About Rajkiran Panuganti

AI engineer, researcher, and advisor · Previously at Microsoft and Google · PhD, Ohio State · B.Tech, IIT Bombay

AI engineer, researcher, and advisor. Previously Principal Applied Scientist Manager at Microsoft.

Rajkiran Panuganti is an AI engineer, researcher, and advisor with two decades of experience building large-scale AI systems. He spent 14 years at Microsoft, where he worked on Microsoft 365 Copilot Chat, the AI assistant that helps enterprise users retrieve information across their files, emails, and chats. His earlier work at Microsoft included Bing's web search ranking, Cortana's natural language understanding stack, and the experimentation platform that became Azure Machine Learning.

His Bing work included Sort Rank, the algorithm that determined the relative importance of every webpage in the Bing index, and the Names Ranker that powered web search ranking for queries containing person entities. He holds patents from his time at Microsoft, including work on search refiner generation. Before Microsoft, he was a software engineer at Google in the platform infrastructure team.

Today, Rajkiran is building a new AI startup in stealth. Alongside that, he advises early-stage AI startups including Codemod, Nelumbium Capital, and AppAxon, helping them navigate the practical and architectural challenges of building production Generative AI systems. He also conducts independent research on mechanistic interpretability. His paper CircuitProbe (arXiv, 2026) introduces a method for detecting reasoning circuits inside transformer models using activation statistics, replacing brute-force layer search with a process roughly 1000x faster.

Alongside his research and advisory work, Rajkiran writes a weekly deep-dive newsletter analyzing what's actually happening at the frontier of AI: model releases, agent infrastructure, research trends, and the gap between what gets demoed and what actually ships in production. The same column runs on LinkedIn as My Thoughts on LLMs.

Rajkiran holds a PhD in Computer Science from The Ohio State University, where his research focused on enabling high-performance computing inside high-productivity languages like MATLAB. He earned his bachelor's in Electronics and Communications Engineering from the Indian Institute of Technology Bombay, where his thesis on computer vision was advised by Dr. Subhasis Chaudhuri.

He writes for engineers, researchers, and builders who want substance over hype.

Currently

  • Founder · Stealth Startup
    Oct 2025 — Present

    Building a new AI startup. More to share soon.

  • Advisor · Codemod
    Jan 2024 — Present

    Advising on AI strategy. Codemod builds developer tooling that automates undifferentiated work across massive codebases, including those produced by AI.

  • Advisor · AppAxon
    Jan 2024 — Present

    Advising on Generative AI applications in cybersecurity.

  • Strategic Advisor · Nelumbium Capital
    Mar 2023 — Present

    Advising on the AI engine that powers their systemic-risk modeling. Nelumbium applies complexity economics to financial systems, with the premise that shocks to the system are not exogenous.

Previously

  • Applied Science · Microsoft 365 Copilot Chat · Microsoft
    2009 — 2023

    14 years at Microsoft across Bing, Cortana, Microsoft 365 Search, and Microsoft 365 Copilot Chat (formerly BizChat). Worked on LLM behavior, retrieval-augmented generation, evaluation metrics, privacy, and Responsible AI for the enterprise Copilot experience.

    • Microsoft 365 Copilot Chat: deep work on LLM behavior, RAG, metric design, privacy and Responsible AI for the enterprise Copilot.
    • Cortana: NLP, intent and entity extraction, and the orchestration engine that later evolved into the orchestration layer powering BizChat.
    • Bing Sort Rank: variant of PageRank that determined the relative importance of pages in the Bing index. Saved hundreds of millions in serving costs.
    • Bing Names Ranker: built a person knowledge graph from the open web to power people-related search queries and disambiguation.
    • Azure ML: built the experimentation workflow system from scratch, which matured into part of Azure Machine Learning.
    • Two patents granted, including search refiner generation for applications.
  • Software Engineer · Google
    2007 — 2008

    Platform infrastructure. Performance tuning of widely used internal tools through scalable architecture redesigns.

  • Research Assistant · Ohio Supercomputer Center
    Jul 2004 — Dec 2007

    Research on high-productivity languages for parallel computing.

  • Research Scientist (Internship) · Hewlett-Packard
    Jun 2006 — Sep 2006

    Developed High-Performance MATLAB for parallel computing.

  • Engineering Intern · Sun Microsystems
    May 2002 — Jun 2002

    Built a bug tracking system.

Education

  • PhD, Computer Science · The Ohio State University
    2003 — 2008

    Specialized in enabling high-performance frameworks for machine learning workloads, including distributed systems, parallel computing, and NVIDIA CUDA. Thesis: enabling high-performance computing in high-productivity languages like MATLAB.

  • Bachelor of Technology, Electronics and Communications Engineering · Indian Institute of Technology Bombay
    1999 — 2003

    Thesis in computer vision, advised by Dr. Subhasis Chaudhuri. First introduction to machine learning.

Research

See all research →

Elsewhere