Applied Data Analytics Research and Enterprise Group

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Profile Information

Applied Data Analytics REG image credit Clint Adair on UnsplashVast amounts of data are generated every day: from the text and visual content placed online by users and providers, to innumerable IoT data streams and the click trails and other collateral data emanating from users’ interaction with the online world, we need better methods to make sense of, manage, organise, visualise, utilise and monetise data.

The common aim in all data analytics is to turn data into information, and ultimately knowledge, that can be used to add value to businesses, help people lead healthier lives at all ages, optimise manufacturing processes, and enrich user experiences.

The Applied Data Analytics Research Group’s expertise is grounded in new and established methods and tools from computer science, statistics and mathematics including a wide range of machine learning and statistical modelling techniques. Building on these are more specialised approaches for the analysis of textual, image and structured numerical data. We have worked with a wide range of specific data types, including social media posts, free-text user comments, medical images, user-generated photographs, geolocation data, corporate and financial data, product lifecycle and PPS data, food labels, genomic data and medical data. This expertise in data methods and data types is complemented by specialisation in three application domains: (1) Health (BSMS: Ford, Cassell, Bremner, van Marwijk; PABS: Smith; CEM: Belz, Touloumis); (2) Business intelligence (UoB SPPO: Mullick; CEM: Chernov, Touloumis); and (3) Manufacturing processes (CEM: Song, Belz, Wang).

Group leader: Professor Anya Belz, Professor of Computer Science in the School of Computing, Engineering and Mathematics at the University of Brighton

Group members at the University of Brighton:

Dr Alexey Chernov, Senior Lecturer

Professor Colin Smith, Professor of Functional Genomics

Mr Ran Song, Senior Lecturer

Dr Anestis Toulmoumis, Senior Lecturer

Dr Yan Wang, Principal Lecturer

Group members at Brighton and Sussex Medical School:

Dr Stephen Bremner, Senior Lecturer in Medical Statistics 

Professor Jackie Cassell, Head of the Department of Primary Care and Public Health & Director of Knowledge Exchange

Dr Elizabeth Ford, Lecturer in Research Methodology

Professor Harm Van Marwijk, Professor in General Practice

Fingerprint Dive into the research topics where Applied Data Analytics Research and Enterprise Group is active. These topic labels come from the works of this organisation's members. Together they form a unique fingerprint.

Streptomyces coelicolor Medicine & Life Sciences
Heat-Shock Response Medicine & Life Sciences
Polyribosomes Medicine & Life Sciences
Logistics Engineering & Materials Science
logistics Earth & Environmental Sciences
Hot Temperature Medicine & Life Sciences
Decision making Engineering & Materials Science
Odds Ratio Medicine & Life Sciences

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2017 2021

CoQuaND

Belz, A.

1/11/1831/03/19

Project: Grant

Research Output 2012 2018

Adding the Third Dimension to Spatial Relation Detection in 2D Images

Birmingham, B., Muscat, A. & Belz, A., 7 Sep 2018, (Accepted/In press) Proceedings of the 11th International Conference on Natural Language Generation . The Association for Computational Linguistics, p. 146-151

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBNResearchpeer-review

Open Access
File

An integrated MCDM approach considering demands-matching for reverse logistics

Wang, H., Jiang, Z., Zhang, H., Wang, Y., Yang, Y. & Li, Y., 11 Oct 2018, In : Journal of Cleaner Production. 208, p. 199-210 12 p.

Research output: Contribution to journalArticleResearchpeer-review

Logistics
logistics
Decision making
decision making
Analytic hierarchy process

From Image to Language and Back Again

Belz, A., Berg, T. & Yu, L., 23 Apr 2018, In : Natural Language Engineering. 24, 3, p. 325-362 38 p.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
File