The notion of an algorithm is perhaps the key foundational concept in Computer Science, with the measurement of the resources used by algorithms and their implementations, that is, their computational complexity, central to their study and application. As the amount of available data explodes across science, technology, and society, and new potential applications emerge, never has it been so important that research in algorithmics, the science of algorithms, translates into effective implementations and that the weight of algorithmics research is brought to bear on new potential applications. Algorithmics is absolutely central within modern-day Computer Science.
Research in algorithmics has two broad strands: obtaining better and better upper bounds as regards the resources used within a solution to a given problem; and proving better and better lower bounds as to the resources required for any such solution. The study of upper bounds obviously translates into practical advances; however, so can the study of lower bounds, and more generally complexity-theoretic (completeness) results, in areas such as cryptography and pseudorandomness. The real-world interface with algorithmics inspires new algorithmic analyses, when, for instance, new problems are thrown up or new practically-imposed restrictions forbid existing methodologies; in addition, complexity-theoretic completeness results for real-world problems inspire the search for new heuristic, randomized, approximate, and fixed-parameter algorithms that translate to effective practical solutions.
The study of algorithmics traditionally takes place within Theoretical Computer Science although there are myriad interfaces both within Computer Science and without.
However, often deep theoretical insights and advances do not rapidly percolate 'upwards' into real-world implementations and 'sideways' into other academic domains. On the other hand, algorithmic problems emerging within industry, science, and society do not always percolate 'downwards' to the theoreticians who have the tools and techniques to provide improved algorithmic solutions. Moreover, the boundary between Computer Science and other subjects is becoming ever more fluid; for instance, aspects of computation are becoming increasingly embedded in core Mathematics and new algorithmic aspects of topics such as combinatorics, probability, algebra, and topology, are rapidly emerging.
In short, there are massive opportunities for research in algorithmics to be transformative across science, technology, and society. The key aim of the AlgoUK network of researchers is to facilitate multi-faceted interactions within the UK's algorithmic research community and also inter-disciplinary interactions between these researchers and those in industry and other subjects such as Mathematics, Biology, and Chemistry. The founding research groups, and hosting sites for the workshops, are at Durham, Kings College London, Leicester, Liverpool, Royal Holloway, and Warwick, but the network is open to all who wish to engage with it.
|