Satrajit Ghosh.

Satrajit Ghosh

Director
Open Data in Neuroscience Initiative

Satrajit Ghosh is director of the Open Data in Neuroscience Initiative and a principal research scientist at the McGovern Institute for Brain Research at the Massachusetts Institute of Technology. He is also assistant professor of otolaryngology-head and neck surgery at Harvard Medical School. He is a computer scientist and computational neuroscientist by training.

Ghosh directs the Senseable Intelligence Group, whose research portfolio comprises projects on spoken communication, brain imaging and informatics to address gaps in scientific knowledge in three areas: the neural basis and translational applications of human spoken communication, machine-learning approaches to precision psychiatry and medicine, and preserving information for reproducible research and knowledge generation. He is a principal investigator on National Institutes of Health projects supported by the BRAIN Initiative and the Common Fund and is a big proponent of open and collaborative science.

He received his B.S. (honors) degree in computer science from the National University of Singapore and his Ph.D. in cognitive and neural systems from Boston University.

Explore more from The Transmitter

Research image of portions of the adult dentate gyrus.

Machine learning spots neural progenitors in adult human brains

But the finding has not settled the long-standing debate over the existence and extent of neurogenesis during adulthood, says Yale University neuroscientist Juan Arellano.

By Claudia López Lloreda
3 July 2025 | 7 min listen

Xiao-Jing Wang outlines the future of theoretical neuroscience

Wang discusses why he decided the time was right for a new theoretical neuroscience textbook and how bifurcation is a key missing concept in neuroscience explanations.

By Paul Middlebrooks
2 July 2025 | 112 min listen
Overlapping speech bubbles.

Memory study sparks debate over statistical methods

Critics of a 2024 Nature paper suggest the authors failed to address the risk of false-positive findings. The authors argue more rigorous methods can result in missed leads.

By Katie Moisse
2 July 2025 | 5 min read