Yifeng Gao

Welcome

I am a Ph.D. candidate in the Department of Computer Science at George Mason University. My advisor is Prof. Jessica Lin. I received my B.S. degree in Mathematics and Applied Mathematics from Xidian University in 2012 and received my M.S. degree in Computer Engineering from Stonybrook University in 2013.

In the broad research area of data mining and machine learning, my research focuses on 1) similarity search, motif discovery, and anomaly detection in time series; 2) spatial temporal pattern mining; 3) efficient and interpretable machine learning; 4) Interdisciplinary applications in broader areas such as health-care, user behavior analysis, and cybersecurity.

Resource

Resource for paper "TapNet: Multivariate Time Series Classification with Attentional Prototype Network" can be found in Github

Resource for paper "Discovering Subdimensional Motifs of Different Lengths in Large-Scale Multivariate Time Series" can be found in Github

Resource for paper "Efficient Discovery of Time Series Motifs with Large Length Range in Million Scale Time Series" can be found in Support Website

Resource for paper "TrajViz: A Tool for Visualizing Patterns and Anomalies in Trajectory" can be found in Github Webpage

Publication

Li Zhang, Yifeng Gao, Jessica Lin, "Semantic Discord: Finding Unusual Local Patterns for Time Series", in SIAM International Conference on Data Mining (SDM 2020), Cincinnati, May 2020. (to appear) [acceptance rate: 24%]


Xuchao Zhang*, Yifeng Gao*, Jessica Lin, Chang-Tien Lu, "TapNet: Multivariate Time Series Classification with Attentional Prototype Network", in AAAI Conference on Artificial Intelligence (AAAI 2020), New York, Feb. 2020. (to appear) [acceptance rate: 20.6%] *These two authors contributed equally.


Yifeng Gao, Jessica Lin, Constantin Brif, "Ensemble Grammar Induction For Detecting Anomalies in Time Series" in International Conference on Extending Database Technology (EDBT 2020), Copenhagen, Mar. 2020. (to appear) [acceptance rate: 20.5%]


Yifeng Gao, Jessica Lin, "HIME: Discovering Variable-length Motifs in Large-Scale Time Series" in Knowledge and Information Systems Journal (KAIS), Springer, 2019, 61(1), pp.513-542


Yifeng Gao, Jessica Lin, "Discovering Subdimensional Motifs of Different Lengths in Large-Scale Multivariate Time Series" in Proceedings of the IEEE International Conference on Data Mining (ICDM 2019), Long Paper, Beijing, Nov. 2019. (to appear) [acceptance rate: 9.08%]


Yifeng Gao, Jessica Lin, "Exploring Variable-Length Time Series Motifs in One Hundred Million Length Scale" in Data Mining and Knowledge Discovery Journal (DMKD), Springer, 2018, 32(5), pp.1200-1228


Yifeng Gao, Jessica Lin, "Efficient Discovery of Time Series Motifs with Large Length Range in Million Scale Time Series" in Proceedings of the IEEE International Conference on Data Mining (ICDM 2017), long paper [pdf]


Yifeng Gao, Qingzhe Li, Xiaosheng Li, Jessica Lin, Huzefa Rangwala, "TrajViz: A Tool for Visualizing Patterns and Anomalies in Trajectory" in The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, demonstration track [pdf]


Elizabeth K. Bowman, Matt Turek, Paul Tunison, Reed Porter, Steve Thomas, Vadas Gintautas, Peter Shargo, Jessica Lin, Qingzhe Li, Yifeng Gao, Xiaosheng Li; Ranjeev Mittu, Carolyn Penstein Rose, Keith Maki, Chris Bogart, Samrihdi Shree Choudhari, "Advanced text and video analytics for proactive decision making." In Next-Generation Analyst V, International Society for Optics and Photonics, (SPIE 2017), Anaheim, May 2017.


Ranjeev Mittu, Jessica Lin, Qingzhe Li, Yifeng Gao, Huzefa Rangwala, Peter Shargo, Joshua Robinson, Carolyn Rose, Paul Tunison, Matt Turek, Stephen Thomas, Phil Hanselman, "Foundations for context-aware information retrieval for proactive decision support." In Next-Generation Analyst IV, International Society for Optics and Photonics, (SPIE 2016), Baltimore, May 2016.


Yifeng Gao, Jessica Lin, Huzefa Rangwala, "Iterative Grammar-Based Framework for Discovering Variable-Length Time Series Motifs" in Proceedings of the 15th IEEE International Conference on in Machine Learning and Applications (ICMLA16) [pdf]


Xing Wang, Yifeng Gao, Jessica Lin, Huzefa Rangwala, Ranjeev Mittu "A machine learning approach to false alarm detection for critical arrhythmia alarms" in Proceedings of the 14th IEEE International Conference on in Machine Learning and Applications (ICMLA15)[pdf]


Shuhong Gong, Yifeng Gao, Houbao Shi, Ge Zhao, A practical MGA ARIMA model for forecasting real time dynamic rain induced attenuation, Journal of Radio Science, 2013[pdf]


Yifeng Gao, Dan Lv "Principal coordinate strategy: a novel adaptive control strategy for differential evolution" in Proceedings of the 14th annual conference companion on Genetic and evolutionary computation (GECCO12), undergraduate student track[pdf]


Yifeng Gao, Shuhong Gong, Ge Zhao, "A Novel and Robust Evolution Algorithm for Optimizing Complicated Functions", 2011 Fourth International Workshop on Advanced Computational Intelligence (IWACI 2011) [pdf]