A research collaboration has found an efficient way to expand the collective behavior of swarming microrobots: Mixing different sizes of the micron-scale ‘bots enables them to self-organize into... Read more about Swarming microrobots self-organize into diverse patterns
Six assistant professors win NSF early-career awards
Two operations research and information engineers, two electrical engineers and two mathematicians from Cornell have received National Science Foundation (NSF) Faculty Early Career Development Program awards.
Over the next five years, each researcher will receive up to $500,000 “to build a firm scientific footing for solving challenges and scaling new heights for the nation, as well as serve as academic role models in research and education,” according to the NSF website.
The five assistant professors are: Jayadev Acharya, electrical and computer engineering; Siddhartha Banerjee, operations research and information engineering; Christina Delimitrou, electrical and computer engineering; Nathan Kallus, operations research and information engineering at Cornell Tech; Karola Mészáros, mathematics in the College of Arts and Sciences; and Inna Zakharevich, mathematics in the College of Arts and Sciences.
Acharya will use his funds to shed light on poorly understood trade-offs in data science and machine learning. For example, an app on a mobile device that searches the web would ideally be small, communicate as little data as possible and maintain the privacy of the user. But these constraints are often at odds with each other. Strong privacy requires more data and computation, and data-efficient systems require more computation. The project aims to establish fundamental trade-offs between resources and design efficient solutions to improve these systems. Outreach activities will connect project researchers with undergraduate students and underrepresented communities....
Delimitrou will use her funds to study cloud microservices, which are becoming increasingly pervasive in data centers. As modern cloud services have grown in popularity, their designs have shifted from complex monolithic applications to specialized, loosely coupled microservices, which require fast network processing and low request latency. These issues affect the availability and efficiency of cloud services. The project will pursue automated, learning-based techniques to take a holistic view to designing a hardware and software system for interactive microservices that run on large data centers....