Personal Information

Thavisha Dharmawardena
Postdoctoral Associate, NASA Hubble Fellow
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Email:t.dharmawardena AT
Personal Home;
CCPP Advisor:David Hogg
Thavisha Dharmawardena achieved her master’s degree in 2014 from the University College London, working with Professor Micheal Barlow. She moved to Taiwan in 2015 to achieve her PhD, and was mentored by Professor Francisca Kemper at Academia Sinica Institute of Astronomy and Astrophysics and Professor Chung-Ming Ko at the National Central University. During her PhD, Thavisha worked on understanding the properties of cold dust emission from evolved stars. In 2019, she moved to Heidelberg, Germany, to carry out her postdoctoral research at the Max Planck Institute for Astronomy in the Gaia group, where she worked with Dr. Coryn Bailer-Jones. She recently joined the Flatiron Institute’s Center for Computational Astrophysics in New York as a Flatiron Research Fellow. She is currently focused on understanding the Milky Way's three-dimensional structure by examining its dust distribution using state-of-the-art machine learning techniques. Interstellar dust obscures our view of the universe by scattering, absorbing, and re-emitting light. It is crucial to our understanding of key astrophysical processes. Meanwhile, its distribution traces galactic structure, making three-dimensional dust distribution vital to our understanding of the Milky Way. As a Hubble Fellow, Thavisha will extend her 3D mapping efforts to explore the dust density and grain size distributions of the Milky Way at parsec resolutions, using large surveys such as Gaia and the Sloan Digital Sky Survey (SDSS). She will explore how dust is processed in the interstellar medium and provide a comprehensive view of the interlink between dust, gas, and stars. Extending on this, she will exploit prior knowledge to simultaneously refine distances and map dust. She will extend her work to develop 3D dust maps of the Small Magellanic Cloud, a local low-metallicity counterpart to high-redshift galaxies. Understanding low-metallicity dust is relevant both to understanding the underlying stellar populations in high-redshift galaxies and successfully modeling star-formation in the early universe.