Howdy!
I'm a Senior Applied Scientist at Amazon Search, where I lead the development of scalable and cost-efficient LLM-powered search & recommendation systems. I received my Ph.D. in Computer Science from Texas A&M University, and my B.S. in Statistics from the School of the Gifted Young at the University of Science and Technology of China. My research spans efficient LLM systems, reward modeling, and machine learning foundations. I serve as Area Chair at Language and Molecules @ ACL and Scaling Environments for Agents @ NeurIPS, and on the program committees of multiple top-tier conferences.
Research Interests
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LLMs & Alignment: Post-Training, Reward Modeling, Evolving Agents
Search & Recommendation: LLM-based Recommender Systems, Retrieval-Augmented Generation, Multi-Modality
Foundation Models: Self-Supervised Learning, Graph Neural Networks, Model Explainability
AI4Science: Geometric Deep Learning, Bioinformatics, Biomedical Imaging
Selected Publications
* Equally contributed.The World Won't Stay Still: Programmable Evolution for Agent Benchmarks.
Guangrui Li, Yaochen Xie, Yi Liu, Ziwei Dong, Xingyuan Pan, Tianqi Zheng, Jason Choi, Michael J. Morais, Binit Jha, Shaunak Mishra, Bingrou Zhou, Chen Luo, Monica Xiao Cheng, Dawn Song
Preprint, 2026
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.
Xuan Zhang*, Limei Wang*, Jacob Helwig*, Youzhi Luo*, Cong Fu*, Yaochen Xie*, ... (47 more), Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi Jaakkola, Connor W Coley, Xiaoning Qian, Xiaofeng Qian, Tess Smidt, Shuiwang Ji
Foundations and Trends® in Machine Learning 18 (4), 385-849, 2025
Genetic InfoMax: Exploring Mutual Information Maximization in High-Dimensional Imaging Genetics Studies.
Yaochen Xie, Yuchao Lin, Ziqian Xie, Sheikh Muhammad Saiful Islam, Degui Zhi, Shuiwang Ji
Transactions on Machine Learning Research (TMLR), 2024
Task-Agnostic Graph Explanations.
Yaochen Xie, Sumeet Katariya, Xianfeng Tang, Edward Huang, Nikhil Rao, Karthik Subbian, Shuiwang Ji
The 36th Annual Conference on Neural Information Processing Systems (NeurIPS), 2022
Self-Supervised Representation Learning via Latent Graph Prediction.
Yaochen Xie*, Zhao Xu*, and Shuiwang Ji
International Conference on Machine Learning (ICML), 24460-24477, 2022.
Self-supervised Learning of Graph Neural Networks: A Unified Review.
Yaochen Xie, Zhao Xu, Jingtun Zhang, Zhengyang Wang, and Shuiwang Ji
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
Tutorial
Services
Area Chair
Language and Molecules @ Annual Meeting of the Association for Computational Linguistics (ACL) 2024
Scaling Environments for Agents @ Annual Conference on Neural Information Processing System (NeurIPS) 2025
Program Committee Member
Annual Conference on Neural Information Processing System (NeurIPS) 2021-2023
International Conference on Machine Learning (ICML)2022-2024
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)2021-2022
International Conference on Learning Representation (ICLR)2022-2023
Journal Reviewer
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Transactions on Machine Learning Research (TMLR)
Nature Communications
IEEE Transactions on Image Processing (TIP)
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
Data Mining and Knowledge Discovery (DAMI)
Miscellaneous
+ Meet our new family member Sesame, a bernedoodle born on 7/10/2023. Pup training overfits easily!
+ I love perfomance driving, and am interested in auto engineering&tuning. My favorite drive is the Local 2.0, WA.