Department of Computer Science & Engineering
University of California, Riverside
Office: 368 Winston Chung Hall (WCH), Bourns College of Engineering, Riverside, CA -92521
Email: nbegu001 AT cs DOT ucr DOT edu
My research area is Data Mining, Time Series Analysis, Information Retrieval, and Pattern Recognition. Currently I am doing my PhD under the supervision of the most brilliant person I have ever seen, Professor Dr. Eamonn Keogh. My DBLP is here. My Google Scholar profile is here.
· May 25, 2016: Successfully defended my PhD Dissertation titled Exploiting Time Series Primitives to Solve Realistic Data Mining Problems. [thesis]
· October 16, 2015: My Summer project in Yahoo Labs was selected to be filed as a defensive publication.
· June 15, 2015: Started working as a Summer Intern in Yahoo! Labs, CA.
· May 12, 2015: Our paper titled Accelerating Dynamic Time Warping Clustering with a Novel Admissible Pruning Strategy, was accepted in KDD 2015.
· June 16, 2014: Started working as a Summer Intern in Bell Labs, NJ.
· June 6, 2014: Our paper titled Rare Time Series Motif Discovery from Unbounded Streams was accepted in VLDB 2015.
· August 30, 2013: Our IRI paper was selected for submission in IRI best papers!
· June 20, 2013: Our paper titled Towards a Minimum Description Length Based Stopping Criterion for Semi-Supervised Time Series Classification was accepted in IRI 2013.
· March 6, 2013: Successfully qualified as a PhD candidate.
1. Intern Scientist, Yahoo! Labs
Project: Multi Dimensionl Time Series Shapelet Classification Using Discriminative Model
Manager: Yi Chang
Latest: My project is selected to be filed as a defensive publication by Yahoo!
2. IP Platform Researcher Intern, Bell Labs (Alcatel-Lucent, USA Inc.)
Project: Multi Dimensionl Time Series Clustering Using Minimum Description Length
Mentor: Huseyin Uzunalioglu
4. Teaching Assistant, UC Riverside
Fall 2012-Spring 2013
I. CS 006 (Effective Use of Worldwide Web)
II. CS 008 (Introduction to Computing)
5. Software Engineer, IMS (Intercontinental Medical Statistics) Health
December 2009-August 2011
2. Accelerating Dynamic Time Warping Clustering with a Novel Admissible Pruning Strategy, Nurjahan Begum, Liudmila Ulanova, Jun Wang, and Eamonn Keogh, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015. Acceptance Rate: 19%. [pdf] [Project Page] [Talk] [Slides] [Poster]
5. Rare Pattern Discovery from Time Series, Nurjahan Begum, and Eamonn Keogh, Grace Hopper Celebration of Women in Computing (GHC), 2014. [pdf]
6. Semi-supervision Dynamically Improves Time Series Clustering under Dynamic Time Warping, Hoang Anh Dau, Nurjahan Begum, and Eamonn Keogh, Int’l Conference on Information and Knowledge Management (CIKM), 2016. [pdf] [Project Page]
7. Clustering in the Face of Fast Changing Streams, Liudmila Ulanova, Nurjahan Begum, Mohammad Shokoohi-Yekta and Eamonn Keogh, SIAM Int'l Conference on Data Mining (SDM), 2016. [pdf][slides][Poster][Project Page]
8. A Minimum Description Length Technique for Semi-Supervised Time Series Classification, Nurjahan Begum, Bing Hu, Thanawin Rakthanmanon and Eamonn Keogh, Integration of Reusable Systems, Special Issue in Advances in Intelligent and Soft Computing, Springer Berlin Heidelberg (AISC), (IRI Best Papers), 2014. [pdf]
9. Towards a Minimum Description Length Based Stopping Criterion for Semi-Supervised Time Series Classification, Nurjahan Begum, Bing Hu, Thanawin Rakthanmanon and Eamonn Keogh, in the Proceedings of the 14th IEEE International Conference on Information Reuse and Integration (IRI), 2013. Acceptance Rate: ~26%.[pdf] [slides] [Project Page].
10. Optimal Queries Processing in a Heterogeneous Sensor Network using Multicommodity Network Flow Method, Nurjahan Begum, Samia Tasnim and Mahmuda Naznin, in the Proceedings of the17th IEEE International Conference on Industrial Engineering and Engineering Management (IE&EM), 2010. [pdf]
PhD, Spring 2016
Masters of Science, Winter 2016
Bachelor of Science, 2004-2009