Welcome
Curious about how to write my Chinese name? It’s simply 吴仁杰.
About me
I’m currently a 4th year Ph.D student in the Department of Computer Science and Engineering at University of California, Riverside. My advisor is brilliant Dr. Eamonn Keogh. My research interest includes time series analysis, data mining, and machine learning.
Honors & Awards
- Dean’s Distinguished Fellowship
Sep. 2017 · University of California, Riverside - Outstanding Graduate (山东省优秀毕业生)
May. 2017 · Dept. Human Resources & Social Security of Shandong, China - Outstanding Model of Student Leaders (哈工大优秀学生干部标兵)
Dec. 2014 · Harbin Institute of Technology - National Scholarship (国家奖学金)
Nov. 2014 · Ministry of Education, China
- Dean’s Distinguished Fellowship
Certifications
- Microsoft Certified System Administrator
Aug. 2009 · Microsoft - Microsoft Certified IT Professional
Feb. 2009 · Microsoft - Microsoft Certified Technology Specialist
Dec. 2008 · Microsoft
- Microsoft Certified System Administrator
News
- Sep. 9, 2021: Our paper “Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress” is accepted by IEEE TKDE.
- Aug. 24, 2021: Our paper “When is Early Classification of Time Series Meaningful?” is accepted by IEEE TKDE.
- Aug. 14, 2021: The Hexagon ML/UCR Time Series Anomaly Archive is now available: https:
// www .cs .ucr .edu /~eamonn /time _series _data _2018 /UCR _Time Series Anomaly Datasets2021.zip. - Mar. 15, 2021: Our time series anomaly detection contest is now live. Go to https://compete.hexagon-ml.com/practice/competition/39/ for details.
- Jan. 25, 2021: Extended abstract of “FastDTW is approximate and Generally Slower than the Algorithm it Approximates” is accepted by ICDE2021.
- Oct. 23, 2020: Our paper “FastDTW is approximate and Generally Slower than the Algorithm it Approximates” is accepted by IEEE TKDE.
Publications
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Renjie Wu, Audrey Der, and Eamonn J. Keogh, “When is Early Classification of Time Series Meaningful?,” IEEE Transactions on Knowledge and Data Engineering (TKDE), in press, 2021.
↪ [arXiv] [doi] [supporting page] -
Renjie Wu and Eamonn J. Keogh, “FastDTW is approximate and Generally Slower than the Algorithm it Approximates (Extended Abstract),” 37th IEEE International Conference on Data Engineering (ICDE2021), pp. 2327-2328, 2021.
↪ [doi] [supporting page] -
Renjie Wu and Eamonn J. Keogh, “Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress,” IEEE Transactions on Knowledge and Data Engineering (TKDE), in press, 2021.
↪ [arXiv] [doi] [supporting page] -
Renjie Wu and Eamonn J. Keogh, “FastDTW is approximate and Generally Slower than the Algorithm it Approximates,” IEEE Transactions on Knowledge and Data Engineering (TKDE), in press, 2020.
↪ [arXiv] [doi] [supporting page]