J. Jagannath, A. Jagannath, S. Furman, T. Gwin,"Deep Learning and Reinforcement Learning for Autonomous Unmanned Aerial Systems: Roadmap for Theory to Deployment" in Deep Learning for Unmanned Systems. Studies in Computational Intelligence, Koubaa A., Azar A.T. (eds), vol 984. Springer, Cham., 2021. [pdf][bibtex]
J. Jagannath, N. Polosky, A. Jagannath, F. Restuccia, T. Melodia, "Neural Networks for Signal Intelligence: Theory and Practice," in Machine Learning for Future Wireless Communications, F.‐L. Luo (Ed.). Wiley - IEEE Series, 2020, ISBN: 97811195622523. [pdf][bibtex]
A. Jagannath, J. Jagannath, "Embedding-Assisted Attentional Deep Learning for Real-World RF Fingerprinting of Bluetooth", IEEE Transactions on Cognitive Communications and Networking, 2023. [pdf][bibtex]
K. Ramezanpour, J. Jagannath, A. Jagannath, “Security and privacy vulnerabilities of 5G/6G and WiFi 6: Survey and research directions from a coexistence perspective”, Computer Networks (Elsevier), vol. 221, 109515, ISSN 1389-1286, 2023. [pdf][bibtex]
C. Farquhar, S. Kafle, K. Hamedani, A. Jagannath, J. Jagannath, "Marconi-Rosenblatt Framework for Intelligent Networks (MR-iNet Gym): For Rapid Design and Implementation of Distributed Multi-agent Reinforcement Learning Solutions for Wireless Networks", Computer Networks (Elsevier), vol. 222, 109489, ISSN 1389-1286, 2023. [pdf][bibtex]
A. Jagannath, J. Jagannath, PSPV Kumar, “A Comprehensive Survey on Radio Frequency (RF) Fingerprinting: Traditional Approaches, Deep Learning, and Open Challenges”, Computer Networks (Elsevier), vol. 219, 109455, ISSN 1389-1286, 2022. [pdf][bibtex]
K. Ramezanpour, J. Jagannath, “Intelligent Zero Trust Architecture for 5G/6G Networks: Principles, Challenges, and the Role of Machine Learning in the context of O-RAN”, Computer Networks (Elsevier), vol. 217, 109358, ISSN 1389-1286, 2022. [pdf][bibtex].
A. Jagannath, J. Jagannath, "Multi-task Learning Approach for Modulation and Wireless Signal Classification for 5G and Beyond: Edge Deployment via Model Compression", Physical Communications (Elsevier), vol. 54, 101793, ISSN 1874-4907, 2022. [pdf][bibtex]
J. Jagannath, A. Jagannath, J. Henney, T. Gwin, Z. Kane, N. Biswas, A. Drozd, "Design of Fieldable Cross-Layer Network using Embedded Software Defined Radios: Survey and Novel Architecture with Field Trials", Computer Networks (Elsevier), vol. 209, 108917, ISSN 1389-1286, 2022. [pdf][bibtex]
A. Jagannath, J.Jagannath, "Dataset for Modulation Classification and Signal Type Classification for Multi-task and Single Task Learning", Computer Networks (Elsevier), vol. 199,108441, ISSN 1389-1286, 2021.[pdf][bibtex]
A. Jagannath, J.Jagannath, T. Melodia, ''Redefining Wireless Communication for 6G: Signal Processing Meets Deep Learning with Deep Unfolding", IEEE Transactions on Artificial Intelligence, vol. 2, no. 6, pp. 528-536, Dec. 2021. [pdf][bibtex]
J. Jagannath, N. Polosky, A. Jagannath, F. Restuccia, T. Melodia, "Machine Learning for Wireless Communications in the Internet of Things: A Comprehensive Survey," Ad Hoc Networks (Elsevier) vol. 93, pp 101913, June 2019. [pdf] [bibtex]
J. Jagannath, S. Furman, A. Jagannath, L. Ling, A. Burger, A. Drozd, "HELPER: Heterogeneous Efficient Low Power Radio for Enabling Ad Hoc Emergency Public Safety Networks," Ad Hoc Networks (Elsevier) , vol. 89, pp 218-235, June 2019. [pdf][bibtex]
J. Jagannath, S. Furman, T. Melodia, A. Drozd, "Design and Experimental Evaluation of a Cross-Layer Deadline-Based Joint Routing and Spectrum Allocation Algorithm," IEEE Transactions on Mobile Computing, vol. 18, no. 8, pp. 1774-1788, August 2019. [pdf][bibtex]
N. Cen, J. Jagannath, S. Moretti, Z. Guan, T. Melodia, "LANET: Visible-Light Ad Hoc Network," Ad Hoc Networks (Elsevier), vol. 84, pp 107-123, March 2019. [pdf] [bibtex]
A. Jagannath, Z. Kane, J. Jagannath, “RF Fingerprinting Needs Attention: Multi-task Approach for Real-World WiFi and Bluetooth” in Proc. of IEEE Global Communications Conference (GLOBECOM), Rio de Janeiro, Brazil, December 2022. [pdf][bibtex]
J. Jagannath, K. Ramezanpour, A. Jagannath, "Digital Twin Virtualization with Machine Learning for IoT and Beyond 5G Networks: Research Directions for Security and Optimal Control", in Proc. of ACM Workshop on Wireless Security and Machine Learning (WiseML), San Antonio, Texas, USA May, 2022. [pdf][bibtex]
J. Jagannath, K. Hamedani, C. Farquhar, K. Ramezanpour, A. Jagannath, "MR-iNet Gym: Framework for Edge Deployment of Deep Reinforcement Learning on Embedded Software Defined Radio", in Proc. of ACM Workshop on Wireless Security and Machine Learning (WiseML), San Antonio, Texas, USA May, 2022. [pdf][bibtex] [Best Paper Award]
N. Polosky, BC. da Silva, M. Fiterau, J. Jagannath, "Constrained Offline Policy Optimization", in Proc. of the 39th International Conference on Machine Learning (ICML), Baltimore, MD, July, 2022. [pdf][bibtex]
A. Jagannath, J. Jagannath, Y. Wang, T. Melodia, "Deep neural network goes lighter: A case study of deep compression techniques on automatic RF modulation recognition for Beyond 5G networks" in Proc. of SPIE Defense and Commercial Sensing, Orlando, Florida, USA, May, 2022. [pdf][bibtex]
C. Farquhar, PSPV Kumar, A. Jagannath, J. Jagannath, "Distributed Transmission Control for Wireless Networks using Multi-Agent Reinforcement Learning" in Proc. of SPIE Defense and Commercial Sensing, Orlando, Florida, USA, May, 2022. [pdf][bibtex]
N. Polosky, T. Gwin, S. Furman, P. Barhanpurkar, J. Jagannath, "Machine Learning Subsystem for Autonomous Collision Avoidance on a small UAS with Embedded GPU", in Proc. IEEE International Workshop on Communication and Networking for Swarms Robotics, 2022. [pdf][bibtex]
J. Jagannath, A. Jagannath, J. Henney, N. Biswas, T. Gwin, Z. Kane, A. Drozd, "Fieldable Cross-Layer Optimized Embedded Software Defined Radio is Finally Here!", in Proc. of IEEE Conference on Military Communications (MILCOM), San Diego, CA, USA, Nov 2021. [pdf][bibtex]
K. Hamedani, L. Liu, J. Jagannath, Y. Yi, “Adversarial Classification of the Attacks on Smart Grids Using Game Theory and Deep Learning”, in Proc. of ACM Workshop on Wireless Security and Machine Learning (WiseML), Abu Dhabi, UAE, July 2021. [pdf][bibtex]
A. Jagannath, J. Jagannath. "Multi-task Learning Approach for Automatic Modulation and Wireless Signal Classification", in Proc. of IEEE International Conference on Communications (ICC), Montreal, Canada, June 2021. [pdf][bibtex][video]
A. Jagannath, J. Jagannath, “Jam-Guard: Low-Cost, Hand-held Device for First Responders to Detect and Localize Jammers” in Proc. of 14th International Conference on Signal Processing and Communication Systems (ICSPCS), Adelaide, Australia, Dec 2020. [pdf][bibex]
A. Jagannath, J. Jagannath, A. Drozd “High Rate-Reliability Beamformer Design for MIMO-OFDM System under Hostile Jamming”, in Proc. of 29th International Conference on Computer, Communication and Networks (ICCCN), Honolulu, HI, USA, Aug, 2020. [pdf][bibtex]
A. Jagannath, J. Jagannath, A. Drozd, “Towards Higher Spectral Efficiency: Rate-2 Full-Diversity Complex Space-Time Block Codes,” in Proc. of IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA, December 2019. [pdf][bibtex]
A. Jagannath, J. Jagannath, A. Drozd, “Artificial Intelligence-based Cognitive Cross-layer Decision Engine for Next-Generation Space Mission,” in Proc. of IEEE Cognitive Communication for Aerospace Applications (CCAA) Workshop, Cleveland, OH, June 2019. [pdf][bibtex]
J. Jagannath, T. Melodia, “VL-ROUTE: A Cross-Layer Routing Protocol for Visible Light Ad Hoc Network,” in Proc. of IEEE Symp. on a World of Wireless, Mobile, and Multimedia Networks (WoWMoM), Washington D.C., USA, June 2019. [pdf][bibtex]
J. Jagannath, S. Furman, A. Jagannath, A. Drozd, “Energy Efficient Ad Hoc Networking Devices for Off-the-Grid Public Safety Networks”, in Proc. of IEEE Consumer Communications & Networking Conference (CCNC), Las Vegas, NV, USA, January 2019. [pdf][bibtex]
A. Jagannath, J. Jagannath, B. Sheaffer, A. Drozd, “Developing a Low Cost, Portable Jammer Detection and Localization Device for First Responders”, in Proc. of IEEE Consumer Communications & Networking Conference (CCNC), Las Vegas, NV, USA, January 2019. [pdf][bibtex]
J. Jagannath, N. Polosky, D. O’Connor, L. Theagarajan, B. Sheaffer, S. Foulke, P. Varshney, “Artificial Neural Network based Automatic Modulation Classifier for Software Defined Radios,” in Proc. of IEEE International Conference on Communications (ICC), Kansas City, MO, USA, May 2018.[pdf][bibtex]
J. Jagannath, T. Melodia, "An Opportunistic Medium Access Control Protocol for Visible Light Ad Hoc Networks," in Proc. of International Conference on Computing, Networking and Communications (ICNC), Maui, HI, USA, March 2018.[pdf] [bibtex]
N. Polosky, J. Jagannath, D. O'Connor, H. Saarinen, S. Foulke, “Artificial Neural Network with Electroencephalogram Sensors for Brainwave Interpretation: Brain-Observer-Indicator Development Challenges,” in Proc. of 13th International Conference & Expo on Emerging Technologies for a Smarter World (CEWIT), Stony Brook, NY, USA, November 2017.[pdf] [bibtex]
J. Jagannath, D. O'Connor, N. Polosky, B. Sheaffer, L. N. Theagarajan, S. Foulke, P. K. Varshney, S. P. Reichhart, "Design and Evaluation of Hierarchical Hybrid Automatic Modulation Classifier using Software Defined Radios," in Proc. of IEEE Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, January 2017. [pdf] [bibtex]
J. Jagannath, T. Melodia, A. Drozd, "DRS: Distributed Deadline-Based Joint Routing and Spectrum Allocation for Tactical Ad-hoc Networks" in Proc. of IEEE Global Communications Conference (GLOBECOM), Washington D.C., USA, December 2016. [pdf][bibtex]
J. Jagannath, H. Saarinen, T. Woods, J. O’Brien, S. Furman, A. Drozd, T. Melodia, "COmBAT: Cross-layer Based Testbed with Analysis Tool Implemented Using Software Defined Radios," in Proc. of IEEE Conference on Military Communications (MILCOM), Baltimore, MD, USA, November 2016. [pdf] [bibtex]
T. Wimalajeewa, J. Jagannath, P. K. Varshney, A. L. Drozd, W. Su, "Distributed Asynchronous Modulation Classification Based on Hybrid Maximum Likelihood Approach," in Proc. of IEEE Conference on Military Communications (MILCOM) , Tampa, FL, USA, Oct 2015. [pdf] [bibtex]
J. Jagannath, H. M. Saarinen, A. L. Drozd, "Framework for Automatic Signal Classification Techniques (FACT) for Software Defined Radios," in IEEE Symposium on Computational Intelligence in Security and Defense Applications (CISDA) , Verona, NY, USA, May 2015. [pdf] [bibtex]
S. Foulke, J. Jagannath, A. L. Drozd, T. Wimalajeewa, P. K. Varshney, W. Su, "Multisensor Modulation Classification (MMC)," in Proc. of IEEE Conf. on Military Communications (MILCOM), Baltimore, MD, October 2014. [pdf] [bibtex]
A. L. Drozd, T. Arcuri, J. Jagannath, D. A. Pados, T. Melodia, E. Demirors, G. Sklivanitis, "Network Throughput Improvement in Cognitive Networks by Joint Optimization of Spectrum Allocation and Cross-layer Routing," in NATO Symposium on "Cognitive Radio and Future Network " (IST-123), The Hauge, The Netherlands, May 2014. [pdf] [bibtex]
J. Jagannath, A. Saji, H. Kulhandjian, Y. Sun, E. Demirors, T. Melodia, "A Hybrid MAC Protocol with Channel-dependent Optimized Scheduling for Clustered Underwater Acoustic Sensor Networks," in Proc. of ACM Conference on Underwater Networks and Systems (WUWNet), Kaohsiung, Taiwan, November 2013. [pdf] [bibtex]
J. Jagannath, "Energy efficient cluster based hybrid MAC protocol with channel dependent optimized intra-cluster scheduling," M.S. Thesis , Department of Electrical Engineering, State University of New York at Buffalo, May 2013. [bibtex]
J. Jagannath, "Cross-layer Optimized Networking for Next-Generation 5G Ad Hoc Networks," Ph.D. Dissertation , Department of Electrical and Computer Engineering, Northeastern University, August 2019. [pdf][bibtex]
Routing data through distributed communication network. U.S. Patent Number: US 10,721,162 B2. Patent Granted.
Vertebral assist spinal medical device. U.S. Patent Number US 10,966,757 B2. Patent Granted.
Apparatus and method for jammer resistant protocol stack design. U.S. Patent Number: US 11,115,090 B2. Patent Granted.
Rate-2 complex space-time block codes for 3×3 and 4×4 MIMO systems. U.S. Patent Number: US 11,271,681 B2. Patent Granted.
Transceiver with machine learning for generation of communication parameters and cognitive resource allocation: US 11,490,273 B2 Patent Granted.
Multi-task learning neural network framework for RF spectrum sensing and classification. April 2020. Patent Granted
Sensitivity enhancing emitter description technique using machine learning. US20230164572A1. Patent Pending
Machine learning framework for control of autonomous agent operating in dynamic environment. April 2020. Patent Pending.
Zero trust architecture for networks employing machine learning engines. April 2021. Patent Pending.
System and methodology for coexistence between wireless fidelity and cellular network. Aug 2021. Patent Pending.
Identifying Transponder Hardware or Waveform In Wireless Network Via Machine Learning Module. Oct 2022. Patent Pending.
Machine Learning System For Identifying And Countering Non-Friendly Radar Networks. Patent Pending
Distributed Authentication with Network Segmentation and Dynamic authorization for networks. Provisional Patent.
Signal Intelligence System to Integrate Spectrum Prediction with Emitter Classification and PNT. Provisional Patent.
Method And System To Evaluate Channel Occupancy Via Encoder-Decoder Network And Artificial Neural Network. Provisional Patent.