Jyun-Yu Jiang My Mandarin Name is ''姜俊宇''.


This is a photo taken at Hokkaido, Japan.

General Information [Curriculum Vitae] [Google Scholar] [DBLP]

I am an applied scientist and a researcher at Amazon Search. I received my Ph.D. from Department of Computer Science at University of California, Los Angeles in 2021. Before that, I received my M.S. and B.S. degrees from Department of Computer Science and Information Engineering at National Taiwan University in 2015 and 2013.

My research interests include Machine Learning, Data Mining, Natural Language Processing, Information Retrieval, Computational Social Science, and Bioinformatics. More specifically, I am interested in developing effective machine learning techniques and efficient algorithms to solve real-world problems.

Contact Information

  • E-mail: My email address is jyunyu [AT] amazon [DOT] com or My email address is jyunyu.jiang [AT] gmail [DOT] com

Publications

2023

  • Yu Yan, Jyun-Yu Jiang, Mingzhou Fu, Ding Wang, Alexander Pelletier, Dibakar Sigdel, Wei Wang and Peipei Ping. MIND-S: A Novel Deep Learning Prediction Model For Elucidating Protein PTMs In Human Diseases. Cell Reports Methods, 2023.
  • Patrick H. Chen, Wei-Cheng Chang, Jyun-Yu Jiang, Hsiang-Fu Yu, Inderjit Dhillon and Cho-Jui Hsieh. FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search. In Proceedings of 2023 The Web Conference (WWW '23), ACM, 2023.
  • Xiusi Chen, Yu Zhang, Jinliang Deng, Jyun-Yu Jiang and Wei Wang. Gotta: Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation. In Proceedings of the 2023 SIAM International Conference on Data Mining (SDM '23), SIAM, 2023.

2022

  • Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh and Hsiang-Fu Yu. Uncertainty in Extreme Multi-label Classification. Technical Report, 2022.
  • Hsiang-Fu Yu, Jiong Zhang, Wei-Cheng Chang, Jyun-Yu Jiang, Wei Li and Cho-Jui Hsieh. Hands-on Tutorial "PECOS: Prediction for Enormous and Correlated Output Spaces." The 28th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22), ACM, 2022.
  • Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh and Hsiang-Fu Yu. Relevance under the Iceberg: Reasonable Prediction for Extreme Multi-label Classification. In Proceedings of The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '22), ACM, 2022.
  • Xiusi Chen, Jyun-Yu Jiang, Kun Jin, Yichao Zhou, Mingyan Liu, Paul Jeffrey Brantingham and Wei Wang. ReLiable: Offline Reinforcement Learning for Tactical Strategies in Professional Basketball Games. In Proceedings of The 31st ACM International Conference on Information and Knowledge Management (CIKM '22), ACM, 2022.
  • Xiusi Chen, Jyun-Yu Jiang and Wei Wang. Scalable Graph Representation Learning via Locality-Sensitive Hashing. In Proceedings of The 31st ACM International Conference on Information and Knowledge Management (CIKM '22), ACM, 2022.
  • Jyun-Yu Jiang, Yichao Zhou, Xiusi Chen, Yan-Ru Jhou, Liqi Zhao, Sabrina Liu, Po-Chun Yang, Jule Ahmar and Wei Wang. COVID-19 Surveiller: toward a robust and effective pandemic surveillance system based on social media mining. In Philosophical Transactions of the Royal Society A, 2022.

2021

2020

2019

2018

2017

Before 2016

Large-scale Machine Learning

  • Patrick H. Chen, Wei-Cheng Chang, Jyun-Yu Jiang, Hsiang-Fu Yu, Inderjit Dhillon and Cho-Jui Hsieh. FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search. In Proceedings of 2023 The Web Conference (WWW '23), ACM, 2023.
  • Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh and Hsiang-Fu Yu. Uncertainty in Extreme Multi-label Classification. Technical Report, 2022.
  • Hsiang-Fu Yu, Jiong Zhang, Wei-Cheng Chang, Jyun-Yu Jiang, Wei Li and Cho-Jui Hsieh. Hands-on Tutorial "PECOS: Prediction for Enormous and Correlated Output Spaces." The 28th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22), ACM, 2022.
  • Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh and Hsiang-Fu Yu. Relevance under the Iceberg: Reasonable Prediction for Extreme Multi-label Classification. In Proceedings of The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '22), ACM, 2022.
  • Xiusi Chen, Jyun-Yu Jiang and Wei Wang. Scalable Graph Representation Learning via Locality-Sensitive Hashing. In Proceedings of The 31st ACM International Conference on Information and Knowledge Management (CIKM '22), ACM, 2022.
  • Jyun-Yu Jiang*, Patrick H. Chen*, Cho-Jui Hsieh and Wei Wang. Clustering and Constructing User Coresets to Accelerate Large-scale Top-K Recommender Systems. In Proceedings of the 2020 World Wide Web Conference (WWW '20), ACM, 2020. (*equal contribution) [slides] [code]

Information Retrieval and Web Search

Social Media Mining

Bioinformatics and Biomedical Informatics

General Machine Learning Research

Selected Awards

Problem Solving Contest

Education

2016/09 -- 2021/06

2013/09 -- 2015/07

2009/09 -- 2013/06

2006/09 -- 2009/06

Taipei Municipal Jianguo High School, Taipei, Taiwan

Diploma in Math and Science Gifted Program


Last modified at PT 16:26 02/01/2023

My email address is jyunyu.jiang [AT] gmail.com

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