Share on Facebook Tweet on Twitter Share on LinkedIn Share by email
Algorithms and Theory

Exploring game theory, market equilibriums, efficient algorithms

We are working in emerging fields within theoretical computer science, including privacy in statistical databases and quantum computing. We also investigate algorithms and mathematics for the Internet, including web search, social-network analysis, spam fighting, and web security.

Classical areas of interest include complexity, cryptography, algebraic computation, random structures, and spectral methods for data analysis. We strive to develop scalable algorithms for learning and data mining, cryptographic algorithms, graph algorithms, synchronization algorithms, networking algorithms, and sampling algorithms. We also look at problems at the intersection of systems, networking, and algorithms research: We study the algorithmic foundations of the systems that drive today’s computing—such as cloud computing, data centers, large-scale distributed systems, and mobile computing—and we apply our expertise in practice to advance the state of the art in applied algorithm design and deliver highly efficient, scalable, robust solutions.

We also conduct research in several theoretical areas in mathematics and physics that are beyond the traditional scope of computer science but are closely connected. Researchers actively work on combinatorics, geometry and topology, probability theory, statistical physics, number theory, and functional analysis.


Nathan Wiebe, Ashish Kapoor, and Krysta M. Svore, Quantum Nearest-neighbor Algorithms for Machine Learning, in Quantum Information and Computation, vol. 15, no. 3&4, pp. 0318-0358, Rinton Press, March 2015

Margus Veanes and Nikolaj Bjørner, Symbolic Tree Automata, in Information Processing Letters, vol. 115, no. 3, pp. 418-424, Elsevier, March 2015

Gao Huang, Jianwen Zhang, Shiji Song, and Zheng Chen, Maximin Separation Probability Clustering, AAAI - Association for the Advancement of Artificial Intelligence, January 2015

Shipra Agrawal and Nikhil R. Devanur, Fast algorithms for online stochastic convex programming, in SODA 2015 (ACM-SIAM Symposium on Discrete Algorithms), SIAM – Society for Industrial and Applied Mathematics, January 2015

Robert A Cochran, Loris D’Antoni, Benjamin Livshits, David Molnar, and Margus Veanes, Program Boosting: Program Synthesis via Crowd-Sourcing, in POPL 2015: 42nd ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, ACM – Association for Computing Machinery, January 2015

More publications ...