Ali
dr nour ali is a senior lecturer in the department of computer science at brunel university london since june 2017. she currently co-heads the brunel software engineering lab ( and is the director of undergraduate placements, she received her phd in software engineering from universidad politecnica de valencia – spain and has a major in computer science from bir-zeit university- palestine. before moving to brunel, she was a principal lecturer in software engineering at university of brighton and held research fellowships at lero, the irish software engineering research centre and the politecnico di milano. she also has been a visiting researcher at leicester university and free university of bolzen. she has been principal investigator and member of several research and knowledge transfer projects. her research focuses on developing software architecture techniques, methods and tools and applying them to different challenging systems and situations such as distributed, mobile and adaptive. she has over 70 publications in journals, books and conferences. here are links to her publications on dblp and google scholar . she also is a reviewer for top journals and national funding bodies such as epsrc. she serves in several programme and organization committees of conferences and workshops in her area and has co-edited 4 books. dr ali has experience of higher education teaching, from undergraduate to msc level. she has a pg certificate in teaching and learning in higher education from the university of brighton. she is also fellow of the higher education academy (hea). dr ali’s research interests focus on the usage of software architectural models, techniques and tools for distributed and adaptive systems. i have used different techniques and combined them with software architecture such as model driven engineering, reverse engineering, middleware, optimization and machine learning. currently, i am working on three main areas: 1) micro-service software architecture 2) autonomic architecture in the healthcare domain 3) mobile ambients that are self-adaptive. module leader: cs3100 software project management other modules: cs1005 computation and logic, group project level 1 cs307x level 3 final year project.
Dr Nour Ali
Dr Nour Ali is a Senior Lecturer in the Department of Computer Science at Brunel University London since June 2017. She currently co-heads the Brunel Software Engineering Lab ( and is the Director of Undergraduate Placements, She received her PhD in Software Engineering from Universidad Politecnica de Valencia – Spain and has a Major in Computer Science from Bir-Zeit University- Palestine. Before moving to Brunel, she was a Principal Lecturer in Software Engineering at University of Brighton and held research fellowships at Lero, the Irish Software Engineering Research Centre and the Politecnico di Milano. She also has been a visiting researcher at Leicester University and Free University of Bolzen. She has been Principal Investigator and member of several research and knowledge transfer projects. Her research focuses on developing software architecture techniques, methods and tools and applying them to different challenging systems and situations such as distributed, mobile and adaptive. She has over 70 publications in journals, books and conferences. Here are links to her publications on dblp and google scholar . She also is a reviewer for top journals and national funding bodies such as EPSRC. She serves in several Programme and Organization Committees of conferences and workshops in her area and has co-edited 4 books. Dr Ali has experience of Higher Education teaching, from undergraduate to MSc level. She has a PG Certificate in Teaching and Learning in Higher Education from the University of Brighton. She is also Fellow of the Higher Education Academy (HEA). Dr Ali’s research interests focus on the usage of software architectural models, techniques and tools for distributed and adaptive systems. I have used different techniques and combined them with software architecture such as Model Driven Engineering, Reverse Engineering, Middleware, Optimization and Machine Learning. Currently, I am working on three main areas: 1) Micro-service software architecture 2) Autonomic architecture in the healthcare domain 3) Mobile Ambients that are self-adaptive. Module Leader: CS3100 Software Project Management Other Modules: CS1005 Computation and Logic, Group Project Level 1 CS307x Level 3 Final Year Project.
Shepperd
martin shepperd received a phd in computer science from the open university in 1991 for his work in measurement theory, many sorted algebras and their application to empirical software engineering. he was seconded to the parliamentary office of science & technology. presently he is head of department and holds the chair of software technology and modelling at brunel university london, uk. he has published more than 150 refereed papers and three books in the areas of software engineering and machine learning. he is a fellow of the british computer society. previously martin has worked as a software developer for hsbc. software engineering, empirical research, cost modelling and prediction, machine learning (including case-based reasoning, metaheuristics, rule induction algorithms and grey relational algebra), data imputation and noise handling, reproducibility, replicability and meta-analysis. introductory data science (cs5702 modern data) to the msc students and research methods to the doctoral students (cs5767).
Professor Martin Shepperd
Martin Shepperd received a PhD in computer science from the Open University in 1991 for his work in measurement theory, many sorted algebras and their application to empirical software engineering. He was seconded to the Parliamentary Office of Science & Technology. Presently he is Head of Department and holds the chair of Software Technology and Modelling at Brunel University London, UK. He has published more than 150 refereed papers and three books in the areas of software engineering and machine learning. He is a fellow of the British Computer Society. Previously Martin has worked as a software developer for HSBC. Software engineering, Empirical research, Cost modelling and prediction, Machine learning (including case-based reasoning, metaheuristics, rule induction algorithms and Grey relational algebra), Data imputation and noise handling, Reproducibility, replicability and meta-analysis. Introductory data science (CS5702 Modern Data) to the MSc students and Research methods to the doctoral students (CS5767).
Swift
dr. stephen swift is a research lecturer in the school of information systems, computing and mathematics at brunel university london. he received a b.sc. degree in mathematics and computing from the university of kent, canterbury, u.k., an m.sc. in artificial intelligence from cranfield university, cranfield, u.k. and a ph.d. degree in intelligent data analysis from birkbeck college, university of london, london, u.k. he has four years post-doctoral research experience on an epsrc funded project entitled “modelling short multivariate time series” (involving moorfields eye hospital) gr/m94120) and a bbsrc funded project entitled “analysing virus gene expression data to understand regulatory interactions” (bio14300) in collaboration with the departments of virology and biochemistry at university college london and the school of computer science and information systems, birkbeck college. he has also spent four years in industry as a web designer, programmer and technical architect. research interests include multivariate time series analysis, heuristic search, data clustering, and evolutionary computation. he has applied his research to a number of real world areas including software engineering, bioinformatics and health care.
Dr Stephen Swift
Dr. Stephen Swift is a Research Lecturer in the School of Information Systems, Computing and Mathematics at Brunel University London. He received a B.Sc. degree in Mathematics and Computing from the University of Kent, Canterbury, U.K., an M.Sc. in Artificial Intelligence from Cranfield University, Cranfield, U.K. and a Ph.D. degree in Intelligent Data Analysis from Birkbeck College, University of London, London, U.K. He has four years post-doctoral research experience on an EPSRC funded project entitled “Modelling Short Multivariate Time Series” (involving Moorfields Eye Hospital) GR/M94120) and a BBSRC funded project entitled “Analysing Virus Gene Expression Data to understand Regulatory Interactions” (BIO14300) in collaboration with the Departments of Virology and Biochemistry at University College London and the School of Computer Science and Information Systems, Birkbeck College. He has also spent four years in industry as a web designer, programmer and technical architect. Research interests include multivariate time series analysis, heuristic search, data clustering, and evolutionary computation. He has applied his research to a number of real world areas including Software Engineering, Bioinformatics and Health Care.
Neykova
dr rumyana neykova is a lecturer at brunel university london. she has a phd from imperial college london where she was also a fellow and a research associate. her phd focuses on development and applications of a type theory (called session types) for runtime verification of concurrent and distributed systems. her body of work builds on the foundations of concurrency theory and type systems to offer practical, yet rigorous, verification techniques for distributed systems. she utilises type systems, formal methods, model checkers, compiling techniques, and code generation to help prevent communication faults (such as deadlocks and communication mismatches), increase software reliability, improve performance, assist the software development process, and enhance software understanding. i am teaching on the following modules: year 1: cs1005 logic and computation year 2: cs2002 software developement and management year 3: cs3001 advanced topics in computer science i am supervising final year undergraduate project, as well as msc dissertations teaching and industry: i am advisor on brunel talent marketplace, where i am supervising projects between students and industry.
Dr Rumyana Neykova
Dr Rumyana Neykova is a lecturer at Brunel University London. She has a PhD from Imperial College London where she was also a fellow and a research associate. Her PhD focuses on development and applications of a type theory (called session types) for runtime verification of concurrent and distributed systems. Her body of work builds on the foundations of concurrency theory and type systems to offer practical, yet rigorous, verification techniques for distributed systems. She utilises type systems, formal methods, model checkers, compiling techniques, and code generation to help prevent communication faults (such as deadlocks and communication mismatches), increase software reliability, improve performance, assist the software development process, and enhance software understanding. I am teaching on the following modules: Year 1: CS1005 Logic and Computation Year 2: CS2002 Software Developement and Management Year 3: CS3001 Advanced Topics in Computer Science I am supervising Final Year Undergraduate Project, as well as MSc Dissertations Teaching and Industry: I am advisor on Brunel Talent Marketplace, where I am supervising projects between students and Industry.
Arzoky
dr mahir arzoky is a lecturer in the department of computer science at brunel university london. prior to this he was a post-doctoral research fellow working on a research project titled assessing the quality of test suites in industrial code (aquatic - epsrc: ep/m024083/1). he was a core member of the fault analyses in industry and academic research network (fiar-net - epsrc: ep/n011627/1), where he promoted collaborations between industry and academic research in software engineering through a series of national and international workshops. prior to this, he was a research associate in machine learning at the cognitive digital system engineering centre, birmingham city university, where he worked on a collaborative data-driven smart city project that aimed to simplify complex decision making, informing policy and strategic service developments using unified data, and state of the art machine learning simulation and modelling. he was also part of an innovation engine project, part-funded by the european regional development fund, that aimed at stimulating demand for new or improved services, processes and products from local sme businesses and start-up companies by bringing and helping to solve existing challenges within the life sciences, digital and creative sectors. dr arzoky obtained his phd from the department of computer science at brunel university london in 2015. his research interest lies in the areas of artificial intelligence, intelligent data analysis, data mining and software engineering, in specific search based software engineering. artificial intelligence, intelligent data analysis, heuristic search, search based software engineering, clustering, refactoring
Dr Mahir Arzoky
Dr Mahir Arzoky is a Lecturer in the Department of Computer Science at Brunel University London. Prior to this he was a Post-doctoral Research Fellow working on a research project titled Assessing the Quality of Test Suites in Industrial Code (AQUATIC - EPSRC: EP/M024083/1). He was a core member of the Fault Analyses in Industry and Academic Research Network (FIAR-NET - EPSRC: EP/N011627/1), where he promoted collaborations between industry and academic research in software engineering through a series of national and international workshops. Prior to this, he was a Research Associate in Machine Learning at the Cognitive Digital System Engineering Centre, Birmingham City University, where he worked on a collaborative Data-driven Smart City project that aimed to simplify complex decision making, informing policy and strategic service developments using unified data, and state of the art machine learning simulation and modelling. He was also part of an Innovation Engine project, part-funded by the European Regional Development Fund, that aimed at stimulating demand for new or improved services, processes and products from local SME businesses and start-up companies by bringing and helping to solve existing challenges within the Life Sciences, Digital and Creative sectors. Dr Arzoky obtained his PhD from the Department of Computer Science at Brunel University London in 2015. His research interest lies in the areas of Artificial Intelligence, Intelligent Data Analysis, Data Mining and Software Engineering, in specific Search Based Software Engineering. Artificial Intelligence, Intelligent Data Analysis, Heuristic Search, Search Based Software Engineering, Clustering, Refactoring
Tucker
allan tucker is reader in the department of computer science where he heads the intelligent data analysis group consisting of 17 academic staff, 15 phd students and 4 post-docs. he has been researching artificial intelligence and data analytics for 21 years and has published 120 peer-reviewed journal and conference papers on data modelling and analysis. his research work includes long-term projects with moorfields eye hospital where he has been developing pseudo-time models of eye disease (epsrc - £320k) and with defra on modelling fish population dynamics using state space and bayesian techniques (nerc - £80k). currently, he has projects with google, the university of pavia italy, the royal free hospital, ucl, zoological society of london and the royal botanical gardens at kew. he was academic lead on an innovate uk, regulators’ pioneer fund (£740k) with the medical and health regulatory authority on benchmarking ai apps for the nhs, and another on detecting significant changes in adaptive ai models of healthcare (£195k). he is currently academic lead on two pioneer funds on explainability of ai (£168k) and in-silico trials (£750k). he serves regularly on the pc of the top ai conferences (including ijcai, aaai, and ecml) and is on the editorial board for the journal of biomedical informatics. he hosted a special track on "explainable ai" at the ieee conference on computer based medical systems in 2019 and was general chair for ai in medicine 2021. he has been widely consulted on the ethical and practical implications of ai in health and medical research by the nhs, and the use of machine learning for modelling fisheries data by numerous government thinktanks and academia. data mining / data science machine learning artificial intelligence bayesian networks big data biomedical informatics eco informatics i have designed and led the following modules: business intelligence (msc) - at brunel (~150 students) and nith, oslo (~30 students) for 1 year. machine learning (msc) - at brunel (~10 students) for 3 years. logic and computation (level 1) - at brunel (~200 students) for 4 years. artificial intelligence option (level 3) - at brunel (~200 students) for 4 years. high performance computational infrastructures (msc) - at brunel (~30 students) for 1 year. other teaching: • java programming (level 1) - at brunel (~200 students) for 5 years. • masters level statistics course - at brunel graduate school (~10 students) for 1 year.
Dr Allan Tucker
Allan Tucker is Reader in the Department of Computer Science where he heads the Intelligent Data Analysis Group consisting of 17 academic staff, 15 PhD students and 4 post-docs. He has been researching Artificial Intelligence and Data Analytics for 21 years and has published 120 peer-reviewed journal and conference papers on data modelling and analysis. His research work includes long-term projects with Moorfields Eye Hospital where he has been developing pseudo-time models of eye disease (EPSRC - £320k) and with DEFRA on modelling fish population dynamics using state space and Bayesian techniques (NERC - £80k). Currently, he has projects with Google, the University of Pavia Italy, the Royal Free Hospital, UCL, Zoological Society of London and the Royal Botanical Gardens at Kew. He was academic lead on an Innovate UK, Regulators’ Pioneer Fund (£740k) with the Medical and Health Regulatory Authority on benchmarking AI apps for the NHS, and another on detecting significant changes in Adaptive AI Models of Healthcare (£195k). He is currently academic lead on two Pioneer Funds on Explainability of AI (£168k) and In-Silico Trials (£750k). He serves regularly on the PC of the top AI conferences (including IJCAI, AAAI, and ECML) and is on the editorial board for the Journal of Biomedical Informatics. He hosted a special track on "Explainable AI" at the IEEE conference on Computer Based Medical Systems in 2019 and was general chair for AI in Medicine 2021. He has been widely consulted on the ethical and practical implications of AI in health and medical research by the NHS, and the use of machine learning for modelling fisheries data by numerous government thinktanks and academia. Data Mining / Data Science Machine Learning Artificial Intelligence Bayesian Networks Big Data Biomedical Informatics Eco Informatics I have designed and led the following modules: Business Intelligence (MSc) - at Brunel (~150 students) and NITH, Oslo (~30 students) for 1 year. Machine Learning (MSc) - at Brunel (~10 students) for 3 years. Logic and Computation (Level 1) - at Brunel (~200 students) for 4 years. Artificial Intelligence option (level 3) - at Brunel (~200 students) for 4 years. High Performance Computational Infrastructures (MSc) - at Brunel (~30 students) for 1 year. Other teaching: • JAVA programming (level 1) - at Brunel (~200 students) for 5 years. • Masters level Statistics course - at Brunel Graduate School (~10 students) for 1 year.