The University of Reading – Coordinator
Relevant Expertise
The Department of Computer Science at the University of Reading is part of the School of Mathematical, Physical and Computational Sciences (SMPCS). The research in the Department is organised in three main research groups and five Research Laboratories: namely AI, Consensus Algorithms for Blockchain, Data Science, Big Data Analytics, Advanced Computing for Environmental Sciences, Computer Vision and Cyber-Physical & Embedded Data Intelligence. There has been a sustained pattern of large scale collaborative projects led by the research leaders in the Department addressing several challenging domains. These have included pattern discovery and multi-view data mining, cyber security and privacy preserving technologies, semantic workflow integration and decision support, multi-modal semantic-collateral media indexing and retrieval.
Responsibilities
The University of Reading Team’s responsibilities in Critical-Chains include project coordination and also contributing to a number of core R&D tasks such as payment clearing and settlement process systems, transaction flows modelling and mining, predictive modelling, inter & internet banking, context-aware privacy-security-by design, privacy impact assessment, requirements engineering, framework architecture specification, multi-lateral biometrics-based access control, evaluation methodology and validation scenarios specification and dissemination of results including stakeholder engagement, outreach and clustering activities.
Responsible Staff
Professor Atta Badii, Associate Professor Giuseppe Di Fatta, Elliot Jordan, Maheshkumar Sundaram, Joel Runevic
Atta Badii, is a Research Professor (Computer Science) leader of the Data Intelligence Research Group and CoordinaTtor of the Critical-Chains prpjecty at the University of Reading. Atta has a multi-disciplinary academic and industrial research experience in the fields of distributed intelligent systems, multi-modal indexing and retrieval, security-privacy-accountability by design, criminal networks analytics, data mining and predictive modelling applications in the overall context of the cyber-physical system-of-systems and service-oriented architectures. He has coordinated several large scale European and UK funded projects; contributed to over 40 collaborative projects to-date and has served as the Scientific and Technical Leader of several projects at both national and international level (e.g. FastMatch, MOSAIC, VideoSense, i-Tracs, Dream, Content Safari, and SciCafe2.0- European Observatory for Crowd-Sourcing). Atta has pioneered several paradigms in user-centred assistive-ambient technologies particularly personalised context-aware privacy protective design; and has served on editorial and research steering boards as coordinator/technical leader/invited expert e.g. as the Chair of the Security Architectures and Virtualisation Taskforce of the European Road Map Project SECURIST and as Chair of the VideoSense: European Video-Analytics Network of Excellence and Expert Advisor on the large scale EPSRC-funded Research Programme on Big Data and Human Rights at the University of Essex.
Giuseppe Di Fatta is a Professor and the Head of the Department of Computer Science. In 1999, he was a research fellow at the International Computer Science Institute (ICSI), Berkeley, CA, USA; from 2000 to 2004, he was with the High-Performance Computing and Networking Institute of the National Research Council, Italy; from 2004 to 2006, he was with the University of Konstanz, Germany. His research interests include data mining algorithms and distributed and parallel computing. He contributed to the implementation of the first release (2006) of KNIME and has led a number of successful Knowledge Transfer Partnerships projects on big data analytics and Data Science. He has published over 100 articles in peer-reviewed conferences and journals. He serves on the editorial board of the Elsevier Journal of Network and Computer Applications and is the co-founder of the IEEE ICDM Workshop on Data Mining in Networks.
Elliot Jordan is a Senior Research Assistant at the University of Reading. He has been here since August 2019 and has spent his time here working on the Critical-Chains project. He specialises in Blockchain and has produced Blockchain and Directed Acyclic Graph (Tangle) frameworks for experimental purposes. His contributions to the project include Graph Mining and Machine Learning. Elliot has a BSc in Computer Science from the University of Reading and experience with software engineering in industry involving full-stack development.
Maheshkumar Sundaram is a Research Assistant (AI Software Engineering & Data Science) at the University of Reading from September 2020. Maheshkumar graduated from the University of Edinburgh with a Master’s in Data Science with Distinction (September 2019 – August 2020). His areas of expertise are Machine Learning, Data Analytics and Software Engineering. Prior to his Master’s Degree, he has worked as a Junior Engineer – Development for 2 years with a focus on APIs and front-end development. Currently, he is involved in the research project “Critical-Chains” working on the development of Machine Learning and Graph Mining models for anomaly detection on financial data.
Joel Runevic works at the Department of Computer Science, University of Reading. He specialises in machine learning systems and has produced various algorithms in content-filtering and medical applications. He is currently exploring the potential applications of machine learning in graph networks with a specific focus on detecting anomalous behaviours. In his spare time, he conducts research into how AI can be used to achieve transformative efficiencies in delivering healthcare particularly in supporting mass-screening programmes such as in automated x-ray image labelling for early cancer detection.