Nasser M. Nasrabadi is a professor in the Lane Department of Computer Science and Electrical Engineering at West Virginia University. Nasrabadi’s research and teaching interests are in the areas of image processing, computer vision, machine learning, deep neural networks, biometrics, and sparsity theory. He received the BS and Ph.D. degrees in electrical engineering from Imperial College of Science and Technology (University of London), London, England, in July 1980 and October 1984, respectively. He previously worked as a member of the technical staff at Phillips Research Laboratory in NY, an assistant professor in the Department of Electrical Engineering at Worcester Polytechnic Institute, an associate professor with the Department of Electrical and Computer Engineering at the University at Buffalo, and as a senior research scientist with the U.S. Army Research Laboratory. Nasrabadi has served as an associate editor for IEEE Transactions on Image Processing; IEEE Transactions on Circuits, Systems, and Video Technology, and IEEE Transactions on Neural Networks. Upon joining WVU in 2016, he founded the Biometrics & Identity, Innovation Center and he is the director of Cognitive Computing Laboratory (CCL). His current research interests are in image processing, computer vision, biometrics, deep learning, statistical machine learning theory, sparsity, robotics, and neural network applications to image processing. He is a Fellow of IEEE.

Education History

  • Electrical Engineering Electrical and Computer Engineering, Imerial College

Work Experience

Professor, West Virginia University

Publications

Zhangming Ding, Nasser M. Nasrabadi, Yun Fu, “Semi-supervised Task-driven Deep Transfer Learning via Coupled Neural Networks,” IEEE Transaction on Image Processing Neural, vol. 27, issue 11, pp. 5214-5224, June 2018.

Tianpei Xie, Nasser M. Nasrabadi, Alfred O. Hero III, “Learning to Classify with Possible Sensor Failures,” IEEE Transactions on Signal Processing, vol. 65, no.4, pp. 836-849, 2017.

A Torfi, SM Iranmanesh, N M. Nasrabadi, J Dawson, “3D Convolutional Neural Networks for Cross Audio-Visual Matching Recognition,” IEEE Access, vol. 5, pp. 22081-22091, 2017.

Tianpei Xie, Nasser M. Nasrabadi, Alfred O. Hero III, “Learning to Classify with Possible Sensor Failures,” IEEE Transactions on Signal Processing, vol. 65, no.4, pp. 836-849, 2017.

Minh Dao, Nam Nguyen, Nasser M. Nasrabadi, Trac D. Tran, “Multi-Sensor Classification via Joint Sparse Representation for discriminating between human and animal footsteps,” IEEE Transactions on Signal Processing, vol. 64, no. 9, pp. 2400-2415, May 2016.

Soheil Bahrampour, Nasser M. Nasrabadi, Asok Ray, Kenneth W. Jenkins, “Multimodal Task-Driven Dictionary Learning,” IEEE Transactions on Image Processing, vol. 25, no. 1, pp. 24-38 Jan. 2016.

Benjamin S. Riggan, Christopher Reale, Nasser M. Nasrabadi, “Coupled Auto-Associative Neural Networks for Heterogeneous Face Recognition,” IEEE Access, vol. 3, pp. 1620-1632, Oct. 2015.

Qing Qu, Nasser M. Nasrabadi, Trac D. Tran, “Subspace Vertex Pursuit: A Fast and Robust Near-Separable Nonnegative Matrix Factorization Method for Hyperspectral Unmixing,” IEEE Journal of Selected Topics in Signal Processing, vol. 9, no. 6, pp. 1142-1155, Sept. 2015.

Xiaoxia Sun, Qing Qu, Nasser M. Nasrabadi, Trac D. Tran, “Task-driven Dictionary Learning for Hyperspectral Image Classification with Structured Sparsity Priors,” IEEE Trans. On Geoscience and Remote Sensing, vol. 53, no. 8, pp. 4457-4471, Aug. 2015

Zhangyang Wang, Nasser M. Nasrabadi, Thomas S. Huang, “Semi-supervised Hyperspectral Classification Using Task-driven Dictionary Learning with Laplacian Regularization,” IEEE Transactions on Geoscience and Remote Sensing, Vol.53, No.3, pp. 1161-1173, March 2015.

Umamahesh Srinivas, Nasser M. Nasrabadi, Vishal Monga, “Graph-based Sensor Fusion for Classification of Transient Acoustic Signals,” IEEE Transactions on Cybernetics, Accepted to appear in Vol., No. , pp. 00-00 Dec. 2014.

Zhaowen Wang, Nasser M. Nasrabadi, Thomas Huang, “Spatial-spectral Classification of Hyperspectral Images using Discriminative Dictionary Designed by Learning Vector Quantization,” IEEE Trans. On Geoscience and Remote Sensing, Vol. 52, No. 8, pp. 4808-4822, August 2014.

Xiaoxia Sun, Qing Qu, Nasser M. Nasrabadi, Trac D. Tran, “Structured Priors for Sparse Representation Based Hyperspectral Image Classification,” IEEE Geoscience and Remote Sensing Letter, To appear in vol.11, no. 5, pp. 00-00, Sept. 2014.

Qing Qu, Nasser M. Nasrabadi, Trac D. Tran, “Abundance Estimation for Bilinear mixture models via joint sparse and low rank representations,” IEEE Trans. On Geoscience and Remote Sensing, Vol. 52, No. 7, pp.4404-4422, July 2014.

Nasser M. Nasrabadi, “Hyperspectral Target Detection: An Overview of Current and Future Challenges,” IEEE Signal Processing Magazine, vol.31, no.1, pp. 34-44, Jan. 2014.

Vishal M. Patel, Glenn R. Easley, Nasser M. Nasrabadi, and Rama Chellappa, “Separated Component-Based Restoration of Speckled SAR Images,” IEEE Trans. On Geoscience and Remote Sensing, Vol. 52, No. 2, pp. 1019-1029, Feb. 2014.

Sumit Shekhar, Vishal M. Patel, Nasser M. Nasrabadi and Rama Chellappa, “Joint sparse representation for robust multimodal biometrics recognition,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 36, No. 1, pp. 113-126, Jan. 2014.

Honors and Awards

  • IEEE Fellow (2001)
  • ARL Fellow (1999)
  • SPIE Fellow (1997)

Professional Organizations

IEEE
SPIE
ARL