Dr. Vincent J. Amuso received his B.S. in Electrical Engineering from Western New England College, his M.S. in Electrical Engineering from Syracuse University, and his Ph.D. in Electrical Engineering from the Rensselaer Polytechnic Institute. His Ph.D. research used classical signal processing techniques married with stochastic modeling and neural networks, to successfully develop an algorithm used to separate mixed speech. The three main components of the algorithm include multiple layer neural networks, maximum likelihood deconvolution and Bayesian inference networks.
Dr. Amuso was employed by the Rome Air Development Center as an electronics engineer in the Advanced Concepts and Analysis Branch. His responsibilities included the investigation of the feasibility of state-of-the-art concepts in the area of radar signal processing. He was employed by the General Electric Co. as an Electrical/Systems engineer where his responsibilities included the design of hardware for airborne and ground-based radar and infrared systems. As a systems engineer he was responsible for the application and implementation of a multiple model Extended Kalman Filter (EKF) in modified spherical coordinates to determine the time to intercept of a target by using angle only measurements. He was also responsible for the design and development of a missile launch detection algorithm, the design and development of a discrimination algorithm used to identify helicopters by a ground-based infrared detection system, and the modeling and simulation of infrared atmospheric and target phenomenology. Dr. Amuso was employed as professor at Mohawk Valley Community College. The Sensis Corporation employed him as a senior radar systems engineer where his responsibilities included system requirement derivation, analysis and flow down, and the generation of software and hardware requirements specifications. He also had responsible for the development and implementation of an offline signal and track processor (MATLAB based) used to analyze collected coherent radar data. The signal processing functionality included waveform design, pulse compression, digital demodulation, moving target indicator (MTI) processing, Doppler processing, multiple time around processing and monopulse processing. The track processing functionality included clutter and weather map generation, same scan and multi-scan correlation. He was also responsible for the development and implementation of a Bayesian Inference Network technique used to reduce false alarm returns caused by anomalous propagation and turbulent clutter.
Dr. Amuso was the head of the Electrical Engineering Department from 2006 through 2009. He now teaches courses in the areas of signal processing and communications systems. He also delivers courses in the areas of neural networks and evolutionary computation techniques applied to radar and acoustic systems. He performs research in the design and analysis of deep Ground Penetrating Radar (GPR) systems as well as three-dimensional SAR target modeling. He also performs research in the area of speech signal processing. Dr. Amuso is actively working both as a researcher and consultant in the area of Waveform Diversity & Design and Ultra Narrowband RF Tomography with the Air Force Research Laboratory. He is one of the founding co-chairman of the first International Waveform Diversity & Design conference (2004), and has co-authored and co-edited the seminal book in the area of Waveform Diversity & Design. Dr. Amuso has authored or co-authored several papers in the areas of multi-mission waveform design and deep GPR target modeling.
· Wicks, Mokole, Blunt, Schneible & Amuso, Principles of Waveform Diversity and Design, SCITECH Publishing, Raleigh, NC, 2010.
· L. Garcia, E. Saber, S. Vantaram, V. Amuso, M. Shaw and R. Bhaskar, “Automatic Image Segmentation by Dynamic Region Growth and Multi-resolution Merging”, IEEE Transactions on Image Processing, Vol. 18, No. 10, Oct. 2009.
· Ciccarelli, S.M.; Amuso, V.J.; “MEMS Tomographic Imaging System Simulation”; Aerospace and Electronic Systems Magazine, IEEE, Volume 24, Issue 7, July 2009 Page(s):32 – 35.
· Steven Ciccarelli, Vincent J. Amuso, “Simulation of the front-end of a MEMS based Ultra Narrow Band Tomographic Imaging System”; Fourth International Conference on Waveform Diversity and Design, Orlando, Florida, February 2009.
· Vincent J. Amuso, Jason Enslin, “The Strength Pareto Evolutionary Algorithm 2
· (SPEA2) Applied to Simultaneous Multimission Waveform Design”, Third International Conference on Waveform Diversity and Design, Pisa, Italy, June 2007.