Bryan Kim, Ferdinando Fioretto and Endadul Hoque
Electrical engineering and computer science (EECS) faculty members Bryan Kim, Endadul Hoque, and Ferdinando Fioretto all received notable awards from the National Science Foundation (NSF). All three are new faculty members who started at 鶹ƵUniversity in the 2019-2020 academic year.
Kim was awarded $488,277 for a three-year project rethinking storage interfaces from a solid state drive (SSD) from a holistic perspective by exploiting trade-offs among capacity, performance and reliability (CPR) and designing a flexible capacity-variant interface that allows the SSD to maintain performance.
“This project explores the idea of capacity-variance where the SSD’s capacity is gracefully reduced over time. With capacity-variance, the SSD can provide a consistent level of performance and reliability throughout its lifetime,” says Kim. “This can be beneficial for performance-sensitive applications and a performance engineering perspective, and also makes it easy to identify worn-out SSDs that need replacement.”
Hoque and his co-principal investigator, Omar Haider Chowdhury, were awarded $500,000 for a three-year project developing a transformative defense mechanism to retrofit modern, but insecure, internet of things (IoT) ecosystems.
“This project will focus on defending IoT systems against unforeseen adversarial threats by preventing rogue/faulty native as well as third-party apps from administering unexpected or unsafe operations on IoT devices,” says Hoque. “It will yield a platform-agnostic solution, which will not only improve the security, privacy and safety postures of programmable IoT systems but also be a fundamental shift in IoT security.”
Fioretto and Pascal Van Hentenryck from Georgia Tech received a $500,000 grant as principal investigators for their project aimed at leveraging robust artificial intelligence for transforming the electrical power grid. They plan to use Deep Constrained Learning, a tight integration of machine learning and optimization that delivers real time reliable near-optimal solutions to large-scale nonconvex optimization problems.
“If successful, the project may fundamentally transform how the grid is operated and bring significant economic and environmental benefits,” says Fioretto. “While the development of Deep Constrained Learning is grounded in energy applications, the project findings may generalize to a broader class of engineering applications with hard physical or operational constraints.”
鶹ƵUniversity is one of only 34 private doctoral universities classified as R1 in the Carnegie Classification of Institutions of Higher Education. The R1 distinction is an indicator of “very high research activity” at a university.
“These three professors joined the EECS department in 2019. Within one year of their initial appointments, these three professors received competitive merit-based NSF grants,” says Electrical Engineering and Computer Science Department Chair Jae Oh. “I am delighted to see their success from the beginning of their career, and I look forward to supporting them for their career goals.”
