Chen Luo

Sr. Applied Scientist
Amazon Search
Amazon.com

Email: cheluo (at) amazon (dot) com

101 Lytton Ave
Palo Alto, CA 94301

Linkedin
Twitter

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.

Selected Talks

  • From Search to Conversational Shopping with Generative AI, Keynote, GenAI in E-Commerce Workshop, RecSys, 2025. [link]
  • Generative AI for Search and Interaction, AI Seminar, Rice University, 2025. [link]
  • Language Model Alignment for Conversational Shopping at Amazon, SIGIR, 2025.
  • Next-Generation Shopping Experience, Guest Lecture, Rice University, 2024.
  • Practical ML on Large-Scale Systems and Search Engines, Guest Lecture, George Mason University, 2023.
  • Industrial Machine Learning, US ATLAS ML Training, Lawrence Berkeley National Lab, 2023. [link]
  • Scalable Machine Learning for Product Search, Keynote, ROADS Workshop, MLSys, 2023. [link]
  • Machine Learning for Product Search, Guest Lecture, Georgia Tech, 2023.
  • Towards Scalable, Unbiased, and Interactive Product Search, Keynote, AI4WebAds Workshop, AAAI, 2023. [link]
  • Making Product Search More Scalable, Unbiased, and Interactive, University of North Texas, 2022.
  • Practical Usage of Hashing for Product Search, Pinterest Search and LinkedIn Search, 2022.

Publications Google Scholar Citation

  • Intention Knowledge Graph Construction for User Intention Relation Modeling
    Jiaxin Bai, Zhaobo Wang, Junfei Cheng, Dan Yu, Zerui Huang, Weiqi Wang, Xin Liu, Chen Luo, Yanming Zhu, Bo Li, Yangqiu Song
    The 19th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2026), Rabat, Morocco, March 24–29, 2026 [paper]
  • How Far Are LLMs from Professional Poker Players? Revisiting Game-Theoretic Reasoning with Agentic Tool Use
    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
    The International Conference on Learning Representations (ICLR 2026) [paper]
  • Seeing but Not Believing: Probing the Disconnect Between Visual Attention and Answer Correctness in VLMs
    Zhining Liu, Ziyi Chen, Hui Liu, Chen Luo, Xianfeng Tang, Suhang Wang, Jingying Zeng, Zhenwei Dai, Zhan Shi, Tianxin Wei, Hanqing Lu, Benoit Dumoulin, Hanghang Tong
    The International Conference on Learning Representations (ICLR 2026) [paper]
  • Bradley-Terry and Multi-Objective Reward Modeling Are Complementary
    Zhiwei Zhang, Hui Liu, Xiaomin Li, Zhenwei Dai, Jingying Zeng, Fali Wang, Minhua Lin, Ramraj Chandradevan, Linlin Wu, Zhen Li, Chen Luo, Zongyu Wu, Xianfeng Tang, Qi He, Suhang Wang
    The International Conference on Learning Representations (ICLR 2026) [paper]
  • Language Model Alignment for Conversational Shopping at Amazon
    Chen Luo, Dimitri Papadimitriou, Hariharan Muralidharan, Dhineshkumar Ramasubbu, Aakash Kolekar, Wenju Xu, Cong Xu, Anirudh Srinivasan, Mukesh Jain, Qi He
    The 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2025), Padua, Italy, July 13–18, 2025 [paper]
  • Examples as the Prompt: A Scalable Approach for Efficient LLM Adaptation in E-Commerce
    Jingying Zeng, Zhenwei Dai, Hui Liu, Samarth Varshney, Zhiji Liu, Chen Luo, Zhen Li, Qi He, Xianfeng Tang
    The 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2025), Padua, Italy, July 13–18, 2025 [paper]
  • EcomScriptBench: A Multi-task Benchmark for E-commerce Script Planning via Step-wise Intention-Driven Product Association
    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
    The 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), Vienna, Austria, July 27–August 1, 2025 [paper]
  • Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models
    Yingqian Cui, Pengfei He, Jingying Zeng, Hui Liu, Xianfeng Tang, Zhenwei Dai, Yan Han, Chen Luo, Jing Huang, Zhen Li, Suhang Wang, Yue Xing, Jiliang Tang, Qi He
    Findings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL Findings 2025), Vienna, Austria, July 27–August 1, 2025 [paper]
  • Reasoning with Graphs: Structuring Implicit Knowledge to Enhance LLMs Reasoning
    Haoyu Han, Yaochen Xie, Hui Liu, Xianfeng Tang, Sreyashi Nag, William Headden, Yang Li, Chen Luo, Shuiwang Ji, Qi He, Jiliang Tang
    Findings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL Findings 2025), Vienna, Austria, July 27–August 1, 2025 [paper]
  • SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains
    Ran Xu, Hui Liu, Sreyashi Nag, Zhenwei Dai, Yaochen Xie, Xianfeng Tang, Chen Luo, Yang Li, Joyce C. Ho, Carl Yang, Qi He
    The 2025 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2025), Albuquerque, New Mexico, April 29–May 4, 2025 [paper]
  • Enabling Generalized Zero-Shot Vulnerability Classification
    Jinghao Hu, Jinsong Guo, Chen Luo, Yang Hu, Matthias Lanzinger, Zhanshan Li
    IEEE Transactions on Dependable and Secure Computing (IEEE TDSC), IEEE, Jan 21, 2025 [paper]
  • A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware Demonstration
    Yingqian Cui, Pengfei He, Xianfeng Tang, Qi He, Chen Luo, Jiliang Tang, Yue Xing
    The 28th International Conference on Artificial Intelligence and Statistics (AISTATS 2025), Phuket, Thailand, May 3–5, 2025 [paper]
  • Exploring Query Understanding for Amazon Product Search
    Chen Luo, Xianfeng Tang, Hanqing Lu, Yaochen Xie, Hui Liu, Zhenwei Dai, LImeng Cui, Ashutosh Joshi, Sreyashi Nag, Yang Li, Zhen Li, Rahul Goutam, Jiliang Tang, Haiyang Zhang, and Qi He
    2024 IEEE International Conference on Big Data . (IEEE BigData'24), Washington, DC, USA, Dec, 2024 [paper]
  • IntentionQA: A Benchmark for Evaluating Purchase Intention Comprehension Abilities of Language Models in E-commerce
    Wenxuan Ding, Weiqi Wang, Sze Heng Douglas Kwok, Minghao LIU, Tianqing Fang, Jiaxin Bai, Xin Liu, Changlong Yu, Zheng Li, Chen Luo, Qingyu Yin, Bing Yin, Junxian He, Yangqiu Song
    The 2024 Conference on Empirical Methods in Natural Language Processing. (EMNLP'24), Miami, Florida, USA, Dec, 2024 [paper]
  • MIND: Multimodal Shopping Intention Distillation from Large Vision-language Models for E-commerce Purchase Understandingicon
    Baixuan Xu, Weiqi Wang, Haochen Shi, Wenxuan Ding, Huihao JING, Tianqing Fang, Jiaxin Bai, Xin Liu, Changlong Yu, Zheng Li, Chen Luo, Qingyu Yin, Bing Yin, Long Chen, Yangqiu Song
    The 2024 Conference on Empirical Methods in Natural Language Processing. (EMNLP'24), Miami, Florida, USA, Dec, 2024 [paper]
  • Large Language Models Are Poor Clinical Decision-Makers: A Comprehensive Benchmark
    Fenglin Liu, Zheng Li, Hongjian Zhou, Qingyu Yin, Jingfeng Yang, Xianfeng Tang, Chen Luo, Ming Zeng, Haoming Jiang, Yifan Gao, Priyanka Nigam, Sreyashi Nag, Bing Yin, Yining Hua, Xuan Zhou, Omid Rohanian, Anshul Thakur, Lei Clifton, David A. Clifton
    The 2024 Conference on Empirical Methods in Natural Language Processing. (EMNLP'24), Miami, Florida, USA, Dec, 2024 [paper]
  • BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering
    Haoyu Wang, Ruirui Li, Haoming Jiang, Jinjin Tian, Zhengyang Wang, Chen Luo, Xianfeng Tang, Monica Xiao Cheng, Tuo Zhao, Jing Gao
    The 2024 Conference on Empirical Methods in Natural Language Processing. (EMNLP'24), Miami, Florida, USA, Dec, 2024 [paper]
  • Understanding Inter-Session Intentions via Complex Logical Reasoning
    Jiaxin Bai, Chen Luo, Zheng Li, Qingyu Yin, Yangqiu Song
    Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . (KDD'24), Barcelona, Spain, Aug, 2024 [paper]
  • Planning Ahead in Generative Retrieval: Guiding Autoregressive Generation through Simultaneous Decoding
    Hansi Zeng*, Chen Luo, Hamed Zamani
    The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval. (SIGIR'24), Washington D.C., USA, July, 2024 [paper]
  • IterAlign: Iterative Constitutional Alignment of Large Language Models
    Xiusi Chen*, Hongzhi Wen, Sreyashi Nag, Chen Luo, Qingyu Yin, Ruirui Li, Zheng Li, Wei Wang
    2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics. (NAACL'24), Mexico City, Mexico, June, 2024 [paper]
  • Scalable and Effective Generative Information Retrieval
    Hansi Zeng*, Chen Luo, Bowen Jin, Sheikh Muhammad Sarwar, Tianxin Wei, Hamed Zamani
    Proceedings of the Web Conference, 2024. (WWW'24), Singapore, May, 2024 [paper]
  • Mitigating Exploitation Bias in Learning to Rank with an Uncertainty-aware Empirical Bayes Approach
    Tao Yang*, Cuize Han, Chen Luo, Parth Gupta, Jeff Phillips, Qingyao Ai
    Proceedings of the Web Conference, 2024. (WWW'24), Singapore, May, 2024 [paper]
  • RA-NER: Retrieval augmented NER for knowledge intensive named entity recognition
    Zhenwei Dai, Chen Luo, Zhen Li, Xianfeng Tang, Hanqing Lu, Rahul Goutam, Haiyang Zhang
    The Twelfth International Conference on Learning Representations. (ICLR'24), Vienna, Austria, May, 2024 [paper]
  • Session-aware product filter ranking in e-commerce search
    Hanqing Lu, Xianfeng Tang, Chen Luo, Limeng Cui, Zhenwei DAI, Rahul Goutam, Haiyang Zhang, Monica Xiao Cheng
    The Twelfth International Conference on Learning Representations. (ICLR'24), Vienna, Austria, May, 2024 [paper]
  • Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation
    Wei Jin*, Haitao Mao*, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang
    2023 Conference on Neural Information Processing Systems. (NeurIPS'23), New Orleans, LA, Dec, 2023 [paper]
    Powered the KDD Cup 2023 (1990+ participants, 450+ teams)
  • Complex Query Answering on Eventuality Knowledge Graph with Implicit Logical Constraints
    Jiaxin Bai*, Xin Liu, Weiqi Wang, Chen Luo, Yangqiu Song
    2023 Conference on Neural Information Processing Systems. (NeurIPS'23), New Orleans, LA, Dec, 2023 [paper]
  • Knowledge Graph Reasoning over Entities and Numerical Values
    Jiaxin Bai*, Chen Luo, Zheng Li, Qingyu Yin, Bing Yin, Yangqiu Song
    29th ACM Sigkdd Conference on Knowledge Discovery and Data Mining. (KDD'23), Long Beach, CA, Aug, 2023 [paper]
  • Implicit Query Parsing at Amazon Product Search
    Chen Luo, Rahul Goutam, Haiyang Zhang, Chao Zhang, Yangqiu Song, Bing Yin
    The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. (SIGIR'23), Taipei, Taiwan, July, 2023 [paper]
  • Query Attribute Recommendation at Amazon Search
    Chen Luo, William Headean, Neela Avudaiappan, Haoming Jiang, Tianyu Cao, Qingyu Yin, Yifan Gao, Zheng Li, Rahul Goutam, Haiyang Zhang, Bing Yin
    The ACM Conference on Recommender System, 2022. (RecSys'22), Seatle, US, Sep, 2022 [paper]
  • CERES: Pretraining of Graph-Conditioned Transformer for Semi-Structured Session Data
    Rui Feng*, Chen Luo, Qingyu Yin, Bing Yin, Tuo Zhao, Chao Zhang
    Annual Conference of the North American Chapter of the Association for Computational Linguistics, 2022. (NAACL'22), Seatle, US, July, 2022 [paper]
  • Can clicks be both labels and features? Unbiased Behavior Feature Collection and Uncertainty-aware Learning to Rank
    Tao Yang*, Chen Luo, Hanqing Lu, Parth Gupta, Yin Bing, Qingyao Ai
    The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. (SIGIR'22), Madrid, Spain, July, 2022 [paper]
  • ROSE: Robust Caches for Amazon Product Search
    Chen Luo, Vihan Lakshman, Anshumali Shrivastava, Tianyu Cao, Sreyashi Nag, Rahul Goutam, Hanqing Lu, Yiwei Song and Yin Bing
    Proc. of 2022 International Conference on World-Wide Web. (WWW'22), Lyon, France, April. 2022. [paper]
    Featured on Amazon Science Blog, Rice CS News
  • Massive Text Normalization via an Efficient Randomized Algorithm
    Nan Jiang*, Chen Luo, Vihan Lakshman, Yesh Dattatreya, Yexiang Xue
    Proc. of 2022 International Conference on World-Wide Web. (WWW'22), Lyon, France, April. 2022. [paper]
  • Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs
    Lei Cai, Zhengzhang Chen, Chen Luo, Jiaping Gui, Jingchao Ni, Ding Li, Haifeng Chen
    Proc of 2021 ACM International Conference on Information and Knowledge Management. (CIKM'21), Queensland, Australia, Oct. 2021. [paper]
  • QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction
    Danqing Zhang, Zheng Li, Tianyu Cao, Chen Luo, Tony Wu, Hanqing Lu, Yiwei Song, Bing Yin, Tuo Zhao, Qiang Yang
    Proc of 2021 ACM International Conference on Information and Knowledge Management. (CIKM'21), Queensland, Australia, Oct. 2021. [paper]
  • Scaling-up Split-Merge MCMC with Locality Sensitive Sampling (LSS)
    Chen Luo, Anshumali Shrivastava
    Proc of AAAI Conference on Artificial Intelligence 2019. (AAAI'19), Hawaii, USA, Jan. 2019. [paper]
  • Behavior-based Community Detection: Application to Host Assessment In Enterprise Information Networks
    Cheng Cao, Zhengzhang Chen, Lu-An Tang, James Caverlee, Chen Luo, and Zhichun Li
    Proc of 2018 ACM International Conference on Information and Knowledge Management (CIKM'18), Turin, Italy, Oct. 2018. [paper]
  • Jaccard Affiliation Graph (JAG) Model For Explaining Overlapping Community Behaviors
    Chen Luo, Anshumali Shrivastava
    Proc of 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'18), Barcelona, Spain, Aug. 2018. [paper]
  • TINET: Learning Invariant Networks via Knowledge Transfer
    Chen Luo, Zhengzhang Chen, Lu-An Tang, Anshumali Shrivastava, Zhichun Li, Haifeng Chen, Jieping Ye
    Proc. of 2018 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18), London, United Kingdom, Aug. 2018. [paper]
  • Arrays of (locality-sensitive) Count Estimators (ACE): High-Speed Anomaly Detection on the Edge
    Chen Luo, Anshumali Shrivastava
    Proc. of 2018 International Conference on World-Wide Web (WWW'18), Lyon, France, April. 2018. [paper]
  • Location Detection for Navigation using IMUS With a Map Through Coarse-Grained Machine Learning
    Chen Luo, J. Jose Gonzalez E., Anshumali Shrivastava, Krishna Palem, Yongshik Moon, Soonhyun Noh, Daedong Park, Seongsoo Hong
    Proc. 2017 Design, Automation and Testing in Europe (DATE'17), Swisstech, Lausanne, Switzerland, March. 2017. [paper]
  • SSH (Sketch, Shingle, & Hash) for Indexing Massive-Scale Time Series
    Chen Luo and Anshumail Shirivastava
    Proc. of NIPS 2017 Time Series Workshop, Journal of Machine Learning Research V55. (JMLR'17) [paper]
  • CaPSuLe: Camera Based Positioning System Using Learning
    Chen Luo, Yongshik Moon, Soonhyun Noh, Daedong Park, Anshumail Shirivastava, Seongsoo Hong, and Krishna Palem
    Proc. of international IEEE System-on-Chip Conference (SoCC'16), Seattle, WA, USA September. 2016.
    Featured on The NY Times, The ACM Technews, The Futurity [paper]
  • Hete-CF: Social-Based Collaborative Filtering Recommendation using Heterogeneous Relations
    Chen Luo, Wei Pang, Zhe Wang, and Chenghua Lin
    Proc. 2014 IEEE International Conference on Data Mining (ICDM'14), Shen Zheng, China, December. 2014. [paper]
  • Correlating Events with Time Series for Incident Diagnosis
    Chen Luo, Jian-Guang Lou, Qingwei Lin, Qiang Fu, Rui Ding, Dongmei Zhang, and Zhe Wang
    Proc. 2014 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'14), New York, NY, Aug. 2014. [paper]
  • HetPathMine: A Novel Transductive Classification Algorithm on Heterogeneous Information Networks
    Chen Luo, Renchu Guan, Zhe Wang, and Chenghua Lin
    Proc. of the 36th European Conference on Information Retrieval. (ECIR'14), Amsterdam, Metherlands. April, 2014 [paper]
  • Semi-supervised clustering on Heterogeneous Information Networks
    Chen Luo, Wei Pang, and Zhe Wang
    Proc. of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'14), Tainan, Taiwan, May, 2014 [paper]


Service

Program Committee: AAAI, UAI, CIKM, WSDM, WWW
Reviewer: ICML, NeurIPS, KDD, CIKM, AAAI, UAI


*Last updated on 2026