Abstract: As we advance to the next generation of wireless technology, we are exploiting more degrees of freedom in radio frequency (RF) systems through increased antenna counts and wider bandwidths. However, this progress has led to significant hardware complexity. The key bottleneck lies in analog design, where performance scales with physical size, power consumption, and computational load. Furthermore, a fundamental premise in the design of wireless networks is that we accept the wireless propagation environment as is, thereby placing a significant burden on the endpoints. Yet, the endpoints can only shape their own transmission, not the propagation environment. Rather than adding more complexity to the endpoints, our research asks: Can we design efficient RF systems that actively shape wireless propagation?
This talk introduces computational analog systems, a new class of RF systems providing fundamentally new capabilities for next-generation wireless communications and sensing. Strategically deployed on buildings and roadsides, these systems bring outdoor signals indoors to maintain connectivity, reflect signals around corners to eliminate blind spots, and locate hidden objects by capturing scattered signals. A key to our approach is analog computation through metamaterial structures. These structures physically process wireless signals without digital conversion, achieving near-instantaneous operation with minimal power consumption in a compact form factor. We demonstrate our approach through end-to-end hardware implementations, from hardware fabrication to real-time deployment in city-scale testbeds, operating from sub-6 GHz to millimeter-wave frequencies and spanning multiple network layers.
Bio: Dr. Kun Woo Cho is a postdoctoral researcher in the Department of Electrical and Computer Engineering at Rice University, working under the guidance of Professor Ashutosh Sabharwal. Her research focuses on building millimeter-wave metamaterial surfaces and lenses for wireless communications and radar systems. She earned her Ph.D. in Computer Science from Princeton University in 2024, under the supervision of Professor Kyle Jamieson, and a bachelor’s degree in computer engineering from the University at Buffalo in 2018. She is a recipient of the Siebel Scholarship in 2025, ACM MobiSys Rising Star in 2025, EECS Rising Star from MIT in 2024, the Princeton SEAS Award for Excellence in 2023, and the Best Paper Award from ACM MobiHoc 2023.
