Theory and Algorithms
Theoretical computer science develops efficient algorithms and explores fundamental barriers to efficient and secure computation. Advances in algorithms can provide dramatic performance gains, which are critically important as the era of Moore's Law—and its promise of ever-increasing processor speeds—draws to a close.
Our faculty develop algorithms to find optimal paths, trees, flows, clusters, and other important combinatorial structures in geometric and network data. For problems where computing the best possible solution is prohibitively expensive, we develop fast approximation algorithms to compute provably good solutions, and we explore the limits of what cannot even be approximated quickly. We develop algorithms that exploit geometric, algebraic, and topological properties of data that arise naturally in practice. Within cryptography, we develop protocols for secure multiparty computation and code obfuscation. In algorithmic game theory, we study the impact of strategic behavior among multiple agents. Our research, in addition to its fundamental importance, has many near-term applications in Computer Science and beyond.
CS Faculty and Their Research Interests
|Timothy Chan||computational geometry|
|Chandra Chekuri||algorithms, optimization|
|Jeff Erickson||computational geometry and topology, algorithms|
|Michael Forbes||computational complexity|
|Brighten Godfrey||networked systems theory, distributed algorithms|
|Sariel Har-Peled||computational geometry, geometric approximation algorithms|
|Sheldon Jacobson||optimization, operations research|
|Dakshita Khurana||joining fall 2019; cryptography, privacy, security|
|Ruta Mehta||algorithmic game theory, mathematical economics, efficient algorithms|
|Leonard Pitt||AI and theoretical computing|
|Matus Telgarsky||machine learning theory|
|Mahesh Viswanathan||algorithmic verification of cyberphysical systems|
|Tandy Warnow||multiple sequence alignment, phylogenomics, metagenomics, and historical linguistics|
|Karthik Chandrasekaran, Industrial & Enterprise Systems Engineering||combinatorial optimization, integer programming, probabilistic methods and analysis, randomized algorithms|
|Negar Kiyavash, Electrical & Computer Engineering and Industrial & Enterprise Systems Engineering||learning, statistical signal processing, and information theory; causality; network forensics|
|Rakesh Nagi, Industrial & Enterprise Systems Engineering||social networks, graph algorithms, applied operations research, discrete optimization|
|Alexandra Kolla, University of Colorado at Boulder||complexity theory, spectral methods for graph algorithms|
|Manoj Prabhakaran, IIT Bombay||cryptography, secure multi-party computation|
Related Theory and Algorithms Research Efforts and Groups
- Information Trust Institute (ITI) in the Coordinated Science Lab
- Carl R. Woese Institute for Genomic Biology (IGB)
- Theory and Algorithms Group
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Theory and Algorithms Research News
Genome Web -- Genome Web highlights new research from Assistant Professor Jian Peng and colleagues at the University of California-San Diego that yielded scHiCluster, a single-cell clustering algorithm.
RealClear Defense -- Professor Sheldon Jacobson writes an opinion piece on airport security and TSA PreCheck. "Long airport lines, intensive airport screening, and the summer travel season tend to go together. Already, this year seems to be keeping with that tradition, but what if it didn't have to be that way?"
Science -- Researchers say they have found a new way to give AI a defensive edge against adversarial attacks based on patterns hidden in images. Bo Li, a computer scientist at the University of Illinois who was not involved in the work, says distinguishing apparent features from hidden features is a “useful and good research direction” but also still needs more work.
Nature -- Bo Li, a computer scientist at the University of Illinois at Urbana-Champaign, and her co-authors wrote an algorithm that transcribes a full audio clip and, separately, just one portion of it. If the transcription of that single piece doesn’t closely match the corresponding part of the full transcription, the program throws a red flag — the sample might have been compromised.