Jim Kleewein
Jim Kleewein is a Technical Fellow in Microsoft 365 who helps steer Microsoft Research groups working on efficient AI, agentic systems and AIOps. In 2021, he gave a Microsoft Research Summit keynote on privacy-preserving machine learning and coauthored a post on Microsoft's PPML initiative, which protects customer data when training large-capacity language models. His work on cloud reliability and efficiency includes a 2023 article on using GPT-3.x models to diagnose production incidents and the 2024 Workload Intelligence paper. Speaking for Microsoft 365, he made the case for in-chip microfluidic cooling in 2025 and said in October 2026 that parts of Microsoft 365 Copilot should speed up on the Maia 300 chip.
- Now at
- Microsoft Research
- Links
Timeline
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May 2021
A CloudIntelligence 2021 panel
In May 2021, he joins a panel on how to speed up cloud intelligence collaboration between academia and industry at the CloudIntelligence 2021 workshop, held alongside ICSE 2021.
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October 2021
Microsoft Research Summit keynote
At the Microsoft Research Summit in October 2021, he gives the keynote "Unlocking exabytes of training data through privacy preserving machine learning" on why private data is seldom used to train public models. He also joins the summit's Cloud Intelligence/AIOps panel as a Technical Fellow in Microsoft 365 and gives its closing remarks.
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November 2021
The PPML initiative
In November 2021, he coauthors a Microsoft Research blog post on the Privacy Preserving Machine Learning (PPML) initiative. Microsoft Research and Microsoft product teams run the initiative to protect the confidentiality and privacy of customer data when training large-capacity language models.
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April 2023
LLMs for production incidents
In April 2023, he coauthors "Towards Highly Reliable Services with AIOps", which describes Microsoft 365 research that uses GPT-3.x models to generate root causes and mitigation steps for production incidents. The study covers more than 40,000 incidents.
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April 2024
The Workload Intelligence framework
He coauthors "Workload Intelligence: Punching Holes Through the Cloud Abstraction", submitted to arXiv in April 2024 with Ricardo Bianchini, Rodrigo Fonseca and others. The paper proposes two-way communication between cloud workloads and the cloud platform and reports that it can cut prices to customers by 48.8% on average.
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September 2025
Microfluidic chip cooling
In September 2025, as technical fellow for Microsoft 365 Core Management, he explains the value of Microsoft's in-chip microfluidic cooling, which removes heat up to three times better than cold plates in lab-scale tests. He says the method would let Microsoft overclock servers during spiky workloads such as Teams calls.
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October 2026
Copilot on Maia 300
Microsoft unveils its third-generation Maia 300 AI accelerator in October 2026, and he says parts of Microsoft 365 Copilot should speed up with the chip.
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As of October 2026
Technical Fellow in Microsoft 365
He is a Technical Fellow in Microsoft 365 and sits in the leadership and strategic steering of Microsoft Research's Efficient AI, Agentic Innovation and AIOps groups. The Efficient AI group works on AI efficiency from GPU kernels to context engineering to power Copilot-scale intelligence. He is also an executive sponsor of the Privacy Preserving Machine Learning Innovation group.
Career
- NowMicrosoftTechnical Fellow
- NowMicrosoft ResearchLeadership and Strategic Steering
Sources and credits
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- Jim Kleewein - CloudIntelligence 2021
- Keynote: Unlocking exabytes of training data through privacy preserving machine learning - Microsoft Research
- Panel: Cloud Intelligence/AIOps across academia and industry - Microsoft Research
- Privacy Preserving Machine Learning: Maintaining confidentiality and preserving trust - Microsoft Research
- Towards Highly Reliable Services with AIOps - Microsoft Research
- [2404.19143] Workload Intelligence: Punching Holes Through the Cloud Abstraction
- AI chips are getting hotter. A microfluidics breakthrough goes straight to the silicon to cool up to three times better.
- Microsoft will mainly use its Maia chips for AI inference
- Efficient AI - Microsoft Research: People
- Agentic Innovation - Microsoft Research: People
- AIOps - Microsoft Research: People
- Privacy Preserving Machine Learning Innovation - Microsoft Research: People


