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 ProcessingIEEE 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

Paria Jeihouni, Omid Dehzangi, Annahita Amireskandari, Ali Rezai, Nasser M. Nasrabadi, “MultiSDGAN: Translation of OCT Images to Superresolved Segmentation Labels Using Multi-Discriminators in Multi-Stages,” IEEE Journal of Biomedical and Health Informatics, Sept. 13, 2021.

Domenick D. Poster, Shuowen Hu, Nathan J. Short, Benjamin S. Riggan, and Nasser M. Nasrabadi, “Visible-to-Thermal Transfer Learning for Facial Landmark Detection,” IEEE Access, vol. 8, issue 1, pp. 82306-82319, Dec. 2021.

Sertac Arisoy, Nasser M. Nasrabadi, and Koray Kayabol “Unsupervised Pixel-wise Hyperspectral Anomaly Detection via Autoencoding Adversarial Networks,” IEEE Geoscience and Remote Sensing Letters, vol. 0, no. 0, pp, 2021.

Seyed Mehdi Iranmanesh, Nasser M. Nasrabadi, “HGAN: Hybrid Generative Adversarial Network,” Journal of Intelligent & Fuzzy Systems, Vol. 41-1, Feb. 2021.

Veeru Talreja, Matthew Valenti, and Nasser Nasrabadi, “Deep Hashing for Secure Multimodal Biometrics,” IEEE Transactions on Information Forensics and Security, vol. 16, pp. 1306-1321, Oct. 22, 2021. 10.1109/TIFS.2020.3033189

Moktari Mostofa, Syeda Nyma Ferdous, Benjamin S. Riggan, and Nasser M. Nasrabadi, “Joint-SRVDNet: Joint Super-Resolution and Vehicle Detection Network,” IEEE Access, May 2020.

Fariborz Taherkhani, Veeru Talreja, Matthew Valenti, and Nasser M. Nasrabadi, “Error Corrected Margin-Based Deep Cross-Modal Hashing for Facial Image Retrieval, IEEE Transactions o on Biometrics, Behavior, and Identity Science, Dec. 25, 2019.

Seyed Mehdi Iranmanesh, Benjamin Riggan, Shuowen Hu, Nasser M. Nasrabadi, “Coupled Generative Adversarial Network for Heterogeneous Face Recognition,” Image and Vision Computing, vol. 94, February 2020.

Nasser M. Nasrabadi, “Deep Target: An Automatic Target Recognition Using Deep Convolutional Neural Networks,” IEEE Transactions on Aerospace and Electronic Systems, vol. 55, no. 6, pp. 2687-2697, Dec. 2019

Xiaoxia Sun, Nasser M. Nasrabadi and Trac D. Tran, “Supervised Deep Sparse Coding Networks for Image Classification,” IEEE Trans. on Image Processing, vol. 29, no. 7, pp. 405-418, July 17, 2019.

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