Yadong Lu
Also known as Adam Lu
Yadong Lu is a principal researcher at Microsoft Research whose work spans synthetic training data and agents that operate through visual interfaces, Windows, and the web. In 2018, while pursuing a statistics PhD at UC Irvine, he coauthored an award-winning code-clone detection paper; in 2024, he coauthored AgentInstruct, Windows Agent Arena, and OmniParser. His later projects scaled multimodal web-agent trajectories, gave web agents a terminal to explore sites through code, and built FaraGen1.5’s data pipeline from environments, solvers, and verifiers. As of October 2026, he works in Redmond on computer-use agents and efficient training methods for large vision-language models.
- Now at
- Microsoft Research
- Works
- 17
- Citations
- 67
- h-index
- 4
Publication numbers from OpenAlex, as of 22 October 2026.
Timeline
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2018
Oreo wins a paper award
In 2018, while a statistics PhD student at UC Irvine advised by Pierre Baldi, he coauthors “Oreo: Detection of Clones in the Twilight Zone,” which receives the ESEC/FSE Distinguished Paper Award. The detector combines machine learning, information retrieval, and software metrics to find difficult code clones.
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July 2024
AgentInstruct for post-training
In July 2024, he coauthors AgentInstruct, an agentic framework for synthetic language-model post-training. It creates 25 million prompt-response pairs for teaching language models through instruction tuning.
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September 2024
Windows Agent Arena
In September 2024, he coauthors Windows Agent Arena, a reproducible, open-source Windows benchmark with 150+ tasks that test agent planning, screen understanding, and tool use.
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October 2024
OmniParser for visual agents
In October 2024, he coauthors OmniParser, a compact screen parser that turns UI screenshots into structured elements. Paired with GPT-4V, it improves how agents ground actions to interface regions.
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February 2025
Explorer web trajectories
In February 2025, he coauthors Explorer, a method for synthesizing multimodal web-agent data. Its dataset includes over 94,000 successful trajectories across 49,000 unique URLs.
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May 2026
Webwright terminal harness
In May 2026, he coauthors Webwright, a web-agent harness that gives a model a terminal to spawn browser sessions and explore websites through code.
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June 2026
FaraGen1.5 data pipeline
In June 2026, he coauthors Fara-1.5, which introduces FaraGen1.5, a scalable data pipeline for computer-use agents built from environments, solvers, and verifiers.
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As of October 2026
Principal researcher at Microsoft
As of October 2026, he is a principal researcher at Microsoft Research in Redmond, working on computer-use agents and efficient pre/post-training methods for large vision-language models.
Career
- NowMicrosoft ResearchPrincipal researcher
- 2008–2010China Aerospace Science and Technology Corporation
Education
- University of California, IrvinePhD student in statistics
Sources and credits
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- Multidepartmental Collaboration on Detecting Code Clones Leads to Distinguished Paper Award
- AgentInstruct: Toward Generative Teaching with Agentic Flows
- Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale
- Windows Agent Arena
- OmniParser for pure vision-based GUI agent
- Explorer: Scaling Exploration-driven Web Trajectory Synthesis for Multimodal Web Agents
- Webwright: A Terminal Is All You Need For Web Agents
- Fara-1.5: Scalable Learning Environments for Computer Use Agents
- Yadong Lu at Microsoft Research
- Yadong (Adam) Lu