Realizing Data driven and Hampel preprocessor based Adaptive filtering on a Software Defined Radio testbed: A USRP case Study. - Anu Jagannath; Ashwin Amanna (ICNC, 2018)

Energy Efficient Ad Hoc Networking Devices for Off-the-Grid Public Safety Networks. - Jithin Jagannath; Sean Furman; Anu Jagannath; Andrew L. Drozd (CCNC, 2019)

Developing a Low Cost, Portable Jammer Detection and Localization Device for First Responders. - Anu Jagannath; Jithin Jagannath; Brendan Sheaffer; Andrew L. Drozd (CCNC, 2019)

Towards Higher Spectral Efficiency: Rate-2 Full-Diversity Complex Space-Time Block Codes. - Anu Jagannath; Jithin Jagannath; Andrew L. Drozd (GLOBECOM, 2019)

HELPER: Heterogeneous Efficient Low Power Radio for enabling ad hoc emergency public safety networks. - Jithin Jagannath; Sean Furman; Anu Jagannath; Luther Ling; Andrew Burger; Andrew L. Drozd (Ad Hoc Networks, 2019)

Machine learning for wireless communications in the Internet of Things: A comprehensive survey. - Jithin Jagannath; Nicholas Polosky; Anu Jagannath; Francesco Restuccia 001; Tommaso Melodia (Ad Hoc Networks, 2019)

High Rate-Reliability Beamformer Design for 2×2 Mimo-OFDM System Under Hostile Jamming. - Anu Jagannath; Jithin Jagannath; Andrew L. Drozd (ICCCN, 2020)

Jam-Guard: Low-Cost, Hand-held Device for First Responders to Detect and Localize Jammers. - Anu Jagannath; Jithin Jagannath (ICSPCS, 2020)

Redefining Wireless Communication for 6G: Signal Processing Meets Deep Learning. - Anu Jagannath; Jithin Jagannath; Tommaso Melodia (CoRR, 2020)

High rate-reliability beamformer design for 2x2 MIMO-OFDM system under hostile jamming. - Anu Jagannath; Jithin Jagannath; Andrew L. Drozd (CoRR, 2020)

Deep Learning and Reinforcement Learning for Autonomous Unmanned Aerial Systems: Roadmap for Theory to Deployment. - Jithin Jagannath; Anu Jagannath; Sean Furman; Tyler Gwin (CoRR, 2020)

Multi-task Learning Approach for Automatic Modulation and Wireless Signal Classification. - Anu Jagannath; Jithin Jagannath (ICC, 2021)

Fieldable Cross-Layer Optimized Embedded Software Defined Radio is Finally Here! - Jithin Jagannath; Anu Jagannath; Justin Henney; Noor Biswas; Tyler Gwin; Zackary Kane; Andrew L. Drozd (MILCOM, 2021)

Dataset for modulation classification and signal type classification for multi-task and single task learning. - Anu Jagannath; Jithin Jagannath (Comput. Networks, 2021)

Redefining Wireless Communication for 6G: Signal Processing Meets Deep Learning With Deep Unfolding. - Anu Jagannath; Jithin Jagannath; Tommaso Melodia (IEEE Trans. Artif. Intell., 2021)

Deep Learning and Reinforcement Learning for Autonomous Unmanned Aerial Systems: Roadmap for Theory to Deployment. - Jithin Jagannath; Anu Jagannath; Sean Furman; Tyler Gwin (Deep Learning for Unmanned Systems, 2021)

RF Fingerprinting Needs Attention: Multi-task Approach for Real-World WiFi and Bluetooth. - Anu Jagannath; Zackary Kane; Jithin Jagannath (GLOBECOM, 2022)

MR-iNet Gym: Framework for Edge Deployment of Deep Reinforcement Learning on Embedded Software Defined Radio. - Jithin Jagannath; Kian Hamedani; Collin Farquhar; Keyvan Ramezanpour; Anu Jagannath (WiseML@WiSec, 2022)

Digital Twin Virtualization with Machine Learning for IoT and Beyond 5G Networks: Research Directions for Security and Optimal Control. - Jithin Jagannath; Keyvan Ramezanpour; Anu Jagannath (WiseML@WiSec, 2022)

Design of fieldable cross-layer optimized network using embedded software defined radios: Survey and novel architecture with field trials. - Jithin Jagannath; Anu Jagannath; Justin Henney; Tyler Gwin; Zackary Kane; Noor Biswas; Andrew L. Drozd (Comput. Networks, 2022)

A comprehensive survey on radio frequency (RF) fingerprinting: Traditional approaches, deep learning, and open challenges. - Anu Jagannath; Jithin Jagannath; Prem Sagar Pattanshetty Vasanth Kumar (Comput. Networks, 2022)

Deep neural network goes lighter: A case study of deep compression techniques on automatic RF modulation recognition for Beyond 5G networks. - Anu Jagannath; Jithin Jagannath; Yanzhi Wang; Tommaso Melodia (CoRR, 2022)

Distributed Transmission Control for Wireless Networks using Multi-Agent Reinforcement Learning. - Collin Farquhar; Prem Sagar Pattanshetty Vasanth Kumar; Anu Jagannath; Jithin Jagannath (CoRR, 2022)

Multi-task learning approach for modulation and wireless signal classification for 5G and beyond: Edge deployment via model compression. - Anu Jagannath; Jithin Jagannath (Phys. Commun., 2022)

RF-Fingerprint-BT-IoT: Real-world Frequency Hopping Bluetooth dataset from IoT devices for RF fingerprinting. - Anu Jagannath; Jithin Jagannath (IEEE DataPort, 2022)

Real-world Commercial WiFi and Bluetooth Dataset for RF Fingerprinting. - Anu Jagannath; Zackary Kane; Jithin Jagannath (IEEE DataPort, 2022)

Marconi-Rosenblatt Framework for Intelligent Networks (MR-iNet Gym): For Rapid Design and Implementation of Distributed Multi-agent Reinforcement Learning Solutions for Wireless Networks. - Collin Farquhar; Swatantra Kafle; Kian Hamedani; Anu Jagannath; Jithin Jagannath (Comput. Networks, 2023)

Security and privacy vulnerabilities of 5G/6G and WiFi 6: Survey and research directions from a coexistence perspective. - Keyvan Ramezanpour; Jithin Jagannath; Anu Jagannath (Comput. Networks, 2023)

Generalization of Deep Reinforcement Learning for Jammer-Resilient Frequency and Power Allocation. - Swatantra Kafle; Jithin Jagannath; Zackary Kane; Noor Biswas; Prem Sagar Pattanshetty Vasanth Kumar; Anu Jagannath (IEEE Commun. Lett., 2023)

Embedding-Assisted Attentional Deep Learning for Real-World RF Fingerprinting of Bluetooth. - Anu Jagannath; Jithin Jagannath (IEEE Trans. Cogn. Commun. Netw., 2023)

Bluetooth and WiFi Dataset for Real World RF Fingerprinting of Commercial Devices. - Anu Jagannath; Zackary Kane; Jithin Jagannath (IEEE Commun. Mag., 2024)