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 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.

Publications Google Scholar Citation

* Indicate Equal Contribution

1. Rui Feng, Chen Luo, Qingyu Yin, Bing Yin, Tuo Zhao, Chao Zhang "CERES: Pretraining of Graph-Conditioned Transformer for Semi-Structured Session Data" In: Annual Conference of the North American Chapter of the Association for Computational Linguistics, 2022. (NAACL'22), Seatle, US, July, 2022


2. Tao Yang, Chen Luo, Hanqing Lu, Parth Gupta, Yin Bing, Qingyao Ai "Can clicks be both labels and features? Unbiased Behavior Feature Collection and Uncertainty-aware Learning to Rank" In: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. (SIGIR'22), Madrid, Spain, July, 2022


3. Chen Luo, Vihan Lakshman, Anshumali Shrivastava, Tianyu Cao, Sreyashi Nag, Rahul Goutam, Hanqing Lu, Yiwei Song and Yin Bing "ROSE: Robust Caches for Amazon Product Search" In: Proc. of 2022 International Conference on World-Wide Web. (WWW'22), Lyon, France, April. 2022.


4. Nan Jiang, Chen Luo, Vihan Lakshman, Yesh Dattatreya, Yexiang Xue "Massive Text Normalization via an Efficient Randomized Algorithm" In: Proc. of 2022 International Conference on World-Wide Web. (WWW'22), Lyon, France, April. 2022.


5. Lei Cai, Zhengzhang Chen, Chen Luo, Jiaping Gui, Jingchao Ni, Ding Li, Haifeng Chen, "Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs" In: Proc of 2021 ACM International Conference on Information and Knowledge Management. (CIKM'21), Queensland, Australia, Oct. 2021.


6. Danqing Zhang, Zheng Li, Tianyu Cao, Chen Luo, Tony Wu, Hanqing Lu, Yiwei Song, Bing Yin, Tuo Zhao, Qiang Yang, "QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction" In: Proc of 2021 ACM International Conference on Information and Knowledge Management. (CIKM'21), Queensland, Australia, Oct. 2021.


7. Chen Luo, Anshumali Shrivastava, "Scaling-up Split-Merge MCMC with Locality Sensitive Sampling (LSS)" In: Proc of AAAI Conference on Artificial Intelligence 2019. (AAAI'19), Hawaii, USA, Jan. 2019.


8. Cheng Cao, Zhengzhang Chen, Lu-An Tang, James Caverlee, Chen Luo, and Zhichun Li, "Behavior-based Community Detection: Application to Host Assessment In Enterprise Information Networks" In: Proc of 2018 ACM International Conference on Information and Knowledge Management (CIKM'18), Turin, Italy, Oct. 2018.


9. Chen Luo, Anshumali Shrivastava, "Jaccard Affiliation Graph (JAG) Model For Explaining Overlapping Community Behaviors" In: Proc of 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'18), Barcelona, Spain, Aug. 2018.


10. Chen Luo, Zhengzhang Chen, Lu-An Tang, Anshumali Shrivastava, Zhichun Li, Haifeng Chen, Jieping Ye, "TINET: Learning Invariant Networks via Knowledge Transfer" In: Proc. of 2018 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18), London, United Kingdom, Aug. 2018.


11. Chen Luo, Anshumali Shrivastava, "Arrays of (locality-sensitive) Count Estimators (ACE): High-Speed Anomaly Detection on the Edge" In: Proc. of 2018 International Conference on World-Wide Web (WWW'18), Lyon, France, April. 2018.


12. Chen Luo*, J. Jose Gonzalez E.*, Anshumali Shrivastava, Krishna Palem, Yongshik Moon, Soonhyun Noh, Daedong Park, Seongsoo Hong, "Location Detection for Navigation using IMUS With a Map Through Coarse-Grained Machine Learning" In: Proc. 2017 Design, Automation and Testing in Europe (DATE'17), Swisstech, Lausanne, Switzerland, March. 2017.


13. Chen Luo and Anshumail Shirivastava, "SSH (Sketch, Shingle, & Hash) for Indexing Massive-Scale Time Series" Proc. of NIPS 2017 Time Series Workshop, Journal of Machine Learning Research V55. (JMLR'17)


14. Yongshik Moon*, Soonhyun Noh*, Daedong Park*, Chen Luo*, Anshumail Shirivastava, Seongsoo Hong, and Krishna Palem, "CaPSuLe: Camera Based Positioning System Using Learning" In: 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


15. Chen Luo, Wei Pang, Zhe Wang, and Chenghua Lin "Hete-CF: Social-Based Collaborative Filtering Recommendation using Heterogeneous Relations" In: Proc. 2014 IEEE International Conference on Data Mining (ICDM'14), Shen Zheng, China, December. 2014.


16. Chen Luo, Jian-Guang Lou, Qingwei Lin, Qiang Fu, Rui Ding, Dongmei Zhang, and Zhe Wang "Correlating Events with Time Series for Incident Diagnosis" In: Proc. 2014 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'14), New York, NY, Aug. 2014.


17. Chen Luo, Renchu Guan, Zhe Wang, and Chenghua Lin " HetPathMine: A Novel Transductive Classification Algorithm on Heterogeneous Information Networks" In: Proc. of the 36th European Conference on Information Retrieval. (ECIR'14), Amsterdam, Metherlands. April, 2014


18. Chen Luo, Wei Pang, and Zhe Wang, "Semi-supervised clustering on Heterogeneous Information Networks" In: Proc. of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'14), Tainan, Taiwan, May, 2014

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