Amir Houmansadr

Interests

Privacy-Enhancing Technologies, Network Security, Adversarial Machine Learning

Research

Amir's research group evaluates the privacy of in-the-wild Internet services, such as messaging applications, IoT devices, and machine learning APIs,  and designs and implements tools to enhance the privacy of Internet users, such as anti-censorship systems. To this end, Amir's research group combines the development of practical systems with rigorous theoretical analysis, and incorporates techniques from various disciplines such as computer networking, cryptography, and information theory. The specific problems his research group is currently exploring include Internet censorship resistance, network traffic analysis, covert communications, and machine learning security and privacy. Amir's research has found flaws in popular privacy-preserving tools, and has led to the advent of novel designs to overcome these problems.

Biography

Amir Houmansadr is an associate professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst. He received his Ph.D. from the University of Illinois at Urbana-Champaign in August 2012. Amir was with the University of Texas at Austin as a postdoctoral scholar for two years before joining UMass in 2014. Amir has earned his B.Sc. and M.Sc. degrees from the Electrical Engineering Department of Sharif University of Technology.

Activities & Awards

Amir's work has been publicized in the media through interviews, and he has received several awards for his research, including an NSF CAREER Award in 2016, a Google Faculty Research Award in 2015, and the 2013 Best Practical Paper award of the IEEE Symposium on Security & Privacy (Oakland). Amir serves regularly on the technical program committees and editorial boards of top-tier conferences and journals in the area of security and privacy.