Fundamental Sensing, Communication, and Networking for Personal, Physical, and Security Intelligence

We are entering an era where the digital and physical worlds are becoming indistinguishable. To support this transition, my group is building the fundamental pillars of sensing, communication, and networking, moving them beyond isolated technology silos toward an application-aware design. In this talk, I will present a decade of research that unifies these domains to enable transformative use cases across Personal, Physical, Healthcare, and Security Intelligence.

I will begin with Sensing, demonstrating localization of personal devices in indoor environments using existing connectivity modules, and how we can replace expensive LiDARs with Wi-Fi sensing to enable robust navigation for robotics. I will also introduce radar systems capable of 3D bounding box detection in adverse weather for autonomous driving, which we demonstrate can autonomously drive cars in realistic evaluations. I will discuss mm-accurate tracking for Smartglasses AR/VR using commodity transceivers. Moving to the human scale, novel force sensors for “in-body” medical robotics. This extends to battery-free analog sensing, ranging from smart pacifiers for tongue-tie assessment to soil moisture monitoring in smart agriculture. I will conclude this section with our work on spectrum sensing for detecting hidden spy cameras and securing physical spaces.

Next, I will cover Communication, where we have developed fundamental primitives for diverse connectivity “pipes.” This spans from battery-free, low-power connectivity compatible with commodity Wi-Fi/BLE/LTE, to smart surfaces that augment MIMO throughput, and scalable mm-Wave architectures. Finally, I will cover Networking, outlining our vision for application-aware architectures that optimize Quality of Experience (QoE) rather than simple Quality of Service (QoS). I will discuss how this enables “thin robots,” in which heavy computation is offloaded to the Edge via real-time RAN Intelligent Controllers (RICs) with guaranteed performance. I will also highlight convergent themes in NextG O-RAN optimization and physical layer security.

By converging these technologies, we are building a future where the network does not merely transport data but actively perceives, reasons about, and secures our world. Ultimately, the fundamental limiting factor for AI is access to high-quality data from the physical world; my work builds the bridge to enable the new forms of sensing required to empower AI.

Dinesh Bharadia

Associate Professor, UC San Diego on March 27, 2026 at 10:15 AM in EB2 1231
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"Dinesh Bharadia is an Associate Professor in the Electrical and Computer Engineering Department and the Klein Gilhousen Chancellor’s Endowed Chair at the University of California, San Diego (UCSD), where he leads the Wireless Communication Sensing and Networking Group (WCSNG). He earned his Ph.D. from Stanford University in 2016, followed by a Postdoctoral Associate position at MIT. In 2018, he joined UCSD as an Assistant Professor and was promoted to a tenured position in 2022.

His research focuses on the design and prototyping of advanced systems for communication, sensing, and networking, with applications spanning privacy, security, robotics, health, and everyday life. His work has driven new research directions across fields such as communication theory, RFIC design, and robotics. Many of his innovations have been successfully translated into startups and commercial products, including Haila, Kumu Networks, and Totemic Labs.

Under his leadership, the WCSNG group has secured funding from sources including NSF, industry partners, and DoD grants. This funding supports a vibrant team of more than 40 students at any given time, helping train the next generation of engineers and scientists. He has received numerous prestigious accolades for his contributions to wireless research, including being named to Forbes 30 Under 30 (Science) and MIT Technology Review’s Innovators Under 35 list."

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