Internet censorship is a significant threat to the freedom of speech and open access to information across the world. While there exists an arsenal of tools to circumvent Internet censorship, they fall short in helping censored users effectively and reliably. In this talk, I will present insights from a decade of research on combating Internet censorship, highlighting the key technical and non-technical challenges, as well as promising directions for future advancements.

Speaker's Biography: Amir Houmansadr is an Associate Professor of computer science at UMass Amherst. He received his Ph.D. from the University of Illinois at Urbana-Champaign, and was a postdoctoral researcher at the University of Texas at Austin. Amir is broadly interested in the security and privacy of networked/AI systems. To that end, he designs and deploys privacy-enhancing technologies, analyzes network protocols and services (e.g., messaging apps and machine learning APIs) for privacy leakage, and performs theoretical analysis to derive bounds on privacy (e.g., using game theory and information theory). Amir has received several awards including the 2013 IEEE S&P Best Practical Paper Award, a 2015 Google Faculty Research Award, a 2016 NSF CAREER Award, a 2022 DARPA Young Faculty Award (YFA), the 2023 Best Practical Paper Award from the FOCI Community, the first place at CSAW 2023 Applied Research Competition, a Distinguished Paper Award from ACM CCS 2023, a 2024 Applied Networking Research Prize (ANRP), and a 2024 DARPA Directors Award.

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