Theory and Algorithms
Theoretical computer science studies the foundations computing from a rigorous and mathematical point of view. Core topics include models of computing, design and analysis of algorithms, data structures, protocols and mechanisms, and lower bounds.
Our faculty study algorithms in many diverse areas (computational geometry & topology, graphs, optimization, approximation, randomization), data structures, cryptography and secure computation, economics and computation, complexity theory, foundations of machine learning, and applications to several areas including operations research, computational biology, parallel & distributed computing, and networking to name a few. Our research, in addition to its fundamental importance, has many near and long term applications in Computer Science and beyond.
Faculty & Affiliate Faculty
Geometry, Parallel Algorithms, Computational Biology
Computational Geometry, Algorithms, Data Structures
Combinatorial Optimization, Integer Programming, Probabilistic Methods and Analysis, Randomized Algorithms
Algorithms, Combinatorial Optimization, Mathematical Programming, Graphs
Graphs, Information Theory, Algorithms, Machine Learning
Combinatorial Optimization, Integer Linear Programming, Computational Biology
Computational Geometry and Topology, Algorithms
Pseudorandomness, Algebraic Computation, Computational Complexity
Algorithms, Game Theory, Fair Division
Algorithms for and Analysis of Networks and Distributed Systems
Computational Geometry, Geometric Approximation Algorithms
Optimization, Operations Research
Reinforcement Learning Theory, Machine Learning, Sample Complexity Analysis
Cryptography, Secure Computation, Zero-Knowledge, Differential Privacy
Algorithmic Game Theory, Mathematical Economics, Efficient Algorithms
Social Networks, Graph Algorithms, Applied Operations Research, Discrete Optimization, GPU-Accelerated Algorithms
Cryptography, Distributed Algorithms
Parallel Algorithms, Numerical Methods, Communication Cost Analysis, Quantum Computation
Machine Learning Theory
Model Checking, Logic, Cyberphysical Systems, Software, Security
Graph Algorithms, Statistical Estimation, Heuristics for NP-Hard Optimization Problems, Experimental Algorithmics, Applications to Grand Challenges in Biology and Historical Linguistics
Machine Learning, Information Theory, Representation Learning
Machine Learning Theory, Operations Research, Combinatorial Optimization
Adjunct Faculty
Complexity Theory, Spectral Methods for Graph Algorithms
Cryptography, Secure Multi-Party Computation
Seminars
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- Illinois Computer Science Speaker Series