Reshmi Ghosh - Wikipedia
Reshmi Ghosh is an Indian actress and beauty pageant titleholder. [1] Ghosh was born in 1978 and brought up in Kolkata. She attended school at Carmel Convent School (Class 10, 1995 …
ABOUT ACADEMICS PROJECTS | Reshmi Ghosh
I’m Reshmi, Applied Scientist at Microsoft’s Search and Intelligent Assistance (MSAI) team, focusing on developing state-of-the-art Responsible AI and Trustworthy evaluation …
People — ASSET Lab
Reshmi graduated with a Ph.D. in Civil and Environmental Engineering from Carnegie Mellon University in 2021. She is now a ML Scientist at Microsoft AI. She researched the reliability of …
Reshmi Ghosh @ Microsoft Research
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 …
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Reshmi Ghosh
Deployed an end-to-end pipeline in Python and PySpark to monitor anomalies in Azure services by consuming terabytes of Service Level Indicator data in Synapse VM. Improved existing …
Reshmi Ghosh - Google Scholar
Proceedings of the 33rd ACM International Conference on Information and … R Ghosh, R Seetharaman, H Wadhwa, S Aggarwal, S Basu, S Srinivasan, ... The 7th BlackboxNLP …
[2410.00857] Quantifying reliance on external information over ...
2024年10月1日 · View a PDF of the paper titled Quantifying reliance on external information over parametric knowledge during Retrieval Augmented Generation (RAG) using mechanistic …
Dr. Reshmi Ghosh, Ph.D. - Applied Scientist - YouTube
2023年8月22日 · Dr. Reshmi Ghosh, Ph.D. ( https://www.microsoft.com/en-us/resea... ) is an Applied Scientist as part of Microsoft’s AI acceleration program, under their Office of Applied …
ABOUT ACADEMICS PROJECTS Reviewing Activities - Reshmi Ghosh
Inspired by the bright minds of CMU, working on interdisciplinary research, I challenged myself to pursue both my masters’ degree with a focus in data-driven analysis, a unqiue pathway to …
Reshmi Ghosh - dblp
Reshmi Ghosh: Data-driven stochastic reliability assessment of the US electricity grid under large penetration of variable renewable energy resources. Carnegie Mellon University, USA, 2022