Sarbani Basu

Sarbani Basu is the William K. Lanman Jr. Professor in the Department of Astronomy at Yale University, where she has been a faculty member since 2000 and has served as Department Chair since 2016. She is a leading astrophysicist specializing in helioseismology and asteroseismology, using stellar oscillations to probe the internal structure and dynamics of the Sun and other stars.

Education:

• Bachelor’s Degree, University of Madras (1986)
• Master’s Degree, Savitribai Phule Pune University (formerly University of Pune)
• Ph.D., University of Mumbai (1993), conducted at Tata Institute of Fundamental Research
• Postdoctoral Research, Queen Mary & Westfield College (London)
• Postdoctoral Research, Theoretical Astrophysics Center, Aarhus University, Denmark
• Member, Institute for Advanced Study, Princeton (1997–2000)

Her research focuses on understanding the Sun’s interior structure, rotation, and elemental abundances, particularly helium, using data from networks like GONG and instruments such as MDI and HMI aboard SoHO and SDO. She extends her work to other stars using data from NASA’s Kepler and TESS missions through her leadership in the Kepler and TESS Asteroseismic Science Consortia (KASC and TASC). Her recent publications reflect a deep engagement with global seismology of the Sun, solar core structure, and the reconciliation of helioseismic data with solar models.

Scientific Awards:

• Vainu Bappu Gold Medal (1996)
• NSF CAREER Award (2004)
• Fellow, American Association for the Advancement of Science (2015)
• George Ellery Hale Prize (2018)
• GOPIO Honor for Basic Sciences (2018)

Prof. Basu has held significant leadership roles, including Chair of the ASTRO2020 Decadal Survey panel on Sun, Stars and Stellar Evolution, Vice-Chair and Chair of AURA’s Board of Directors, and Chair of Yale’s Department of Astronomy. She is also co-author of the authoritative textbook Asteroseismic Data Analysis, which provides a comprehensive guide to analyzing asteroseismic data. Her work bridges theoretical modeling, observational data, and large-scale scientific collaboration.