We have a postdoc opening in Millimeter-wave backscatter communication. If you are interested in a postdoc position in this area, send me an email at

Prospective PhD Students

I'm actively looking for highly motivated students who are excited about working at the intersection of Wireless and Embedded Systems. Candidates with any of the following backgrounds would be particularly encouraged to apply: signal processing, computer networks, wireless communication, embedded systems, applied machine learning (intuition learning, deep reinforcement learning, deep learning for signal processing).

Interested individuals may send me an email with the following information: (1) your CV, (2) a copy of your transcripts, (3) a brief description of your background and the research interests related to the areas below. The subject of the email should start with "[Prospective_Student]".  I will reach out if your background seems like a potential good fit.

Active Research Topics: Emerging applications such as smart cities, autonomous vehicles, and mixed reality rely on embedded systems that are engaging with the physical environment through sensors. Building upon this connection, my vision is to advance Omnipresent Sensing by harnessing the wireless infrastructure in every building or city to act as a non-intrusive sensing platform. As wireless communication and edge processing advance, we have the opportunity to combine radar-style RF sensors and wireless communication links to improve sensing coverage while reducing deployment costs. Under the broad umbrella of this vision, my current research focuses on three main areas:

  • Battery-free Wireless Sensors: including Millimeter-wave retro-reflectors as fiducial markers and WiFi backscatter tags for object localization and tracking. This research focuses on RF backscatter technologies with applications in AR/VR, robotic, and health monitoring, where accurate sensing mechanisms are required for machine perception.
  • Sensing-assisted Networks: This research builds the next generation of synergic sensing and networking solutions for connected vehicles and swarm of drones. The goal is to develop new interfaces that expose physical-layer sensing information to the other layers of the networking stack for safety-critical applications or closing security loopholes. The physical information can be anything from the trajectory of users, position of devices, to the profile of wireless propagations.
  • ML in Help of Wireless: The increasing number of smart wearable and portable wireless devices along with natural mobility of users presents a new opportunity to extend current stand-alone sensing platforms to a collaborative crowd-source system, in which the sensors and wireless signals from every person's smartphone contribute to providing smart services for all. This research explores new dimensions in the synergy of sensing and machine learning on low-level wireless signals.

Undergraduate and Masters Students at UIUC

I'm excited to work with undergraduate and Masters students who are interested in gaining research experience. If you are a UIUC student in CS/ECE/ESE (or related degrees) and are interested in my research, please send me an email and we can find a time to meet and discuss potential projects.