A. Abbasi, C. Woodall, J. Gamarra, C. Hui, N. Piccard, T. Ochuodho, S. de-Miguel, R. Sahay, S. Fei, A. Paquette, A. Paquette, H. Chen, A. Catlin, J. Liang, "Forest types outpaced tree species in centroid-based range shifts under global change," Frontiers in Ecology and Evolution, 2024.

R. Sahay, M. Zhang, D. J. Love, C. G. Brinton, "Defending Adversarial Attacks on Deep Learning-Based Power Allocation in Massive MIMO Using Denoising Autoencoders," IEEE Transactions on Cognitive Communications and Networking, 2023. 

R. Sahay, S. Nicoll, M. Zhang, T. Y. Yang, C. Joe-Wong, K. A. Douglas, C. G. Brinton, "Predicting Learner Interactions in Social Learning Networks: A Deep Learning Enabled Approach," IEEE/ACM Transactions on Networking, 2023. 

R. Sahay, J. Stubbs, C. Brinton, G. Birch, "An Uncertainty Quantification Framework for Counter Unmanned Aircraft Systems Using Deep Ensembles," in IEEE Sensors Journal, 2022. 

R. Sahay, S. Appadwedula, D. Love, and C. Brinton, "A Neural Network-Prepended GLRT Framework for Signal Detection Under Nonlinear Distortions," in IEEE Communications Letters, 2022. 

R. Sahay, C. Brinton, and D. Love, "A Deep Ensemble-Based Wireless Reciever Architecture for Mitigating Adversarial Attacks in Automatic Modulation Classification," in IEEE Transactions on Cognitive Communications and Networking, 2021.

R. Sahay and C. Brinton, "Robust Subject-Independent P300 Waveform Classification via Signal Pre-processing and Deep Learning," in IEEE Access, 2021. 

S. Kim, S. Shiveley, A. Douglas, Y. Zhang, R. Sahay, D. Adams, and J. Harley, "Efficient Storage and Processing of Large Guided Wave Datasets with Random Projections," in Structural Health Monitoring, 2020. 

K. Sivamani, R. Sahay, and A. E. Gamal, "Non-intrusive Detection of Adversarial Deep Learning Attacks via Observer Networks," in IEEE Letters of the Computer Society, 2020. 

M. Ebrahimi, R. Sahay, S. Hosseinalipour, and B. Akram, "Vision Paper: Advancing Mental Health in Education through Federated Learning and its Synergies with Broader Human-Centered Domains," in 2025 AAAI AI4EDU: AI for Education: Tools, Opportunities, and Risks in the Generative AI Era Workshop, Philadelphia, PA, Mar. 2025.

A. P. Hridi, R. Sahay, S. Hosseinalipour, and B. Akram, "Revolutionizing AI-Assisted Education with Federated Learning: A Pathway to Distributed, Privacy-Preserving, and Debiased Learning Ecosystems," in Proc. of AAAI 2024 Spring Symposium Series: Federated Learning on the Edge, Mar. 2024.

S. Wang, R. Sahay, C. G. Brinton, "How Potent are Evasion Attacks for Poisoning Federated Learning-Based Signal Classifiers?" in Proc. of IEEE International Conference on Communications (ICC), 2023. 

R. Sahay, G. C. Birch, J. J. Stubbs, and C. Brinton, "Uncertainty Quantification-based Unmanned Aircraft System Detection using Deep Ensembles" Proc. of Spring-2022 IEEE Vehicular Technology Conference, 2022. 

R. Sahay, D. Reis, J. Zollweg, and C. Brinton, "Hyperspectral Image Target Detection Using Deep Ensembles for Robust Uncertainty Quantification," in Proc. of IEEE Asilomar Conference on Signals, Systems, and Computers, 2021. 

R. Sahay, C. Brinton, and D. Love, "Frequency-based Automated Modulation Classification in the Presence of Adversaries," in Proc. of IEEE International Conference on Communications (ICC), 2021. 

R. Sahay, D. Love, and C. Brinton, "Robust Automatic Modulation Classification in the Presence of Adversarial Attacks," in Proc. of 2021 IEEE Conference of Information Science and Systems (CISS). 

R. Sahay, R. Mahfuz, and A. E. Gamal, "Combatting Adversarial Attacks through Denoising and Dimenisonality Reduction: A Cascaded Autoencdoer Approach," in Proc. of 2019 IEEE Conference of Information Science and Systems (CISS).