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Exploring Algorithms and Complexity: Design, Analysis, and Optimization Techniques

This research focuses on three major themes in algorithms and complexity: algorithm design, analysis, and engineering; computational complexity of algebraic structures; and optimization techniques and heuristics. The primary goal is to study the resources required to solve problems, with an emphasis on minimizing CPU time and memory usage. It covers both theoretical foundations and empirical analyses of algorithm performance. Specific topics include storage and processing of large datasets, pattern mining, and parallel computing, aimed at optimizing real-world applications.

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Exploring Algorithms and Complexity: Design, Analysis, and Optimization Techniques

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  1. Research Away Day Algorithms and Complexity Themes

  2. Three Themes • Algorithm Design, Analysis and Engineering • Computational Complexity of Algebraic Structures. • Optimization and Heuristics • Common thread: study (mathematically or empirically) the amount of resources (CPU time or memory) needed to solve a particular problem. Find algorithms to minimize resources.

  3. Algorithms Research Design and Analysis Applications Algorithm Engg • Mathematical analysis of: • -solution quality • - resource usage • or, proofs of impossibility. • RIGOUR/ : RAE √ • Implement algorithms • as computer code. Empirical • analyses of: • -solution quality • -resource usage • RAE? “Interesting” abstractions of real computational problems.

  4. Algorithm Design + Geography • Relevant sub-interests: • storage and processing of large data sets. • Specific topics: • space-efficient storage and processing of XML files • data mining • expertise mainly in “pattern mining” • e.g. given observations of vehicles at various points (ANPR), find interesting patterns of behaviour • parallel computing (GPUs)

  5. Geometric Geographical Data • No current expertise, but related to current strengths: • Digital Elevation Maps -> Flow data

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