Yan Zheng

Sr. Staff Research Scientist, Risk Modeling

Research Areas: Data Analytics, Machine Learning, and Deep Learning

Biography

Dr. Yan Zheng joined Visa Research as a Staff Research Scientist in 2017, and was promoted to Sr. Staff Research Scientist in March 2019. Prior to joining Visa, Yan was a Research Assistant at the University of Utah, and a Research Intern at Visa Research. Yan received her Ph.D. in Computer Science from the University of Utah in 2017, and a B.S. in Computer Science from Nankai University. Her Ph.D. thesis titled, “Algorithms and Coresets for Large Scale kernel Smoothing,” focused on algorithms for dealing with large-scale kernel smoothing problem, including kernel density estimate and kernel regression.

As a member of the Data Analytics team, her research interests are in deep learning and large-scale data analytics, in particular data mining, databases and machine learning. Dr. Zheng regularly serves on the program committee of data mining conferences and has published 13 papers in several international conferences and journals, including Virtual Dedicated Server (VDS), Knowledge Discovery and Data Mining (KDD), Association for Computing Machinery's (ACM) Special Interest Group on Management of Data (SIGMOD), and many more.

Conferences

Zheng, Y., Ou, Y., Lex, A., & Phillips, J. M. (2019). Visualization of Big Spatial Data using Coresets for Kernel Density Estimates. Visual Data Science.
Zheng, Y., & Phillips, J. M. (2017). Coresets for Kernel Regression. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
Phillips, J. M., & Zheng, Y. (2015). Subsampling in Smoothed Range Spaces. Algorithmic Learning Theory.
Zheng, Y., & Phillips, J. M. (2015). L∞ Error and Bandwidth Selection for Kernel Density Estimates of Large Data. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
Phillips, J., Wang, B., & Zheng, Y. (2015). Geometric Inference on Kernel Density Estimates. International Symposium on Computational Geometry.
Zheng, Y., Jestes, J., Phillips, J., & Li, F. (2013). Quality and Efficiency in Kernel Density Estimates for Large Data. ACM SIGMOD International Conference on Management of Data.
Yang, J., Shi, G., Zheng, Y., & Wang, Q. (2009). The research on offline palmprint identification. Computer Science and Information Engineering.
Zheng, Y., Shi, G., Wang, Q., & Zhang, L. (2008). Location of Special Areas on Palmprint. Congress on Image and Signal Processing.
Zheng, Y., Shi, G., Zhang, L., Wang, Q., & Zhao, Y. (2007). Research on Offline Palmprint Image Enhancement. IEEE International Conference on Image Processing.
Zheng, Y., Shi, G., Wang, Q., & Zhang, L. (2007). Palmprint Image Quality Measures in Minutiae-based Recognition. International Workshop on Systems, Signals and Image Processing. EURASIP Conference Focused on Speech and Image Processing, Multimedia Communications and Services.
Zheng, Y., Liu, Y., Shi, G., Li, J., & Wang, Q. (2007). Segmentation of Offline Palmprint. IEEE International Conference on Signal-Image Technologies and Internet-Based System.
Liu, Y., Zheng, Y., Shi, G., & Wang, Q. (2007). Research on Skeletonization of Palmprint Image. IEEE International Conference on Signal-Image Technologies and Internet-Based System.

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