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publications
Spatial Interference Cancellation for Simultaneous Wireless and Information Power Transfer
Published in U.S. Patent and Trademark Office, 2020
Recommended citation: S. Gupta, E. Ghaderi, S. Shekhar, S. Venkatasubramanian and A. S. Ramani, "Spatial Interference Cancellation for Simultaneous Wireless and Information Power Transfer," U.S. Patent 10,804,988, Oct. 13, 2020. https://patents.google.com/patent/US10804988B2/en
GRADE-AO: Towards Near-Optimal Spatially-Coupled Codes With High Memories
Published in IEEE International Symposium on Information Theory (ISIT), 2021
Recommended citation: S. Yang, A. Hareedy, S. Venkatasubramanian, R. Calderbank and L. Dolecek, "GRADE-AO: Towards Near-Optimal Spatially-Coupled Codes With High Memories," IEEE International Symposium on Information Theory (ISIT), Melbourne, Australia, 2021, pp. 587-592, doi: 10.1109/ISIT45174.2021.9517931. https://doi.org/10.1109/ISIT45174.2021.9517931
Toward Data-Driven STAP Radar
Published in IEEE Radar Conference (RadarConf), 2022
Recommended citation: S. Venkatasubramanian, C. Wongkamhthong, M. Soltani, B. Kang, S. Gogineni, A. Pezeshki, M. Rangaswamy and V. Tarokh, "Toward Data-Driven STAP Radar," IEEE Radar Conference (RadarConf), New York City, NY, USA, 2022, pp. 1-5, doi: 10.1109/RadarConf2248738.2022.9764354. https://doi.org/10.1109/RadarConf2248738.2022.9764354
Subspace Perturbation Analysis for Data-Driven Radar Target Localization
Published in IEEE Radar Conference (RadarConf), 2023
Recommended citation: S. Venkatasubramanian, S. Gogineni, B. Kang, A. Pezeshki, M. Rangaswamy and V. Tarokh, "Subspace Perturbation Analysis for Data-Driven Radar Target Localization," IEEE Radar Conference (RadarConf), San Antonio, TX, USA, 2023, pp. 1-5, doi: 10.1109/RadarConf2351548.2023.10149781. https://doi.org/10.1109/RadarConf2351548.2023.10149781
Data-Driven Target Localization: Benchmarking Gradient Descent Using the Cramer-Rao Bound
Published in arXiv preprint, 2024
Recommended citation: S. Venkatasubramanian, S. Gogineni, B. Kang, M. Rangaswamy, "Data-Driven Target Localization: Benchmarking Gradient Descent Using the Cramer-Rao Bound," arXiv preprint arXiv:2401.11176, 2024, doi: 10.48550/arXiv.2401.11176. https://doi.org/10.48550/arXiv.2401.11176
Random Linear Projections Loss for Hyperplane-Based Optimization in Neural Networks
Published in The 40th Conference on Uncertainty in Artificial Intelligence (UAI), 2024
Recommended citation: S. Venkatasubramanian*, A. Aloui* and V. Tarokh, "Random Linear Projections Loss for Hyperplane-Based Optimization in Neural Networks," The 40th Conference on Uncertainty in Artificial Intelligence, 2024, doi: 10.48550/arXiv.2311.12356 . https://proceedings.mlr.press/v244/venkatasubramanian24a.html
RASPNet: A Benchmark Dataset for Radar Adaptive Signal Processing Applications
Published in arXiv preprint, 2024
Recommended citation: S. Venkatasubramanian, B. Kang, A. Pezeshki, M. Rangaswamy and V. Tarokh, "RASPNet: A Benchmark Dataset for Radar Adaptive Signal Processing Applications," arXiv preprint, 2024, doi: 10.48550/arXiv.2406.09638. https://doi.org/10.48550/arXiv.2406.09638
Data-Driven Target Localization Using Adaptive Radar Processing and Convolutional Neural Networks
Published in IET Radar, Sonar & Navigation, 2024
Recommended citation: S. Venkatasubramanian, S. Gogineni, B. Kang, A. Pezeshki, M. Rangaswamy and V. Tarokh, "Data-Driven Target Localization Using Adaptive Radar Processing and Convolutional Neural Networks," IET Radar, Sonar & Navigation, 2024, doi: 10.1049/rsn2.12600. https://doi.org/10.1049/rsn2.12600
Steinmetz Neural Networks for Complex-Valued Data
Published in The 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Recommended citation: S. Venkatasubramanian, A. Pezeshki and V. Tarokh, "Steinmetz Neural Networks for Complex-Valued Data," The 28th International Conference on Artificial Intelligence and Statistics, 2025, doi: 10.48550/arXiv.2409.10075. https://doi.org/10.48550/arXiv.2409.10075
An Information-Theoretic Lower Bound on the Generalization Error of Autoencoders
Published in Transactions on Machine Learning Research (TMLR), 2025
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Recommended citation: S. Venkatasubramanian*, S. Moushegian*, A. Aloui* and V. Tarokh, "An Information-Theoretic Lower Bound on the Generalization Error of Autoencoders," Transactions on Machine Learning Research, 2025. https://openreview.net/forum?id=0esF0M467w
Learn2Mix: Training Neural Networks Using Adaptive Data Integration
Published in The 39th Conference on Neural Information Processing Systems (NeurIPS 2025), 2025
Recommended citation: S. Venkatasubramanian and V. Tarokh, "Learn2Mix: Training Neural Networks Using Adaptive Data Integration," The 39th Conference on Neural Information Processing Systems, 2025, doi: 10.48550/arXiv.2412.16482. https://doi.org/10.48550/arXiv.2412.16482
Odyssey: Reconstructing Evolution Through Emergent Consensus in the Global Proteome
Published in bioRxiv preprint, 2025
Recommended citation: A. Singhal*, S. Venkatasubramanian*, S. Moushegian*, S. Strutt, M. Lin, and C. Lee*, "Odyssey: Reconstructing Evolution Through Emergent Consensus in the Global Proteome," bioRxiv 2025.10.15.682677, 2025. https://www.biorxiv.org/content/10.1101/2025.10.15.682677v1
talks
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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