Microsoft Research Lab – Redmond
News & features
Vega: Zero-knowledge proofs for digital identity in the age of AI
| Srinath Setty
Vega turns a full credential into a single proof, sharing only what is needed and nothing more, with performance that works in real apps.
Further Notes on Our Recent Research on AI Delegation and Long-Horizon Reliability
| Philippe Laban, Tobias Schnabel, and Jennifer Neville
Our recent paper, “LLMs Corrupt Your Documents When You Delegate”, has generated discussion about the reliability of AI systems in delegated workflows. We appreciate the interest in this work and want to clarify several important points about what the paper…
mimalloc: A new, high-performance, scalable memory allocator for the modern era
| Daan Leijen
mimalloc is an open-source, modern, scalable memory allocator that is a drop-in replacement for malloc and free. It is relatively small (~12K lines), with clear internal data structures, and is easy to build and integrate into other projects. It provides…
GridSFM: A new, small foundation model for the electric grid
| Weiwei Yang, Andrea Britto Mattos Lima, Thiago Vallin Spina, Spencer Fowers, and Baosen Zhang
Introducing GridSFM, a small foundation model that can predict AC optimal power flow in milliseconds, boosting efficiency and unlocking cost savings. Learn how GridSFM gives grid operators direct visibility into congestion, stability, and system health.
Building realistic electric transmission grid dataset at scale: a pipeline from open dataset
| Andrea Britto Mattos Lima, Thiago Vallin Spina, Weiwei Yang, Spencer Fowers, Ruslan Nagimov, and Baosen Zhang
Microsoft Research is excited to release an open dataset of approximate transmission topology of the U.S. power grid derived from publicly available data. The ability to study transmission-level power grid behavior is essential for modern power systems research. Analyses of…
Microsoft at NSDI 2026: Advances in large-scale networked systems
| Sujata Banerjee
Microsoft researchers share advances in building and operating large-scale distributed systems, spanning datacenters, networking, and the growing intersection with AI during NSDI ’26.
AutoAdapt: Automated domain adaptation for large language models
| Sidharth Sinha, Anson Bastos, Xuchao Zhang, Akshay Nambi, Rujia Wang, and Chetan Bansal
Deploying large language models (LLMs) in real-world, high-stakes settings is harder than it should be. In high-stakes settings like law, medicine, and cloud incident response, performance and reliability can quickly break down because adapting models to domain-specific requirements is a…
New Future of Work: AI is driving rapid change, uneven benefits
| Jaime Teevan, Sonia Jaffe, Rebecca Janssen, Nancy Baym, Siân Lindley, Bahar Sarrafzadeh, Brent Hecht, Jenna Butler, Jake Hofman, and Sean Rintel
For the past five years, the New Future of Work report has captured how work is changing. This year, the shift feels especially sharp. Previous editions have focused on technology’s role in increasing productivity by automating tasks, accelerating communication, and…
Ideas: Steering AI toward the work future we want
| Jaime Teevan, Jenna Butler, Jake Hofman, and Rebecca Janssen
Microsoft Chief Scientist Jaime Teevan and researchers Jenna Butler, Jake Hofman, and Rebecca Janssen unpack the New Future of Work Report 2025 and explore the ideal AI-driven working world. Plus, is AI a tool or a collaborator? And why the answer matters.