Subhrajit Roy
Subhrajit is a research scientist at Google Brain where he focuses on developing machine learning systems for analysing health data. He has co-developed novel sparse multi-task deep neural networks for adverse event prediction in hospitals and is currently focusing on building inclusive healthcare technologies. Previously, he has worked at IBM Research Australia for three years as a research staff member. During this time, he co-designed portable machine learning systems for seizure management in epileptic patients. Recognizing the potential of this work, Forbes magazine included him in their prestigious 30 Under 30 list. He has authored 35+ scientific papers. His work has been cited 1000+ times and featured in IEEE Spectrum, IEEE Pulse, VentureBeat, The World Economic Forum, amongst others. He also serves as an Associate Editor of the Neuromorphic Engineering section of Frontiers in Neuroscience and a reviewer for several AI conferences. He earned his BE degree from Jadavpur University, India and PhD from Nanyang Technological University, Singapore.
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Google
Batch Calibration: Rethinking Calibration For In-Context Learning And Prompt Engineering
Lev Proleev
Diana Mincu
International Conference on Learning Representations (ICLR) (2024)
Healthsheet: development of a transparency artifact for health datasets
Diana Mincu
Lauren Wilcox
Jessica Schrouff
Razvan Adrian Amironesei
Nyalleng Moorosi
ACM FAccT Conference 2022, ACM (2022)
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings
Jessica Schrouff
Sanmi Koyejo
Eva Schnider
Krista Opsahl-Ong
Alex Brown
Diana Mincu
Christina Chen
Silvia Chiappa
Proceedings of Neural Information Processing Systems 2022 (2022)
Multi-task prediction of organ dysfunction in the ICU using sequential sub-network routing
Diana Mincu
Eric Loreaux
Anne Mottram
Jessica Schrouff
Hugh Montgomery
Ali Connell
Nenad Tomašev
Martin Seneviratne
Journal of the American Medical Informatics Association (JAMIA) (2021)
