MIT Graduate Earns ACM Doctoral Dissertation Award
May 17, 2017
Haitham Hassanieh is the recipient of the Association for Computing Machinery (ACM) 2016 Doctoral Dissertation Award. Hassanieh developed highly efficient algorithms for computing the Sparse Fourier Transform, and demonstrated their applicability in many domains including networks, graphics, medical imaging and biochemistry. In his dissertation The Sparse Fourier Transform: Theory and Practice, he presented a new way to decrease the amount of computation needed to process data, thus increasing the efficiency of programs in several areas of computing.
Honorable Mention for the 2016 ACM Doctoral Dissertation Award went to Peter Bailis of Stanford University and Veselin Raychev of ETH Zurich. In Bailis’s dissertation, Coordination Avoidance in Distributed Databases, he addresses a perennial problem in a network of multiple computers working together to achieve a common goal: Is it possible to build systems that scale efficiently (process ever-increasing amounts of data) while ensuring that application data remains provably correct and consistent? Raychev’s dissertation, Learning from Large Codebases, introduces new methods for creating programming tools based on probabilistic models of code that can solve tasks beyond the reach of current methods.
The 2016 Doctoral Dissertation Award recipients will be formally recognized at the annual ACM Awards Banquet on June 24 in San Francisco, CA. The Doctoral Dissertation Award is accompanied by a prize of $20,000, and the Honorable Mention Award is accompanied by a prize totaling $10,000. Financial sponsorship of the award is provided by Google.
