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Lean Neural Networks for Autonomous Radar Waveform Design

Published in Sensors, 2022

Recommended citation: Baietto, A., Boubin, J., Farr, P., Bihl, T. J., Jones, A. M., & Stewart, C. (2022). Lean Neural Networks for Autonomous Radar Waveform Design. Sensors, 22(4), 1317. https://doi.org/10.3390/s22041317
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Lean Neural Networks for Real-time Embedded Spectral Notching Waveform Design

Published in IEEE 31st International Symposium on Industrial Electronics, 2022

Recommended citation: A. Baietto, J. Boubin, P. Farr and T. J. Bihl, "Lean Neural Networks for Real-time Embedded Spectral Notching Waveform Design," 2022 IEEE 31st International Symposium on Industrial Electronics (ISIE), Anchorage, AK, USA, 2022, pp. 1121-1126, doi: 10.1109/ISIE51582.2022.9831772.
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Dataset Augmentation for Robust Spiking Neural Networks

Published in IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, 2023

Recommended citation: A. Baietto, C. Stewart and T. J. Bihl, "Dataset Augmentation for Robust Spiking Neural Networks," in 2023 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C), Toronto, ON, Canada, 2023, pp. 116-121, doi: 10.1109/ACSOS-C58168.2023.00050.
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METHOD OF ANALYZING AND CORRECTING A DYNAMIC WAVEFORM USING MULTIVARIATE ERROR LOSS FUNCTIONS

Published Jul. 25, 2024

Patent No.: US 2024/0249139 A1
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SYSTEMS AND METHODS FOR TRAINING NEURAL NETWORKS

Filed Nov. 11, 2024. Patent pending.

Patent Application No.: 63/718,921

Generative Data for Neuromorphic Computing

Published in 58th Hawaii International Conference on System Sciences, 2025

Recommended citation: A. Baietto and T. J. Bihl, "Generative Data for Neuromorphic Computing," in 58th Hawaii International Conference on System Sciences (HICSS), Big Island, HI, USA, 2025, pp. 7246-7255, https://hdl.handle.net/10125/109719.
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METHOD OF ANALYZIING AND CORRECTING A COMPLEX WAVEFORM BY REAL AND IMAGINARY PARTITIONING AND RECOMBINATION

Published Jan. 16, 2025

Patent No.: US 2025/0020775 A1
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Dataset assembly for training Spiking Neural Networks

Published in Neurocomputing, 2025

Recommended citation: Baietto, A., Bihl, T. J., & Stewart, C. (2025). Dataset assembly for training Spiking Neural Networks. Neurocomputing, 622, 129207. https://doi.org/10.1016/j.neucom.2024.129207
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Lean Neural Networks for Real-time Embedded Spectral Notching Waveform Design

Published: June 03, 2022

Toward Robust Spiking Neural Networks

Published: August 02, 2023

Dataset Augmentation for Robust Spiking Neural Networks

Published: September 28, 2023

Data-Aware Tuning of Deep Learning Models

Published: December 05, 2023

Data-Aware Tuning of Deep Learning Models

Published: November 22, 2024

Generative Data for Neuromorphic Computing

Published: January 09, 2025

CSE 2431 Systems II - Introduction to Operating Systems (Fall 2021)

Undergraduate Course, The Ohio State University, Department of Computer Science and Engineering, 2021

CSE 2431 Systems II - Introduction to Operating Systems (Spring 2022)

Undergraduate Course, The Ohio State University, Department of Computer Science and Engineering, 2022

CSE 2431 Systems II - Introduction to Operating Systems (Spring 2023)

Undergraduate Course, The Ohio State University, Department of Computer Science and Engineering, 2023

Substitue for Jaimie Kelley

CSE 2431 Systems II - Introduction to Operating Systems (Fall 2023)

Undergraduate Course, The Ohio State University, Department of Computer Science and Engineering, 2023

CSE 2431 Systems II - Introduction to Operating Systems (Spring 2024)

Undergraduate Course, The Ohio State University, Department of Computer Science and Engineering, 2024

CSE 2421 Systems I - Introduction to Low-Level Programming and Computer Organization (Fall 2024)

Undergraduate Course, The Ohio State University, Department of Computer Science and Engineering, 2024

Substitue for Janis Jones (3 sections)