Yifeng Gao


Welcome

Dr. Yifeng Gao is an assistant professor in the Department of Computer Science at University of Texas Rio Grande Valley. He received his Ph.D. degree of Computer Science, George Mason University in 2021. He previously recieved a M.S. degree in Computer Engineering from StonyBrook University in 2013. and a B.S. degree in Mathematics and Applied Mathematics from Xidian University in 2012.

In the broad research area of data mining and machine learning, his research focuses on self-supervised learning and representation learning for time series data. In addition, he also interested in various time series data mining tasks such as efficient similarity search, motif discovery, and anomaly detection.


Publication

Garcia, Kevin, Juan M. Perez, and Yifeng Gao "Efficient Hierarchical Contrastive Self-supervising Learning for Time Series Classification via Importance-aware Resolution Selection." 2024 IEEE International Conference on Big Data (BigData). IEEE, 2024


Mucun Sun, Sergio Valdez, Juan M. Perez, Kevin Garcia,Gael Galvan, Cesar Cruz, Yifeng Gao, Li Zhang , ``Entropy-Infused Deep Learning Loss Function for Capturing Extreme Values in Wind Power Forecasting'',IEEE Green Technologies Conference (IEEE-Green).2024.


Arturo Gonzalez, Kevin Garcia, Juan Manuel Perez, Yifeng Gao, and Qi Lu. ``Trajectory Analysis for Collision Detection in Foraging Robot Swarms.'' 21st International Conference on Ubiquitous Robots (UR), Student Poster, 2024


Li Zhang, Yan Zhu, Yifeng Gao, Jessica Lin, ``Discovering High-Ordered Semantic Structures in Massive Time Series: Algorithms and Applications'' in SIAM International Conference on Data Mining (SDM 2024) Tutorial


Li Zhang, Jiahao Ding, Yifeng Gao, Jessica Lin, "PMP: Privacy-Aware Matrix Profile against Sensitive Pattern Inference for Time Series." Proceedings of the 2023 SIAM International Conference on Data Mining(SDM'23)


Li Zhang, Yan Zhu, Yifeng Gao, Jessica Lin, "Robust Time Series Chain Discovery with Incremental Nearest Neighbors." In 2022 IEEE International Conference on Data Mining (ICDM'22).


Sayadi, Hossein, Yifeng Gao, Hosein Mohammadi Makrani, Jessica Lin, Paulo Cesar Costa, Setareh Rafatirad, and Houman Homayoun. "Towards Accurate Run-Time Hardware-Assisted Stealthy Malware Detection: A Lightweight, Yet Effective Time Series CNN-Based Approach." Cryptography 5, no. 4 (2021): 28.


Yifeng Gao, Hosein Mohammadi Makrani, Mehrdad Aliasgari, Amin Rezaei, Jessica Lin, Houman Homayoun, and Hossein Sayadi. "Adaptive-HMD: Accurate and Cost-Efficient Machine Learning-Driven Malware Detection using Microarchitectural Events." in 2021 IEEE 27th International Symposium on On-Line Testing and Robust System Design (IOLTS 2021)


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, Radio Science, Wiley, 2013, 48(3), pp.208-225