Qi He
VP of Applied Science at Microsoft, IEEE Fellow, ACM Distinguished Member
- Role
- Vice President of Applied Science at Microsoft
- Location
- Mountain View, CA, US
- LinkedIn followers
- 500 followers
About Qi He
Qi He, as Microsoft\'s VP of Applied Science, is working at the core of Microsoft’s GenAI stack—adapting and extending frontier models, scaling post-training across both first-party and open-source ecosystems, and advancing applications like GitHub Copilot and beyond.Qi is a technical leader in AI and its business applications, with a track record of 20 years of experience leading and executing large complex AI projects, as well as innovating and constructing necessary AI technologies to achieve business impacts. Qi is a seasoned leader who has held senior positions at multiple tech companies including Microsoft, Amazon, Nextdoor and LinkedIn. He serves as a Steering Committee member of ACM CIKM and an advisory board member of Neurocomputing Journal. He held many editorial and conference chair positions, including Associate Editor of TKDE and Neurocomputing Journal, General Chair of CIKM 2013, PC Chair of CIKM 2019, Industry Chair of Web 2024 and PC Chair of SIGKDD 20••••26 ADS Track, while also served as a (senior) program committee member of SIGKDD, SIGIR, CIKM, and WSDM for over a decade. Qi has published over 70 papers and patents with over citations to date. He received the 2008 ACM SIGKDD Best Application Paper Award and the 2020 ACM WSDM 10-year Test of Time Award. Qi is an Fellow, ACM Distinguished Member and was featured as the People of ACM in February 2021
Experience
Vice President of Applied Science
Jul 2025 — Present
Work at the core of Microsoft’s LLM stack — adapting and extending frontier models, scaling post-training across 1P and OSS, and pushing forward applications like GitHub Copilot and beyond.
Education
Penn State University
Postdoctoral Research Fellow, Computer Science
2008 — 2010
Nanyang Technological University Singapore
Doctor of Philosophy (Ph.D.), Computer Science
2005 — 2008
Skills
- Analytics
- Computer Science
- Analysis
- Statistical Modeling
- Research
- Information Extraction
- Machine Learning
- Data Mining
- Information Retrieval
- Social Networking
- Recommender Systems
- Hadoop
- Statistics
- Natural Language Processing
- Text Mining
- Algorithms
- Big Data
- Data Analysis
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