Nick Feamster is Neubauer Professor of Computer Science and Faculty Director of Research at the Data Science Institute. Previously, he was a full professor in the Computer Science Department at Princeton University, where he directed the Center for Information Technology Policy (CITP); prior to Princeton, he was a full professor in the School of Computer Science at Georgia Tech.
Before joining the faculty at Princeton, he was a professor in the School of Computer Science at Georgia Tech. He received his Ph.D. in Computer science from MIT in 2005, and his S.B. and M.Eng. degrees in Electrical Engineering and Computer Science from MIT in 2000 and 2001, respectively. He was an early-stage employee at Looksmart (acquired by AltaVista), where he wrote the company’s first web crawler; and at Damballa, where he helped design the company’s first botnet-detection algorithm.
Nick is an ACM Fellow. He received the Presidential Early Career Award for Scientists and Engineers (PECASE) for his contributions to cybersecurity, notably spam filtering. His other honors include the Technology Review 35 “Top Young Innovators Under 35” award, the ACM SIGCOMM Rising Star Award, a Sloan Research Fellowship, the NSF CAREER award, the IBM Faculty Fellowship, the IRTF Applied Networking Research Prize, and award papers at ACM SIGCOMM (network-level behavior of spammers), the SIGCOMM Internet Measurement Conference (measuring Web performance bottlenecks), and award papers at USENIX Security (circumventing web censorship using Infranet, web cookie analysis) and USENIX Networked Systems Design and Implementation (fault detection in router configuration, software-defined networking). His seminal work on the Routing Control Platform won the USENIX Test of Time Award for its influence on Software Defined Networking.
Nick is an avid distance runner, having completed nearly 20 marathons, including Boston, New York, and Chicago, as well as the Comrades Marathon, an iconic ultra-marathon in South Africa. He lives in Princeton, New Jersey.
Focus Areas: Network performance, security, and privacy, Internet censorship and access
I design and deploy network protocols and systems that make the Internet work better. I use empirical network measurement and machine learning to understand and improve network performance, security, and privacy. The results of my research often have implications to policy. I regularly work with federal and municipal organizations, including the Federal Communications Commission (FCC) and the City of Chicago on equitable Internet access, security, and privacy. Read more about projects at my research group web page.