Tong Wu
PhD student
Department of Electrical and Computer Engineering
Rutgers, The State University of New Jersey
Phone: 848-445-8554
Email: tong.wu.ee@rutgers.edu
About Me
I am a 5th-year Ph.D. student at Rutgers University. I am fortunate to work with Prof. Waheed Bajwa. Before coming to Rutgers, I obtained my M.S. degree in Electrical Engineering from Duke University in 2011 and B.E. degree in Instrument Science and Engineering from Shanghai Jiao Tong University in 2009. My research interests include machine learning, statistical signal processing, big data analytics, and computer vision.
More information about me can be found at my Linkedin page.
Publications
- T. Wu and W. U. Bajwa, "Learning the nonlinear geometry of high-dimensional data: Models and algorithms," IEEE Trans. Signal Processing, vol. 63, no. 23, pp. 6229-6244, Dec. 2015. [PDF] (published version here)
- T. Wu, P. Gurram, R. M. Rao and W. U. Bajwa, "Clustering-aware structure-constrained low-rank representation model for learning human action attributes," in Proc. IEEE Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), Bordeaux, France, Jul. 11-12, 2016, pp. 1-5. [PDF] (Best Student Paper Award)
- T. Wu, P. Gurram, R. M. Rao and W. U. Bajwa, "Hierarchical union-of-subspaces model for human activity summarization," in Proc. IEEE Int. Conf. on Computer Vision Workshop, Santiago, Chile, 2015, pp. 1053-1061. [PDF]
- T. Wu, A. D. Sarwate and W. U. Bajwa, "Active dictionary learning for image representation," in Proc. SPIE Unmanned Systems Technology XVII, vol. 9468, Baltimore, MD, Apr. 21-23, 2015. [PDF]
- T. Wu and W. U. Bajwa, "Metric-constrained kernel union of subspaces," in Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Brisbane, Australia, Apr. 19-24, 2015, pp. 5778-5782. [PDF]
- T. Wu and W. U. Bajwa, "Subspace detection in a kernel space: The missing data case," in Proc. IEEE Workshop on Statistical Signal Processing (SSP), Gold Coast, Australia, Jun. 29-Jul. 2, 2014, pp. 93-96. [PDF]
- T. Wu and W. U. Bajwa, "Revisiting robustness of the union-of-subspaces model for data-adaptive learning of nonlinear signal models," in Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Florence, Italy, May 4-9, 2014, pp. 3390-3394. [PDF]
- T. Wu, G. Polatkan, D. Steel, W. Brown, I. Daubechies and R. Calderbank, "Painting analysis using wavelets and probabilistic topic models," in Proc. IEEE Int. Conf. on Image Processing (ICIP), Melbourne, Australia, Sep. 15-18, 2013, pp. 3264-3268. [PDF]