I am a research scientist in the Ads Ranking & Foundational AI team at Meta, where I leverage machine learning to tackle critical business challenges. My primary focus has been on Recommendation Systems, exploring various topics within this domain.
Work Experience
- Meta: Research Scientist, Ads Ranking (August 2018 - Present)
- Facebook: Intern, Search Ranking (May 2017 - August 2017)
- Bosch Research and Technology Center: Intern, Natural Language Processing Group (May 2016 - August 2016)
- Qatar Computing Research Institute: Intern, Data Analytics Group (June 2015 - August 2015)
Education
Ph.D. in Information Sciences and Technology, 2013-2018
Pennsylvania State University
Advisor: C. Lee Giles
Pennsylvania State University
Advisor: C. Lee Giles
B.Eng. in Computer Science, 2009-2013
Tsinghua University
Tsinghua University
News
- [2024/11] The Meta Engineering blog highlighted our work on Sequence Learning, a paradigm shift in personalized ads recommendations. [blog]
- [2024/05] We published Scaling User Modeling (SUM), a system that generates large-scale user representations for Meta ads personalization. SUM serves billions of Meta users and has been launched in hundreds of production models in Meta ads ranking. [WWW'24]
Selected Publications [Full List]
- [WWW’24] Scaling User Modeling: Large-scale Online User Representations for Ads Personalization in Meta
- [EDM’19] Active Learning of Strict Partial Orders: A Case Study on Concept Prerequisite Relations
- [AAAI’17] Recovering Concept Prerequisite Relations from University Course Dependencies
- [EMNLP’15] Measuring Prerequisite Relations Among Concepts