University of Toledo, where he worked on extragalactic astronomy. Blagoy Rangelov broadened his knowledge and skillset by becoming a Pre-doctoral Fellow at the Harvard-Smithsonian Center for Astrophysics in Cambridge, MA. There he had the excellent opportunity to carry out research in extragalactic high-energy astrophysics and gained hands-on experience in using modern X-ray telescopes and their data analysis. In 2013 he became a Postdoctoral Scientist at the George Washington University, where he conducted research in galactic and extragalactic high-energy astrophysics and participated in a number of educational and outreach activities. In the Fall of 2016, Blagoy Rangelov joined the Department of Physics at Texas State University.
Research Interests
Multi-wavelength Astronomy: extragalactic multi-wavelength surveys of normal and starburst galaxies; multi-wavelength searches for compact objects; classification of X-ray sources using machine learning techniques; optical imaging and spectroscopy.
High-energy Astrophysics: formation and evolution of X-ray binaries (galactic and extragalactic); compact object populations in galaxies; bow shocks around pulsars and high-velocity stars; identification of GeV and TeV sources, pulsars and pulsar wind nebulae.
Gravitating Systems: star cluster populations and evolution, close binary systems. Computational Astrophysics: N-body simulations, astrostatistics, machine learning, data min- ing and visualization.
High-energy Astrophysics: formation and evolution of X-ray binaries (galactic and extragalactic); compact object populations in galaxies; bow shocks around pulsars and high-velocity stars; identification of GeV and TeV sources, pulsars and pulsar wind nebulae.
Gravitating Systems: star cluster populations and evolution, close binary systems. Computational Astrophysics: N-body simulations, astrostatistics, machine learning, data min- ing and visualization.