Microsoft Research
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Microsoft Research (often abbreviated MSR) is the research division of Microsoft Corporation. Founded in 1991 in Redmond, Washington, it is one of the largest computer science research organizations in the world, with thousands of researchers working across labs in the United States, United Kingdom, China, India, and Canada [1] [2]. The division covers a wide span of fields, including machine learning, systems, programming languages, human-computer interaction, computer vision, quantum computing, and theoretical computer science. Its researchers have authored several of the most influential papers in modern artificial intelligence, including the residual network (ResNet) paper that became one of the most cited works in the history of deep learning, and a 2023 study on GPT-4 titled "Sparks of Artificial General Intelligence" [3] [4].
| Microsoft Research | |
|---|---|
| Type | Corporate research laboratory |
| Founded | 1991 |
| Founders | Bill Gates, Nathan Myhrvold, Rick Rashid |
| Headquarters | Redmond, Washington, United States |
| Parent | Microsoft Corporation |
| Key people | Peter Lee (President), Eric Horvitz (Chief Scientific Officer), Jaime Teevan (Chief Scientist) |
| Website | microsoft.com/en-us/research |
Microsoft Research grew out of a 1991 push by Bill Gates and Microsoft's then chief technology officer Nathan Myhrvold to establish a basic research organization at the company. Myhrvold sent Gates a 21-page memo titled "Microsoft Research Plan" arguing that Microsoft needed a research arm modeled on the great industrial labs of the twentieth century, Bell Labs and Xerox PARC [5] [6]. The timing was unusual. Through the late 1980s and early 1990s, large companies were trimming long-horizon research budgets, and Bell Labs in particular was being broken up. Gates and Myhrvold moved in the opposite direction.
In September 1991, Microsoft hired Rick Rashid to run the new lab. Rashid had been a professor of computer science at Carnegie Mellon University (CMU), where he led the development of the Mach kernel, an influential operating system project that would later underpin macOS and iOS. Rashid was the first head of Microsoft Research and stayed in the role for more than two decades, leading the lab through its expansion from a small Redmond team to a global organization with hundreds of researchers [5] [7]. Under Rashid's tenure, MSR adopted an academic style: papers were published in open conferences, researchers worked closely with universities, and the lab tracked its impact through both peer-reviewed publication and product transfer.
From the start, the lab was given an unusual amount of autonomy by Microsoft's standards. Researchers were expected to identify their own problems, publish openly, and contribute to product groups when ideas became practical. That model produced a steady flow of contributions to Microsoft products: query optimization in SQL Server, Bing's ranking algorithms, the early versions of Cortana, grammar and style features in Office, and the underlying computer vision pipeline of the Kinect sensor for Xbox [8] [9].
MSR runs research labs in multiple cities, with each lab having its own focus areas while collaborating across the network. Redmond remains the headquarters and the largest single lab.
| Lab | Year founded | Location | Notes |
|---|---|---|---|
| Microsoft Research Redmond | 1991 | Redmond, Washington, US | Headquarters; about 350 researchers; founded with the lab itself [1] |
| Microsoft Research Cambridge | July 1997 | Cambridge, United Kingdom | First MSR lab outside the US; founded by Roger Needham [10] |
| Microsoft Research Asia | November 1998 | Beijing, China | Founded by Kai-Fu Lee; long known for computer vision and NLP work; has expanded to Shanghai, Tokyo, Singapore, Hong Kong, and Vancouver [11] [12] |
| Microsoft Research India | January 2005 | Bangalore, India | Founded by P. Anandan; focused initially on emerging-market technology and multilingual systems [13] |
| Microsoft Quantum (Station Q) | 2006 | Santa Barbara, California, US | Founded by Fields-medalist mathematician Michael Freedman; topological quantum computing on UC Santa Barbara campus [14] |
| Microsoft Research New England | July 2008 | Cambridge, Massachusetts, US | Adjacent to MIT; established by Jennifer Chayes [15] |
| Microsoft Research New York City | May 2012 | New York, New York, US | Spun out of the closure of Yahoo Labs East; computational social science and machine learning [1] |
| Microsoft Research Montreal | 2017 | Montreal, Quebec, Canada | Came with the acquisition of Maluuba; deep learning and reinforcement learning for language understanding [16] |
| Microsoft Research Asia-Tokyo | November 2024 | Tokyo, Japan | Newest MSR lab, focused on AI-driven research [1] |
MSR also maintains the Gray Systems Lab, named after database pioneer Jim Gray, in Madison, Wisconsin (founded 2008). Each lab tends to have a distinctive culture. MSR Cambridge is known for programming languages and probabilistic programming, MSR Asia for computer vision and search, MSR New England for theoretical machine learning and economics, MSR New York for online experimentation and reinforcement learning, and MSR Redmond for systems and the broadest cross-section of disciplines [1] [17].
MSR Asia in particular has been at the center of geopolitical attention. In June 2023, the Financial Times reported that Microsoft was working on a "Vancouver Plan" to relocate dozens of senior Chinese AI researchers from Beijing to Canada in response to U.S. export controls and concerns about technology transfer. Microsoft publicly disputed some of the specifics but did move part of the team out of China. As of 2024, MSRA still operates in Beijing while having expanded its presence in Vancouver and other Asia-Pacific cities [12] [18].
MSR's research portfolio covers most of computer science. The largest groupings include:
MSR researchers regularly publish at NeurIPS, ICML, CVPR, SIGGRAPH, STOC, FOCS, SIGCOMM, OSDI, POPL, and PLDI. The lab is one of the most prolific industrial publishers in computer science, and its researchers have won numerous Turing Award (Tony Hoare and Butler Lampson, both formerly at MSR), Fields Medal (Michael Freedman), Godel Prize, and ACM SIGCOMM Test of Time Awards.
MSR has produced or co-produced a number of widely cited results in artificial intelligence.
Kinect (2010). Kinect was the depth-sensing peripheral for Xbox 360, launched in November 2010. The body-tracking pipeline that turned raw depth data into a real-time skeleton was developed by MSR Cambridge researchers, including Jamie Shotton and colleagues. Their algorithm used randomized decision forests trained on a large synthetic dataset. The paper "Real-Time Human Pose Recognition in Parts from Single Depth Images" won the Best Paper award at CVPR 2011 and is one of the most cited industrial computer vision papers of its era [9].
Project Adam (2014). Project Adam was a distributed deep learning training system developed by Trishul Chilimbi, Yutaka Suzue, Johnson Apacible, and Karthik Kalyanaraman at MSR. Presented at OSDI 2014, Adam scaled stochastic gradient descent across thousands of cores and achieved roughly twice the accuracy of comparable systems on ImageNet at much lower cost [21].
ResNet (2015). The single best-known paper to come out of MSR Asia is "Deep Residual Learning for Image Recognition" by Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun, posted to arXiv in December 2015. ResNet introduced residual connections, also called skip connections, which let very deep convolutional neural networks be trained without exploding or vanishing gradients. ResNet-152 won the ILSVRC 2015 ImageNet classification challenge with a top-5 error of 3.57 percent, took first place across five separate ImageNet and COCO tracks, and went on to become one of the most cited papers in the history of computer science with hundreds of thousands of citations [3]. The architecture is foundational to virtually every modern computer vision and Transformer-based model.
DeepSpeed (2020). DeepSpeed is an open-source deep learning optimization library released by Microsoft in February 2020. It includes ZeRO (Zero Redundancy Optimizer), which removes redundant memory copies of optimizer state, gradients, and parameters across data-parallel processes. Together with the ZeRO-Infinity and ZeRO-Offload extensions, DeepSpeed enabled training of language models with hundreds of billions of parameters on commodity GPU clusters and is widely used outside Microsoft, including in many open-source training pipelines [22] [23].
Turing-NLG (February 2020). Turing-NLG was a 17-billion-parameter Transformer language model produced by the Microsoft Project Turing team, trained with DeepSpeed and ZeRO. At the time it was the largest published Transformer language model, with 78 layers, hidden size 4256, and 28 attention heads. Turing-NLG improved state-of-the-art results on benchmarks such as Lambada and WikiText. Less than four months later OpenAI revealed GPT-3 at 175 billion parameters, an order of magnitude larger [24].
Florence (2021) and Florence-2 (2024). Project Florence is a vision foundation model effort at MSR. The original Florence model, described in a 2021 paper, expanded vision representations across coarse-to-fine and image-to-video tasks. Florence-2, released in 2024, is a unified prompt-based vision model that handles captioning, detection, segmentation, and visual question answering in a single architecture, trained on the FLD-5B dataset of 5.4 billion annotations on 126 million images [25] [26].
Phi family of small language models (2023 to present). The Phi project, led for several years by Sebastien Bubeck and colleagues, set out to test how much capability could be packed into very small models trained on carefully curated, often synthetic data. Phi-1 (1.3 billion parameters, 2023) targeted code, Phi-1.5 and Phi-2 (2.7 billion parameters, late 2023) extended the approach to general language. Phi-3 (released April 2024) and Phi-3.5 (August 2024) ranged from 3.8 to 14 billion parameters and were positioned as on-device alternatives to much larger frontier models. Phi-4, released in December 2024 with 14 billion parameters, focused on advanced reasoning [27] [28] [29].
"Sparks of AGI" paper (March 2023). "Sparks of Artificial General Intelligence: Early experiments with GPT-4," posted to arXiv on March 22, 2023, was authored by Sebastien Bubeck and 13 other MSR researchers including Eric Horvitz, Peter Lee, Ece Kamar, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, Marco Tulio Ribeiro, and Yi Zhang. The paper documented Microsoft's months of pre-release access to an early version of GPT-4 and argued that the model showed "sparks" of general intelligence across mathematics, coding, vision, medicine, law, and psychology. The paper attracted both wide attention and methodological criticism, and it shaped much of the public conversation about frontier model capabilities in 2023 [4] [30].
RankNet, LambdaRank, LambdaMART. The learning-to-rank algorithms used in Bing for web ranking grew out of a long collaboration between MSR's Chris Burges and the Bing relevance team starting in 2004. RankNet (ICML 2005, later a Test of Time award winner) was followed by LambdaRank and LambdaMART, the latter winning the 2010 Yahoo Learning to Rank Challenge and remaining a workhorse of search ranking [31].
ONNX (2017). ONNX, the Open Neural Network Exchange, was announced jointly by Microsoft and Facebook in September 2017 as an open format for representing neural networks across frameworks. It became a de facto standard for model interoperability and is now stewarded under the Linux Foundation [32].
MSR's leadership has rotated through a small group of senior figures over the decades.
| Person | Role | Background |
|---|---|---|
| Bill Gates | Co-founder of MSR; Technology Adviser to Microsoft CEO since 2014 | Microsoft co-founder; stepped down from the board in 2020 but continues as adviser [33] |
| Nathan Myhrvold | Co-founder of MSR; former Chief Technology Officer | Wrote the 1991 memo proposing MSR; left Microsoft in 1999 to found Intellectual Ventures [6] |
| Rick Rashid | Founding head of MSR, 1991 to 2013 | Former CMU professor; Mach kernel architect [5] |
| Peter Lee | President of Microsoft Research (current) | PhD Michigan; former CMU department head; former DARPA director; runs MSR worldwide and Microsoft Health Futures [34] |
| Eric Horvitz | Chief Scientific Officer of Microsoft | MD, PhD Stanford; previously Director of MSR; AAAI fellow; founder of the One Hundred Year Study on AI at Stanford [35] |
| Jaime Teevan | Chief Scientist of Microsoft | PhD MIT; led the integration of GPT-4 into Microsoft 365 Copilot starting in 2022; ACM Fellow [36] |
| Jeannette Wing | Corporate VP of MSR, 2013 to 2017 | CMU professor; coined "computational thinking"; later EVP for Research at Columbia [37] |
| Kai-Fu Lee | Founding director of MSR Asia, 1998 to 2000 | PhD CMU; later President of Google China and founder of Sinovation Ventures [11] |
| Roger Needham | Founding director of MSR Cambridge, 1997 to 2003 | Cambridge computer lab head; pioneered Needham-Schroeder protocol; died in 2003 [10] |
| Michael Freedman | Founding director of Station Q, 2006 to 2024 (retired) | Fields Medal winner; led topological quantum computing effort at UCSB [14] |
| Mustafa Suleyman | CEO of Microsoft AI (since March 2024) | Co-founder of DeepMind and Inflection AI; leads consumer AI products including Copilot, Bing, and Edge [38] |
| Sebastien Bubeck | Distinguished Scientist, MSR (2014 to 2024) | Theoretical machine learning; lead author of "Sparks of AGI"; led Phi small-model effort; left for OpenAI in October 2024 [39] |
The lab has also drawn well-known researchers across different periods: Susan Dumais (information retrieval, now Managing Director of MSR New England, NYC, and Montreal), Donald Kossmann (databases, leading MSR Redmond), Christopher Bishop (machine learning author and Director of MSR AI for Science), Yoshua Bengio (advisor through the Maluuba acquisition), Don Syme (creator of F#), and Anders Hejlsberg (creator of TypeScript and C#, working in adjacent Microsoft groups) [16] [19] [20].
MSR's role in Microsoft's overall AI strategy shifted dramatically with the rise of OpenAI. In July 2019, Microsoft announced a $1 billion investment in OpenAI and made Azure its exclusive cloud provider. In January 2023, Microsoft confirmed "the third phase" of the partnership, a multi-year, multi-billion-dollar investment widely reported at $10 billion, on top of additional rounds in 2021 and 2022. Total Microsoft commitments to OpenAI exceed $13 billion by most accounts [40] [41]. The deal gave Microsoft access to OpenAI's frontier models and the right to integrate them into products such as Bing, GitHub Copilot, Microsoft 365 Copilot, and Windows.
For MSR, this raised a strategic question that the lab has had to navigate publicly: how should an in-house research organization position itself when the dominant AI partner sits outside the company. Peter Lee and others have argued that MSR retains an essential role in producing science that informs how Microsoft uses OpenAI models, in studying their behavior, and in pursuing directions OpenAI does not work on, including small models, safety research, scientific computing, and quantum.
In March 2024, Microsoft announced a separate Microsoft AI division, distinct from MSR, led by Mustafa Suleyman as Executive Vice President and CEO of Microsoft AI. Suleyman, a co-founder of DeepMind and of Inflection AI, brought along Inflection's co-founder Karen Simonyan as Chief Scientist of Microsoft AI, plus much of the Inflection technical team in what was widely described as a quasi-acquihire. The new unit took over Copilot, Bing, Edge, and the consumer GenAI team [38] [42]. MSR remained organizationally separate, though the two divisions cooperate. The split increased pressure on MSR to focus on long-horizon research while Microsoft AI handled consumer-facing AI productization.
The transition came with departures. Sebastien Bubeck, who had led much of MSR's small-model and theoretical-AI work, left for OpenAI in October 2024 [39]. Microsoft's broader cost-cutting cycles in 2024 and 2025 trimmed engineering and operations groups elsewhere in the company, though Microsoft Research itself was largely insulated from the deepest cuts.
MSR has long had a publication culture closer to a university than a typical product organization. Researchers are encouraged to publish in top conferences and journals, and many work part-time as adjunct or visiting faculty at universities including Cambridge, MIT, and Carnegie Mellon. The lab maintains a public list of publications, and most papers are available without paywall on the MSR site [2].
MSR has also been a steady contributor to open source. Notable open-source releases that grew out of MSR or related Microsoft research groups include:
Research from MSR has consistently found its way into Microsoft products. The SQL Server query optimizer relies on cost-based optimization techniques drawn from database research at MSR. Bing's ranking is driven by descendants of LambdaMART. Office's grammar and proofing tools, the Visual Studio IntelliCode code completion service, the Hololens spatial mapping pipeline, and many features of Microsoft 365 Copilot all have direct lineage in MSR work [8] [31] [42].