Previous Recipients

“Reliable robotic systems must implement motion planning, state estimation, and control algorithms, and a robot model is needed. These operations are typically addressed independently and can lead to unsafe execution due to sensing and actuation noise and discrepancies between the model and reality. While sensors and actuators keep improving, and system identification techniques can reduce the model gap, the discrepancies persist, for example, in unmodeled environments or due to wear and tear.

“My research seeks to integrate these methods by using factor graphs as a common framework. Factor graphs provide significant advantages by enforcing the problem's structure while allowing explainability. Specifically, factor graph representations of the robot dynamics allow significant speed-ups of optimization algorithms for state estimation and control. For long-horizon planning, however, a kinodynamic motion planner is needed, where the planner must produce the factor graph to be used by the state estimation and control algorithms. A common representation, from system dynamics to planning, allows for computationally efficient and explainable algorithms without sacrificing accuracy.”

“Quantum computers require the ability to control quantum systems and implement error correction. My research focuses on controlling photon modes in superconducting cavities. I am developing and implementing techniques to do fast gates on information stored in these photon modes by using superconducting circuits. I am then applying these techniques to explore device architectures that implement random-access quantum memory processors.”

“My dissertation research focuses on advancing light-based technologies by integrating plasmonic nanostructures into thin films and optoelectronic devices. Plasmonics allows us to control light at the nanoscale—below its diffraction limit—by confining it to conductive nanostructures. I study and develop various approaches, including the use of organic conductive materials with exceptional optical and electronic properties, to enhance light-matter interactions. My work enables tunability and modulation of the optical response of these materials to dynamically control light propagation and emission. This research bridges fundamental materials science with real-world applications, contributing to the development of energy-efficient and miniaturized photonic technologies.”

“My research interests include digital signal processing, wireless system designs, and deep learning. Specifically, my dissertation research focuses on exploiting signal processing and generative AI to enhance the security and privacy of next-generation wireless communication and sensing systems.”