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Senior Manager, Post-Training Research at Scale AI |
I lead a post-training research team at Scale AI, working on post-training data and methods, agentic RL environments, and frontier model evaluations in collaboration with leading AI labs. My research focuses on scalable supervision for long-horizon agents. Previously, I was a Staff Research Scientist at Snap Research, where I led research and production efforts on agentic search, generative recommendation, and personalization. I received my Ph.D. in Computer Science and Engineering from the University of Notre Dame in 2022, advised by Prof. Meng Jiang.
News
Sept. 2026: Our RSI-Bench is calling for task contributions from ML researchers!
June 2026: I've joined Scale AI to work on post-training.
Olds
May 2025: Our hands-on tutorial Training Industry-scale GNNs with GiGL was accepted by KDD 2025. Stay tuned and see you in Toronto!
May 2023: Our tutorial Large-Scale Graph Neural Networks: the Past and New Frontiers was accepted by KDD 2023. Stay tuned and see you in Long Beach!
Nov. 2022: I am thrilled to present our tutorial on Augmentation Methods for Graph Learning at SDM 2023. Stay tuned and see you in Minneapolis!
Oct. 2022: Looking forward to giving a keynote at MLoG Workshop. See you in Orlando!
July 2022: Looking forward to giving a keynote at Mis2-TrueFact Workshop. See you in Washington DC!
Jan. 2022: I am invited to give a talk at ShenLanXueYuan on “Graph Data Augmentation for Graph Machine Learning”.
Honors and Awards
Best Paper Award, ACM CIKM. 2025.
Amazon Post-internship Fellowship, Amazon. 2021.
Snap Research Fellowship, Snap Inc. 2020.
Best Paper Award, DLG-KDD. 2020.
SIGIR Student Travel Grant, ACM CIKM. 2020.
Outstanding Teaching Assistant Honorable Mention, University of Notre Dame. 2019.