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Principal Investigator (Collaborative PIs: Dr. Shiwen Mao at Auburn University),“Collaborative Research: NSF-MeitY: CNS Core: Small: Learning-Assisted Integrated Sensing, Communication and Security for 6G UAV Networks”, NSF, $300,000, 10/1/2024 - 9/30/2027. The total amount of the grant is nearly $600,000.
Principal Investigator (Collaborative PIs: Dr. Shiwen Mao at Auburn University, Dr. Harrison Bai at John Hopkins University, and Dr. Zhicheng Jiao at Rhode Island Hospital/Brown University),“Collaborative Research: SCH: AI-driven RFID Sensing for Smart Health Applications”, NSF, $300,000, 08/15/2023 - 7/31/2027. The total amount of the grant is nearly $1.2M.
Principal Investigator (Collaborative PIs: Dr. Shiwen Mao at Auburn University, and Guanqun Cao at Michigan State University),“Collaborative Research: IMR: MM-1A: Functional Data Analysis-aided Learning Methods for Robust Wireless Measurements”, NSF, $200,000, 10/1/2023 - 9/30/2026. The total amount of the grant is nearly $600,000.
Principal Investigator (Collaborative PIs: Dr. Shiwen Mao at Auburn University, Dr. Slobodan Vucetic and Dr. Jie Wu at Temple University), “Collaborative Research: BPC Supplement: Data Augmentation and Adaptive Learning for Next Generation Wireless Spectrum Systems”, NSF, $54,823.00, 10/1/2021 - 9/30/2024. The total amount of the grant is nearly $240,000.
Principal Investigator (Collaborative PIs: Dr. Shiwen Mao at Auburn University, Dr. Slobodan Vucetic and Dr. Jie Wu at Temple University),“Collaborative Research: CNS Core: Medium: Data Augmentation and Adaptive Learning for Next Generation Wireless Spectrum Systems”, NSF, $279,946, 10/1/2021 - 9/30/2024. The total amount of the grant is nearly $1.2M.
Principal Investigator, “CRII: CNS: RUI: Exploiting Robust Deep Learning Framework for Wireless Localization Systems in Adversarial IoT Environments”, NSF, $174,999, 7/1/2021 - 6/30/2024.
Senior Personnel, “ NSF REU SITE: ASSET: Advanced Secured Sensor Enabling Technologies”, PI (Niki Pissinou), NSF, $405,000.00, 03/1/2023-2/28/2026.
Trustworthy AI (e.g., Robustness, Privacy, Explainability, Fairness, and Adaptation) in Wireless, Smart Health, LLM, HCI, and other IoT Systems
Generative AI, Multimodal AI (e.g., Vision, Audio, Text, Sensors), and Edge AI for Wireless, Smart Health, LLM, HCI, Underwater, Environmental Monitoring, Autonomous Car/Drone/Robot, AR/VR/MR, and Digital Twin
AI-driven IoT Security in Device Fingerprinting, Wireless Sensing, LEO Satellite, Smart Speaker, Autonomous Car/Drone/Robot, and AR/VR/MR
Quantum Machine Learning for IoT Sensing, Communication, and Spectrum Systems
Key Technologies for the Next Generation Backscatter-driven IoT Systems (RFID, LoRa, WiFi, and mmWave Radar): Localization, Sensing, and Communications
Smart Farming (e.g., Wheat Moisture and Mildew Detection, and Temperature Forecasting) Using Wireless Sensing (Wi-Fi CSI and RFID), IoT Sensors, and Machine Learning
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