Anu Jagannath

Ph.D. in Electrical and Computer Engineering, 2024

Education

Ph.D. in Electrical and Computer Engineering - Northeastern University (2024)
M.S. in Electrical Engineering - University at Buffalo (2013)

Anu Jagannath earned her Ph.D. in Electrical and Computer Engineering from Northeastern University in 2024, working under the guidance of Dr. Tommaso Melodia. Her research interests encompassed MIMO communications, deep machine learning, adaptive signal processing, software defined radios, LPI/LPD communications, intelligent spectrum sensing, adaptive physical/cross layer techniques, and wireless sensor networks. She received her M.S. in Electrical Engineering from University at Buffalo in 2013, where she performed research on Medium Access Control protocols for underwater acoustic sensor networks on SM-75 modems. She is currently the Founding Associate Director of Marconi-Rosenblatt AI/ML Innovation Lab at ANDRO Computational Solutions, LLC, where she serves as Technical Lead and Lead developer in multiple RIF, SBIR/STTR efforts.

Publications

2022

Conference Papers

A. Jagannath, J. Jagannath, Y. Wang, and T. Melodia. “Deep neural network goes lighter: A case study of deep compression techniques on automatic RF modulation recognition for Beyond 5G networks.” Proc. of SPIE Defense and Commercial Sensing (2022)Conference

DOI

2021

Journals & Magazines

A. Jagannath, J. Jagannath, and T. Melodia. “Redefining Wireless Communication for 6G: Signal Processing Meets Deep Learning with Deep Unfolding.” IEEE Transactions on Artificial Intelligence (2021)Journal

DOI

2020

Journals & Magazines

A. Jagannath, J. Jagannath, and A. Drozd. “Breaking the Bound: Rate-2, Full Diversity, Orthogonal MIMO-STBC Transceiver Design.” arXiv preprint arXiv:2005.00382 (2020)Journal

DOI

Conference Papers

A. Jagannath, J. Jagannath, and A. Drozd}. “High Rate-Reliability Beamformer Design for MIMO-OFDM System under Hostile Jamming.” Proc. of 29th International Conference on Computer, Communication and Networks (ICCCN) (2020)Conference

DOI

2019

Journals & Magazines

J. Jagannath, S. Furman, A. Jagannath, L. Ling, A. Burger, and A. Drozd}. “HELPER: Heterogeneous Efficient Low Power Radio for Enabling Ad Hoc Emergency Public Safety Networks.” Ad Hoc Networks (Elsevier) (2019)Journal

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J. Jagannath, N. Polosky, A. Jagannath, F. Restuccia, and T. Melodia. “Machine Learning for Wireless Communicationsin the Internet of Things: A Comprehensive Survey.” Ad Hoc Networks (Elsevier) (2019)Journal

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Conference Papers

A. Jagannath, J. Jagannath, and A. Drozd}. “Towards Higher Spectral Efficiency: Rate-2 Full-Diversity Complex Space-Time Block Codes.” Proc. of IEEE Global Communications Conference (GLOBECOM) (2019)Conference

DOI

A. Jagannath, J. Jagannath, and A. Drozd}. “Artificial Intelligence-based Cognitive Cross-layer Decision Engine for Next-Generation Space Mission.” Proc. of IEEE Cognitive Communication for Aerospace Applications (CCAA) Workshop (2019)Conference

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J. Jagannath, S. Furman, A. Jagannath, and A. Drozd. “Energy Efficient Ad Hoc Networking Devices for Off-the-Grid Public Safety Networks.” Proc. of IEEE Consumer Communications & Networking Conference (CCNC) (2019)Conference

DOI

A. Jagannath, J. Jagannath, B. Sheaffer, A. Drozd}, and t. =. “Developing a Low Cost, Portable Jammer Detection and Localization Device for First Responders.” Proc. of IEEE Consumer Communications & Networking Conference (CCNC) (2019)Conference

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Book Chapters

J. Jagannath, N. Polosky, A. Jagannath, F. Restuccia, and T. Melodia. “Neural Networks for Signal Intelligence: Theory and Practice.” Machine Learning for Future Wireless Communications (2019)Book Chapter

DOI Link

2018

Conference Papers

A. Jagannath and A. Amanna. “Realizing Data driven and Hampel preprocessor based Adaptive filtering on a Software Defined Radio testbed: A USRP case Study.” Proc. of International Conference on Computing, Networking and Communications (ICNC) (2018)Conference

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