Biography
Hey, my name is Chen Luo, a Sr. Applied Scientist at Amazon Search (previously known as A9). I obtained my Ph.D. from Rice, working with Anshumali Shrivastava. Before Rice, I was a master student in Key Laboratory of Symbolic Computation and Knowledge Engineering, Jilin University. I recieved my B.S degree from the Department of Computer Science,
Jilin University.
I love traveling, adventuring, having fun. I love music, love saying 'Yes!'. Above all things, I love being kind. I try to live with kindness and integrity, go with the flow, and make a positive impact wherever I can — learning, growing, and hopefully inspiring others along the way. I enjoy coding as well as reading research papers. Even though graduated from school, I still wonder if I am a scientist, an engineer or just a student. :-)
Research
I do research for fun and my interests change more frequently than Houston weather. In short, I'm mainly focuses on solving well-known problems with new algorithms that are suitable for use on large amounts of data.
- Jiaxin Bai, Zhaobo Wang, Junfei Cheng, Dan Yu, Zerui Huang, Weiqi Wang, Xin Liu, Chen Luo, Yanming Zhu, Bo Li, Yangqiu Song
"Intention Knowledge Graph Construction for User Intention Relation Modeling" In: The 19th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2026), Rabat, Morocco, March 24–29, 2026
- Minhua Lin, Enyan Dai, Hui Liu, Xianfeng Tang, Yuliang Yan, Zhenwei Dai, Jingying Zeng, Zhiwei Zhang, Fali Wang, Hongcheng Gao, Chen Luo, Xiang Zhang, Qi He, Suhang Wang
"How Far Are LLMs from Professional Poker Players? Revisiting Game-Theoretic Reasoning with Agentic Tool Use" In: The International Conference on Learning Representations (ICLR 2026)
- Chen Luo, Dimitri Papadimitriou, Hariharan Muralidharan, Dhineshkumar Ramasubbu, Aakash Kolekar, Wenju Xu, Cong Xu, Anirudh Srinivasan, Mukesh Jain, Qi He
"Language Model Alignment for Conversational Shopping at Amazon" In: The 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2025), Padua, Italy, July 13–18, 2025
- Weiqi Wang, Limeng Cui, Xin Liu, Sreyashi Nag, Wenju Xu, Chen Luo, Sheikh Muhammad Sarwar, Yang Li, Hansu Gu, Hui Liu, Changlong Yu, Jiaxin Bai, Yifan Gao, Haiyang Zhang, Qi He, Shuiwang Ji, Yangqiu Song
"EcomScriptBench: A Multi-task Benchmark for E-commerce Script Planning via Step-wise Intention-Driven Product Association" In: The 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), Vienna, Austria, July 27–August 1, 2025
- Jiaxin Bai, Chen Luo, Zheng Li, Qingyu Yin, Yangqiu Song
"Understanding Inter-Session Intentions via Complex Logical Reasoning" In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . (KDD'24), Barcelona, Spain, Aug, 2024
- Hansi Zeng*, Chen Luo, Bowen Jin, Sheikh Muhammad Sarwar, Tianxin Wei, Hamed Zamani
"Scalable and Effective Generative Information Retrieval" In: Proceedings of the Web Conference, 2024. (WWW'24), Singapore, May, 2024
→ View all publications
Invited Talks
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From Search to Conversational Shopping with Generative AI [Keynote]
Generative AI in E-Commerce Workshop, ACM Conference on Recommender Systems (RecSys 2025), Prague, Czech Republic, Sep 2025
[Workshop Page]
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Generative AI for Search and Interaction
AI Seminar Series, Department of Computer Science, Rice University, Houston, TX, Oct 2025
[Event Page]
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Language Model Alignment for Conversational Shopping at Amazon
The 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2025), Padua, Italy, Jul 2025
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Next-Generation Shopping Experience [Guest Lecture]
COMP 480/580: Probabilistic Algorithms and Data Structures, Rice University, Houston, TX, 2024
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Practical Machine Learning on Large-Scale Systems and Search Engines [Guest Lecture]
Department of Computer Science, George Mason University, Fairfax, VA, Nov 2023
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Industrial Machine Learning
US ATLAS Machine Learning Training, Lawrence Berkeley National Lab, Berkeley, CA, Jul 2023
[Event Page]
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Scalable Machine Learning for Product Search [Keynote]
ROADS to Mega-AI Models Workshop, MLSys 2023, Miami, FL, Jun 2023
[Workshop Page]
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Machine Learning for Product Search [Guest Lecture]
Department of Computer Science, Georgia Institute of Technology, Atlanta, GA, Mar 2023
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Towards Scalable, Unbiased, and Interactive Product Search [Keynote]
AI for Web Advertising Workshop, AAAI 2023, Washington, DC, Feb 2023
[Workshop Page]
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Making Product Search More Scalable, Unbiased, and Interactive
Department of Computer Science, University of North Texas, Dallas, TX, Oct 2022
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Practical Usage of Hashing for Product Search
Invited talks at Pinterest Search and LinkedIn Search, 2022
Service
Program Committee: AAAI, UAI, CIKM, WSDM, WWW
Reviewer: ICML, NeurIPS, KDD, CIKM, AAAI, UAI
*Last updated on 2026