Reshmi Ghosh

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Technical Lead & Senior Applied Scientist, Microsoft Turing | Copilot and Agents Core org

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Hi! I am Reshmi Ghosh, a Senior Applied Scientist at Microsoft Turing in the Copilot, Agents and Core org (Previously at MSAI and Microsoft AI Acceleration Program under Office of the CTO). I currently serve as a Technical Lead to drive teams to build the next generation of productivity tools that are trustworthy and efficient. I am working in the areas of long-running asynchronous agentic tasks, computer-use coding harness, safety, personalization/memory, alignment, reasoning, and trustworthy-evaluations.

Most recently I was involved in R&D and productionization of several natural language and multimodal solutions for securing Copilot reasoning and enterprise RAG from direct and indirect prompt injections and worked on several cross-organization projects related to AI security. I have also contributed towards the post-training of AI-systems for aligning with human-preferences while ensuring reliable search experiences.

I have a rich experience of delivering high-impact features/products for Fortune 500 companies and end users. I also love prototyping and working on incubation projects, a desire stemming from my past experience of finishing a forward-looking Ph.D. from Carnegie Mellon University in the intersection of deep learning, natural language processing, and renewable energy policies.

For invited talks, conference presentations, and reviewing activities, see Professional Service.

I am looking forward to continue working in fast-paced teams and across multiple areas and disciplines/roles and growing to become an empathetic product leader. Email me at gsh.reshmi@gmail.com to discuss new opportunities. I do not require visa-sponsorship.

Products shipped/Contributed to:

Current: Next Generation Personalization, Memory Orchestration, Long-running Tasks, Asynchronous Tasks, Reducing Over Mitigation, Mechanistic Interpretability

Last year: Security of Agentic Infrastructure, Deep Reasoning, Evaluation Framework, Coding and Artifact Generation Harness

Older: Working on Agents research and applications. Special focus on Safety and Security (Direct Prompt Injections and Cross-Domain Prompt Injections)

[Fall 2023 – Fall 2024] I had been focused on developing state-of-the-art Responsible AI and Trustworthy evaluation mechanisms for LLM and Multimodal model applications. Additionally, in 2023, I contributed to the development and shipped M365Copilot (Business Chat), followed by Azure Prompt Shields in 2024 to mitigate Cross Domain Prompt Injections.

[2021 - Spring 2023] Before joining MSAI, I was selected to be part of a coveted (~0.1% acceptance rate) AI incubation program at Microsoft’s New England Research and Development Center (NERD) (currently under the Office of the CTO, previously under Jaime Teevan’s Office of Applied Research). During this time, I shipped several products, notably:

  1. Developed and implemented anomaly detection methods for SLA in Azure core services
  2. Developed and deployed in production, intelligent commanding features leveraging seq2seq language model to Microsoft Office. Also prototyped a novel loss function that can predict as well as researching user preferences in UX positioning by developing a novel loss function.
  3. Developed probabilistic graphical models to measure time saved in finding new information by knowledge workers, aiding in productivity increases through Viva Topics (see product announcement here!)
  4. Shipped a LLM application and novel evaluation framework for generating rich-text formatting within a client application.

This work led into MSAI, where I was tech leading efforts to architect and integrate first-ever Generative AI capabilities in Microsoft’s Productivity applications (M365 CoPilots, see Satya Nadella’s announcement of these products here).

Education Background: I hold a Ph.D. from Carnegie Mellon University. I have always been passionate about applying machine learning, deep learning, economics to solving socio-technical problems, such as in the intersection of climate change and renewable energy integration.

With over 10+ years of innovating, leading, and strategizing AI solutions for nuanced user problems, I hope to continue building products and tools that can benefit the scientific community, and users equally.

Products/Software Highlights

Expand each year to scan product focus areas, shipped capabilities, and ongoing bets.

2026 Memory and Copilot Personalization
  • Building long-term memory systems that let Copilot retain user context across sessions while preserving privacy and trust boundaries
  • Researching personalization signals that adapt agent behavior to individual users without compromising safety guardrails
  • Exploring memory-grounded reasoning to reduce hallucinations and improve factual consistency in personalized agentic workflows
2025 It’s becoming all about agents
  • Working with alignment issues of facts for a global audience and reducing over-refusal
  • Contributed to the safe release of agentic workflows in M365 Copilots
  • Learn about agents in Copilot
2024 Year 2 of bringing AI into search and productivity
  • Working on novel post-training of AI systems to prevent security breaches
  • Azure Prompt Shields became available for third-party usage
  • Safeguarding automated search workflows from security breaches and prompt injections

Research Highlights

Selected Papers

Selected list of published papers. For the full list, visit Google Scholar. Citation metrics as of August 2026: 477 citations, h-index 10, i10-index 10.