Weizhu Chen
Technical Fellow and CVP at Microsoft AI; senior author of LoRA, DeBERTa and Samba
- Technical Fellow and Corporate Vice President, leading a modeling team, Microsoft AI1
Weizhu Chen is a Technical Fellow and Corporate Vice President at Microsoft AI, where Chen leads a modeling team working on large-scale model training with a recent focus on agentic and long-horizon reinforcement learning and synthetic data. Chen's Microsoft Research page lists the team's published work including LoRA, DeBERTa, Phi and Rho-1. Chen is senior author of DeBERTa (2020), LoRA (2021) and Samba (2024), and a co-author of the 2025 SambaY paper that describes the architecture of Phi-4-mini-flash-reasoning.12345
Role
Chen is a Technical Fellow and Corporate Vice President at Microsoft AI and leads a modeling team that trains large-scale models, including OpenAI and Microsoft AI models according to Chen's Microsoft Research page, with recent work on agentic and long-horizon reinforcement learning and synthetic data generation.1
Research
Chen is the senior author of DeBERTa (2020), a BERT variant with disentangled attention, and LoRA (2021), a method for adapting large language models with low-rank updates. Chen is also listed among the authors of the Phi-4-Mini technical report (2025).237
With Liliang Ren as first author, Chen co-authored Samba (2024), a hybrid state-space language model, and the 2025 SambaY paper, whose decoder-hybrid-decoder architecture is used in Phi-4-mini-flash-reasoning.456
Work
Phi-4-mini-flash-reasoningOpen weights
Co-author of the SambaY decoder-hybrid-decoder paper, whose architecture Phi-4-mini-flash-reasoning adopts.56
LoRA (external site: arxiv.org)Published research
Senior author of the LoRA paper, which adapts large language models by training low-rank update matrices while freezing the pretrained weights.3
DeBERTa (external site: arxiv.org)Published research
Senior author of the DeBERTa paper on decoding-enhanced BERT with disentangled attention.2
Career timeline
Jun 2020
Senior author of the DeBERTa paper on disentangled attention.2
Jun 2021
Senior author of the LoRA paper on low-rank adaptation of large language models.3
Jun 2024
Senior author of the Samba paper on hybrid state-space language models.4
Mar 2025
Co-authored the Phi-4-Mini technical report.7
Jul 2025
Co-authored the SambaY paper behind Phi-4-mini-flash-reasoning.5
Related people
More sourced profiles at the same organization, in the same field, or from the same school.
- Adam FourneyAlso at Microsoft Research
- Edward BeechingLanguage models
- Andreas C. MüllerAlso at Microsoft
- Jakub PachockiLanguage models
- Bin XiaoAlso at Microsoft
- Johannes HagemannTraining systems
- Charles LamannaAlso at Microsoft
- Mika SenghaasReinforcement learning
- Christopher BishopAlso at Microsoft Research
- Susan ZhangTraining systems
- Eric HorvitzAlso at Microsoft
- Akshita BhagiaLanguage models
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