Please note: This distinguished lecture will take place in DC 1302 and virtually over Zoom.
Tim Roughgarden, Professor
Computer Science Department, Columbia University
Head of Research, a16z crypto
Blockchains that support a general contract layer (e.g., Ethereum) export the functionality of a general-purpose, ownerless, and open-access computer that can enforce property rights for digital data. How is such functionality implemented? Using a lot of extremely cool computer science ideas! And like everywhere else in computer science, theory plays an undeniable role in the understanding and advancement of this technology.
In this talk, I’ll highlight three examples (among many):
- Possibility and impossibility results for permissionless consensus (i.e., implementing an “ownerless” computer).
- Incentive-compatible transaction fee mechanism design (part of implementing an “open-access” computer).
- Succinct proofs of computation (for boosting the computer’s power by piggybacking on off-chain computation).
Bio: Tim Roughgarden is a Professor of Computer Science at Columbia University. Prior to joining Columbia, he spent 15 years on the computer science faculty at Stanford, following a PhD at Cornell and a postdoc at UC Berkeley. His research interests include the many connections between computer science and economics, as well as the design, analysis, applications, and limitations of algorithms. He is also Head of Research at a16z crypto.
For his research, he has been awarded the ACM Grace Murray Hopper Award, the Presidential Early Career Award for Scientists and Engineers (PECASE), the Kalai Prize in Computer Science and Game Theory, the Social Choice and Welfare Prize, the Mathematical Programming Society’s Tucker Prize, and the EATCS-SIGACT Gödel Prize.
He was an invited speaker at the 2006 International Congress of Mathematicians, the Shapley Lecturer at the 2008 World Congress of the Game Theory Society, and a Guggenheim Fellow in 2017. He has written or edited ten books and monographs, including Twenty Lectures on Algorithmic Game Theory (2016), Beyond the Worst-Case Analysis of Algorithms (2020), and the Algorithms Illuminated book series (2017-2020).
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