Five CSL/ECE faculty members receive NSF career awards

Five CSL faculty members have recently been named recipients of NSF CAREER Awards. The NSF CAREER Award is a prestigious award in support of early-career faculty who have the potential to serve as academic role models in both research and education and can advance the mission of their respective department or organization.

CSL and electrical and computer engineering assistant professors Bin Hu, Ilan Shomorony, Alexander Schwing, Richard Zhang, and Jin Zhou were all named NSF CAREER Award recipients.

With the NSF CAREER Award, Hu will be working on his project "Interplay between Control Theory and Machine Learning." This proposal aims to build fundamental connections between control theory and machine learning and reconcile these two areas with a comprehensive interdisciplinary approach. Both are high-impact research areas that are important for managing complex systems like autonomous vehicles, humanoid robotics, smart buildings, and automated healthcare.   

Shomorony will be working on his project "Genomic Data Science: From Informational Limits to Efficient Algorithms." The goal of this project is to develop a framework to establish the informational limits of genomic data science problems and see what genomic data can and cannot reveal. In turn, this will lead to the development of computationally efficient algorithms that process genomic data in an information-optimal way.

Schwing will be working on his project "Learning to Anticipate with Visual Simulation." The goal of this research is to develop methods that can accurately forecast what an observed scene will look like a few seconds from now. For example, given frames of a video showing a traffic intersection, how can a machine anticipate the situation at the intersection a few seconds after the last observed video frame? This project will focus on representations of the suitable data for forecasting, properties of methods that permit accurate forecasting, and what data is necessary to develop accurate forecasting models. 

Zhang will be working on his project "Structure-Exploiting Optimization for Power Systems and Applications to Large-Scale Networks." This project will  investigate structure-exploiting optimization techniques for power system optimization. By identifying and exploiting the mathematical structures that make power system optimization unique from general purpose optimization, this proposal seeks radical, transformative improvements upon the state-of-the-art.

Zhou will be working on his project "Commutated-LC Circuits for Next-Generation RF-Domain Signal Processing." By introducing new commutated-inductor-capacitor circuits, this project aims to tackle the fundamental limits of existing switched-capacitor circuits. This has the potential to substantially reduce the cost and size of next-generation wireless systems which will benefit society through increasing access.