Nasser M. Nasrabadi

Timeline

1. 1980–1984

   Degrees from Imperial College

   He earns his B.Sc. in July 1980 and his Ph.D. in October 1984, both in electrical engineering, at the Imperial College of Science and Technology, University of London.

2. 1996–1998

   Neural networks for images and targets

   In October 1996, the Proceedings of the IEEE publishes “Neural Network Architectures for Vector Prediction,” which he coauthors with Syed A. Rizvi and L-C Wang. In 1998, IEEE Transactions on Image Processing carries two of his papers with L-C Wang: “A Modular Neural Network Vector Predictor Image Coding,” and “Modular Neural Network Recognition of Targets in FLIR Imagery,” the latter with Sandor Der.

3. 1997–2001

   Fellowships at SPIE, ARL and IEEE

   He becomes a Fellow of SPIE in 1997, a Fellow of the US Army Research Laboratory in 1999 and a Fellow of the IEEE in 2001.

4. 2005–2006

   Kernel methods for hyperspectral targets

   With Heesung Kwon, he publishes the Kernel RX-Algorithm, a nonlinear anomaly detector for hyperspectral imagery, in IEEE Transactions on Geoscience and Remote Sensing in February 2005. Their “Kernel Matched Subspace Detectors for Hyperspectral Target Detection” follows in IEEE Transactions on Pattern Analysis and Machine Intelligence in February 2006.

5. 2011–2018

   Sparse representation and an award

   In June 2011, he publishes “Sparse Representation for Target Detection in Hyperspectral Images” with Yi Chen and Trac D. Tran in the IEEE Journal of Selected Topics in Signal Processing. Their January 2013 paper on hyperspectral image classification with kernel sparse methods receives the Highest Impact Paper Award 2018 from IEEE Transactions on Geoscience and Remote Sensing in July 2018.

6. 2015–2016

   Joining West Virginia University

   In July 2015, West Virginia University announces that he will join its Lane Department of Computer Science and Electrical Engineering as a professor; he is a former senior research scientist at the US Army Research Laboratory with earlier appointments at Johns Hopkins University, the State University of New York at Buffalo and Worcester Polytechnic Institute. Department chair Brian Woerner cites his contributions to vector quantization for image compression and expects him to bring senior leadership to the faculty in biometrics and image processing. He founds the Biometrics & Identity Innovation Center and the Cognitive Computing Laboratory in 2016.

7. 2019–2023

   Deep networks for target recognition

   In December 2019, IEEE Transactions on Aerospace and Electronic Systems publishes his “Deep Target: An Automatic Target Recognition Using Deep Convolutional Neural Networks.” In 2023, he coauthors “Deep Transductive Transfer Learning for Automatic Target Recognition” with Shoaib M. Sami and Raghuveer Rao, which builds a classifier for a target domain with no labeled data using a CycleGAN and wins a Best Paper Award at SPIE Defense & Commercial Sensing.

8. As of October 2026

   Professor at Oakland University

   A US patent for fingerprint distortion rectification and restoration with deep convolutional neural networks, listing him, Jeremy Dawson and Ali Dabouei, is granted in 2024. He is a professor in the Department of Computer Science and Engineering at Oakland University and an adjunct professor in the Department of Electrical and Computer Engineering at Johns Hopkins University's Whiting School of Engineering.