Portfolio item number 1
Short description of portfolio item number 1
Short description of portfolio item number 1
Short description of portfolio item number 2
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1).
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Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2).
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Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3).
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Published in GitHub Journal of Bugs, 2024
This paper is about fixing template issue #693.
Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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Published:
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Published:
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Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.
, , 1900
The rapid expansion of mobile and wireless technologies, alongside breakthroughs in deep learning, has led to the emergence of the “Artificial Intelligence of Things” (AIoT). In this cutting-edge paradigm, wireless signals do more than just facilitate communication between devices—they also enable interaction with people and the physical environment. This course provides an in-depth exploration of key concepts in mobile and wireless sensing, including the fundamentals of wireless signals, signal processing techniques, and machine learning algorithms. The course is structured into six comprehensive modules, each focused on a specific application domain, such as localization and tracking, gesture and activity recognition, health sensing, material and environmental sensing, multi-modal sensing, and privacy-preserving sensing. Throughout the course, students will engage with recent research papers that highlight innovative designs, algorithms, and applications within the field of mobile and wireless sensing. A significant component of the course involves a semester-long, research-oriented project where students will gain hands-on experience by designing and building their own AIoT systems. This project will allow students to apply theoretical knowledge to practical challenges, fostering a deeper understanding of the AIoT landscape.