Impact of power spread constraints on a multiuser detection enabled ad hoc network. - Scott Kuzdeba; Joseph Farkas; Brandon Hombs (MILCOM, 2011)

Prototype implementation of a visual communication system employing video imagery. - Scott Kuzdeba; Alexander M. Wyglinski; Brandon Hombs (CCNC, 2013)

Modulation recognition using hierarchical deep neural networks. - Krishna Karra; Scott Kuzdeba; Josh Petersen (DySPAN, 2017)

Performance Metrics for Cognitive Electronic Warfare - Electronic Support Measures. - Scott Kuzdeba; Andrew Radlbeck; Matthew Anderson (MILCOM, 2018)

Kalman Filter Changepoint Detection and Trend Characterization. - Scott Kuzdeba; Brandon Hombs; Jeremy D. Greenlee; Frank H. Guenther (MLSP, 2019)

Dilated Causal Convolutional Model For RF Fingerprinting. - Josh Robinson; Scott Kuzdeba; James Stankowicz; Joseph M. Carmack (CCWC, 2020)

RF Waveform Synthesis Guided by Deep Reinforcement Learning. - T. Scott Brandes; Scott Kuzdeba; Jessee McClelland; Neil Bomberger; Andrew Radlbeck (WIFS, 2020)

RF Fingerprinting with Dilated Causal Convolutions-An Inherently Explainable Architecture. - Scott Kuzdeba; Joseph M. Carmack; Josh Robinson (ACSCC, 2021)

RiftNet Reconstruction Model for Radio Frequency Domain Waveform Representation and Synthesis. - Joseph M. Carmack; Scott Kuzdeba (AIIoT, 2021)

Transfer Learning with Radio Frequency Signals. - Scott Kuzdeba; Josh Robinson; Joseph M. Carmack (CCNC, 2021)

RiftNet: Radio Frequency Classification for Large Populations. - Josh Robinson; Scott Kuzdeba (CCNC, 2021)

Novel device detection using RF fingerprints. - Josh Robinson; Scott Kuzdeba (CCWC, 2021)

Unsupervised Emitter Clustering through Deep Manifold Learning. - James Stankowicz; Scott Kuzdeba (CCWC, 2021)

Neural Network Signal Processing for LTE Receiver Application. - Josh Robinson; Joseph M. Carmack; Amit Bhatia; John Majewski; Scott Kuzdeba; Joseph Farkas; Brandon Hombs; Thomas Koch (DySPAN, 2021)

Neural Network Generative Models for Radio Frequency Data. - Joseph M. Carmack; Amit Bhatia; Josh Robinson; John Majewski; Scott Kuzdeba (UEMCON, 2021)

Multi-Agent Reinforcement Learning Approaches to RF Fingerprint Enhancement. - Joseph M. Carmack; Steve Schmidt; Scott Kuzdeba (WiseML@WiSec, 2021)

RiftNeXt™: Explainable Deep Neural RF Scene Classification. - Steve Schmidt; James Stankowicz; Joseph M. Carmack; Scott Kuzdeba (WiseML@WiSec, 2021)

FPGA Implementation of Radio Frequency Neural Networks. - Amit Bhatia; Josh Robinson; Joseph M. Carmack; Scott Kuzdeba (CCWC, 2022)

Data-Centric Approaches to Radio Frequency Machine Learning. - Scott Kuzdeba; Josh Robinson (MILCOM, 2022)

Systems View to Designing RF Fingerprinting for Real-World Operations. - Scott Kuzdeba; Josh Robinson; Joseph M. Carmack; David Couto (WiseML@WiSec, 2022)

A Conditional Analysis of RF ML Latent Features. - Scott Kuzdeba; Josh Robinson (MILCOM, 2023)

Federated Learning of Things - Expanding the Heterogeneity in Federated Learning. - Scott Kuzdeba (AAAI Spring Symposia, 2024)

Demonstrating Confidence in Radio Frequency Machine Learning Systems. - Matthew Judah; Scott Kuzdeba (SiPS, 2024)