Computer Science and Eningeering Department
University of California, Riverside
Riverside, CA 92507
My email address
- (02/14/2013) Google offered me an summer internship position today, and I will work there (Moutain View, CA) from June to September.
Looking for a 2013 summer internship. Resume available on request.
- (11/16/2011) One proposal based on my Insect project will be funded by the DOD.
- (09/19/2011) We released a major expansion of the UCR Time Series Classification/Clustering datasets. Please reference the datasets in your paper as Keogh, E., Zhu, Q., Hu, B., Hao, Y., Xi, X., Wei, L. and Ratanamahatana, C.A.(2011). The UCR Time Series Classification/Clustering. Homepage:www.cs.ucr.edu/~eamonn/time_series_data/
I graduated from the Rochester Institute of Technology in 2009 with major in Electrical and Microelectronics Engineering
- Yuan Hao, Yanping Chen, Jesin Zakaria, Bing Hu, Thanawin Rakthanmanon and Eamonn Keogh. Towards Never-Ending Learning from Time Series Streams In the 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2013). August 11-14, 2012. Chicago, Illinois, USA.
- Yuan Hao, Bilson Campana and Eamonn Keogh. Monitoring and Mining Insect Sounds in Visual Space In the 12th SIAM International Conference on Data Mining (SDM 2012). April 26-28, 2012. Anaheim, California, USA.
- Yuan Hao, Bilson Campana and Eamonn Keogh. Monitoring and Mining Animal Sounds in Visual Space In Journal of Insect Behavior, 2012.
- Bing Hu, Thanawin Rakthanmanon, Yuan Hao, Scott Evans, Stefano Lonardi, and Eamonn Keogh. Discovering the Intrinsic Cardinality and Dimensionality of Time Series using MDL. In the 11th IEEE International Conference on Data Mining (ICDM 2011). Dec 11-14, 2011. Vancouver, Canada.
- Gustavo Batista, Yuan Hao, Eamonn Keogh, Agenor Mafra-Neto. Towards Automatic Classification on Flying Insects Using Inexpensive Sensors. ICMLA'11: IEEE International Conference on Machine Learning and Applications, 2011.
Dr. Eamonn Keogh is my advisor. My research interest includes Data Mining, Machine Learning, Pattern recognition, Information Retrieval and Computational Entomology.
- Towards Never-Ending Learning from Time Series Streams (NELTS) (Project Homepage)
- Machine learning
- Design & Analysis of Algorithms
- Data Mining Techniques
- Introducion of Artificial Intelligence
- Data Base Management Systems
- Advanced Computer Architecture
- Compiler Construction
- Network Routing
- Wireless Network & Mobile Computing
- Intermediate Data Structures & Algorithm
- Applied Quantum Mechanics