Contact

Phone: 470-578-7431

Email: jzhang51@kennesaw.edu

Office Location: Marietta Campus, 920 Norton Hall, Room 221

Office Hours:
office hours TBD

Jian Zhang

Dr. Jian Zhang is an Associate Professor of Information Technology at Kennesaw State University and Principal Investigator of the Intelligent Sensing, RFID, and Robotics Research Lab. His research group develops AI-enabled sensing, RFID systems, wireless communication, autonomous robotics, smart healthcare technologies, and smart agriculture systems.

Research Group and Funded Projects

Dr. Zhang leads NSF-funded research with students and collaborators in computer science, engineering, AI, wireless sensing, robotics, and cyber-physical systems. Current NSF-supported projects include NSF Award 2549204, Collaborative Research: VINES: Track 1: NSF-MeitY: SoyWatch: Smart Sensing Network for Precision Soybean Breeding, and NSF Award 2245607, Collaborative Research: CCSS: When RFID Meets AI for Occluded Body Skeletal Posture Capture in Smart Healthcare.

Intelligent Embodied  Lab
Dr. Zhang is the director and PI of the Intelligent Embodied Lab and investigates how AI, wireless sensing, and cyber-physical systems can help machines perceive, localize, and reason about people, objects, and environments. The lab's research connects applied machine learning, radio-frequency identification (RFID), indoor localization, ubiquitous sensing, and autonomous systems with real-world problems in health monitoring, supply chains, smart infrastructure, and precision agriculture.

Research Group

The lab currently includes four Ph.D. students and one master's student. Group members work on AI-enabled sensing, RFID systems, autonomous robotics, wireless communication, smart healthcare, smart agriculture, and cyber-physical systems.

Research Interests

  • AI-enabled sensing and perception
  • RFID systems and passive wireless sensing
  • Autonomous robotic systems for logistics and field applications
  • Indoor localization and ubiquitous sensing
  • Next-generation wireless communication and smart agriculture
  • Machine learning for healthcare, mobility, and cyber-physical systems


Funded Research
Dr. Zhang is the Principal Investigator for NSF Award 2549204, Collaborative Research: VINES: Track 1: NSF-MeitY: SoyWatch: Smart Sensing Network for Precision Soybean Breeding. This project develops smart sensor networks, NextG-enabled wireless communication, drone-supported data collection, and multimodal AI tools to support precision soybean breeding and data-driven agricultural decision-making.

He is also the Principal Investigator for NSF Award 2245607, Collaborative Research: CCSS: When RFID Meets AI for Occluded Body Skeletal Posture Capture in Smart Healthcare, which investigates RFID and AI methods for capturing body motion and supporting smart healthcare applications.

 

Students and Collaboration
The lab supports student research and interdisciplinary collaboration across information technology, engineering, artificial intelligence, wireless systems, robotics, agriculture, and healthcare. Students interested in intelligent sensing, RFID, machine learning, robotics, or wireless cyber-physical systems are encouraged to contact Dr. Zhang by email.

Selected Publications and Research Outputs

Dr. Zhang has published research in RFID sensing, autonomous robotics, indoor localization, AI-enabled healthcare, smart logistics, and wireless/cyber-physical systems. His recent work includes publications on robotic RFID inventory, RF hologram tensor localization, RFID-based human motion sensing, adaptive RFID networks, and AI-enabled sensing for healthcare and smart environments.

Google Scholar: https://scholar.google.com/citations?user=n6-XZf4AAAAJ&hl=en
ResearchGate: https://www.researchgate.net/profile/Jian-Zhang-16

Selected Publications

- CMRM: A Cross-Modal Reasoning Model to Enable Zero-Shot Imitation Learning for Robotic RFID Inventory in Unstructured Environments.
- A Framework for Locating Multiple RFID Tags Using RF Hologram Tensors.
- Locating Multiple RFID Tags with Swin Transformer-based RF Hologram Tensor Filtering.
- Robust RFID-Based 6-DoF Localization for Unmanned Aerial Vehicles.
- RFHUI: An RFID-Based Human-Unmanned Aerial Vehicle Interaction System in an Indoor Environment.

Background
Dr. Zhang received his B.S. and M.S. in Applied Physics from Sichuan University in 2005 and 2008, respectively, and his Ph.D. in Electrical Engineering from Auburn University in 2016. From 2016 to 2021, he worked in the RFID Lab at Auburn University as a postdoctoral researcher and assistant research professor. He also has industry experience in telecommunications as a software engineer, project manager, and product manager.

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