Reshmi Ghosh @ Microsoft Research
Reshmi Ghosh
Reshmi is an Applied Scientist in the Microsoft AI program under the Office of Applied Research. She focuses her time to understand modern knowledge search behavior, including analyzing knowledge base updates, search motivation, knowledge consumption and dispersion in organizations. In the past year has dedicated her time accelerating the development of intelligent features in Microsoft Loop and Viva.
Microsoft Research
About

Reshmi is a Ph.D. Applied Scientist in Microsoft Search, Assistant and Intelligence – Microsoft Research (opens in new tab) leading the effort to research and productionize solutions for safeguarding CoPilots against jailbreaks with a primary focus on M365 Chat CoPilot (opens in new tab) (Business Chat). She is exploring the security risks associated with deploying Large Language Models in production and the researching the brittleness of Generative AI solutions across a variety of user scenarios to ensure a sustainable and safe experience for every customer and organization around the globe, who are using Microsoft CoPilots.

Previously, Reshmi was part selected to be part of Cohort 4 of MAIDAP: Microsoft’s coveted AI acceleration program (opens in new tab) (then, under the Office of Applied Research led by Jaime Teevan (opens in new tab)). During this time she served as a Tech Lead to drive teams towards bettering customer experience by integrating state-of-the-art machine learning capabilities in Microsoft products and services while working at the intersection of NLProc, human-centered AI, and Reinforcement Learning.

Before joining Microsoft, she completed my doctorate degree at Carnegie Mellon University, researching novel deep-learning and Bayesian approaches for data augmentation methods to design resilient energy infrastructures that are adaptable to climate change, in collaboration with the University of Michigan and CMU Portugal.

Within Microsoft, Reshmi has spent time researching and building machine learning models that can help understand/predict enterprise user and consumer behavior to power intelligent service improvements (e.g., efficient search, information consumption) and commanding experiences (e.g., search, command prediction, task automation, etc.) before joining the task-force to deliver the first-of-its kind Generative AI solution.

She is a leading mentor and speaker at reputed NLP conferences and also leads research collaborations with universities (University of Massachusetts, Amherst & MIT CSAIL).

Please see Reshmi’s Personal Website (opens in new tab) or Twitter (opens in new tab) for the latest updates about her work.

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