Beilei Xu’s research interests are image/video analytics, machine learning and statistical modeling. Prior to joining University of Rochester, Beilei was a senior research scientist at PARC, Conduent and Xerox, where she contributed and led a variety of projects ranging from data analytic research in managed print services, subsystem modeling of xerographic marking process, image rendering and image-based defect detection, to computer vision and machine learning research in healthcare and transportation.
Beilei holds a Ph.D. in Medical Physics from University of Chicago. She is a certified Design for Lean Six Sigma Black Belt. She has been a reviewer/referee for several journals and served on program committees and chaired sessions of conferences in the areas of image/video processing, healthcare, and transportation. She has served on the review panel for the National Science Foundation grant review committees. Beilei has published 27 papers, a book chapter and holds 120 US patents with more pending applications. She is a recipient of the Xerox Innovation Group President’s Award and the Xerox Anne Mulcahy Inventor Award for her contributions to Xerox intellectual property.
- Lin, B. Xu, W. Wu, T. Richardson, E. A. Bernal, B. Martens, C. Thornton, C. Heatwole, “Deep Metric Learning with Triplet Networks: Application to Hand-grip Myotonia,” IEEE EMB Special Topic Conference on Healthcare Innovations and Point-of-Care Technologies, 2019
- Wu, B. Xu, E. A. Bernal, R. L. Hill, E. B. Brown, and D. Desa “Breast Cancer Tissue Sub-Type Classification from Second Harmonic Generation Images via Machine Learning,” IEEE EMB Special Topic Conference on Healthcare Innovations and Point-of-Care Technologies, 2019
- Cheng, B. Xu, W. Wu, L. Lin, T. Richardson, and E. A. Bernal, “An Unsupervised Machine Learning Framework for Parkinson’s Disease Progression Analysis and Subtyping,” IEEE EMB Special Topic Conference on Healthcare Innovations and Point-of-Care Technologies, 2019
- Shreve, R. Bala, W. Wu, B. Xu, P. Matts, A, Purwar, “Deep CNNs for Facial Skin Age Modeling,” accepted to International Conference on Machine Vision Applications, May 27–31 2019, Tokyo, Japan.
- Gavai, W. Wu, B. Xu, et. al., “Hybrid Image-based Defect Detection for Railroad Maintenance,” 2019 IS&T International Symposium on Electronic Imaging, Jan. 13-17, 2019, Burlingame, CA.
- Lei Lin, Beilei Xu, Wencheng Wu, Trevor W. Richardson, and Edgar A. Bernal. “Medical Time Series Classification with Hierarchical Attention-based Temporal Convolutional Networks: A Case Study of Myotonic Dystrophy Diagnosis.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 83-86. 2019.
Conference Proceedings and Presentations
- B. Xu, Collaboration with URMC, Presented to the Board of RDSC, March 2019.
- L. Lin, B. Xu, W. Wu, T. Richardson, E. Bernal. Deep Metric Learning with Triplet Networks: Application to Myotonic Dystrophy Diagnosis. CEIS, April 2019.
- W. Wu, R. Hill, E. Brown, B. Xu, E. Bernal, E. Patak. Image-Based Biomarkers for Cancer Recurrence Prediction using SHG imaging, CEIS April 2019. (Best Poster Award)
- B.Xu, W. Wen, S. Wshah, R. Elmoudi, L. Lin. Advanced Modeling of Power System Dynamics Using Machine Learning. NYISO, Albany, August 2019.
- B. Xu, W. Wen, S. Wshah, R. Elmoudi. Advanced Modeling of Power System Dynamics Using Machine Learning. NYSERDA, Albany, Nov 2018.