IDSAI team
We carry out basic research in advanced data analytics, from foundations and method development to wider-ranging applications. In particular, our strengths are in climate, environment, sustainability and health. This work is underpinned by work on the philosophy of AI and the extent to which conceptual and ethical assumptions are built into algorithms.
The Institute for Data Science and Artificial Intelligence is overseen by the IDSAI Executive Board chaired by the Vice-President and Deputy Vice-Chancellor (Research and Impact), Professor Krasimira Tsaneva-Atanasova. The Board brings together the Pro Vice-Chancellor and Executive Deans from all the University’s Faculties:
- Professor Alex Gerbasi from Faculty of Environment, Science and Economy
- Professor Sallie Lamb from Faculty of Health and Life Sciences
- Professor Gareth Stansfield from Faculty of Humanities, Arts and Social Sciences.
The IDSAI Deputy Director, IDSAI Assistant Directors and the IDSAI Manager are also members of the Executive Board.
The Executive Board holds the full executive authority for IDSAI and looks to the Directors to deliver on the Institute’s aim to drive exciting new interdisciplinary research and education.
The Executive Board is supported by IDSAI Senior Administrator Helen Chapman.
The IDSAI Management Group is responsible to the Vice-President and Deputy Vice-Chancellor (Research and Impact), Professor Krasimira Tsaneva-Atanasova, and the IDSAI Executive Board for the effective running of the IDSAI.
The IDSAI Management Group is led by the IDSAI Director, Aline Villavicencio and includes the Deputy Director of IDSAI, Associate Professor Miriam Koschate-Reis and the IDSAI Manager.
- IDSAI Assistant Director for Education - Dr Eilis Hannon
- IDSAI Assistant Director for Partnerships - Professor Mark Kelson
- IDSAI Assistant Director - Professor Oliver Hauser
- IDSAI Manager – Dr Emily Paremain
The Management Group is supported by Helen Chapman, Senior Administrator, IDSAI.
The IDSAI theme leads build new communities and catalyse new interdisciplinary research activities in their areas. They are also a key point of liaison and information regarding the Alan Turing Institute.
Information about each research theme area can be found here.
| Lead | Theme |
| Professor Tim Dodwell | Data Centric Engineering |
| Professor Sabina Leonelli | Data Ethics, Governance and Openness |
| Dr Niccolo Tempini | Data Ethics, Governance and Openness |
| Professor Leif Isaksen | Humanities, Heritage and Creative Industries |
| Dr Federico Botta | Urban Analytics |
| Dr Lewys Brace | Security and Policing |
| Professor Oliver Hauser | Behavioural and Experimental Data Science |
| Dr Fabrizio Costa | Foundations of Data Science |
| Professor David Llewellyn | Health |
| Dr Eilis Hannon | Health |
| Dr Chico Camargo | Computational Social Science |
| Dr Chunbo Luo | Remote Sensing |
| Prof Hywel Williams | Environmental Intelligence |
| Dr Janice Ranson | Reproducibility |
| Prof Danny Williamson | Uncertainty Quantification |
| Prof Peter Challenor | Uncertainty Quantification |
| Prof Ed Keedwell | Trustworthy AI |
| Dr Zhivko Zhelev | Trustworthy AI |
| Dr Ke Li | Trustworthy AI |
Finley Gibson
Finley joined IDSAI in September 2022 following his PhD with the University of Exeter. With a background in physics and robotics, Finley's research interests centre on machine learning and optimisation. In particular optimisation of expensive multi-objective problems, and applications of optimisation to the tuning of machine learning algorithms.
Data science expertise: Bayesian optimisation, deep neural networks, multi-objective optimisation, image classification and automated hyperparameter tuning.
Charlie Kirkwood
Charlie joined the Institute in October 2022 following his PhD in mathematics at the University of Exeter in partnership with the Met Office. Charlie’s background was originally in geology, and he has spent the last 7+ years learning how data science and artificial intelligence can help us to model and understand the environment; a topic in which he has a range of publications.
Data science interests: Neural networks, gaussian processes, deep learning, Bayesian statistics, ensemble methods, decision trees, model checking & calibration, interpretable AI, visualisation.
Cédric Mesnage
Cédric has over 20 years research experience in Artificial Intelligence. He was awarded a PhD in Computer Science from the University of Lugano, Switzerland in 2012, and a Master of research in Algorithms and Data Modelling from the University of Caen, France in 2005. He has since worked as a researcher in Data Science at the University of Bristol and Queen Mary University, lectured in Data Science at Southampton Solent and supervises Master students in Data Science at the University of Sheffield.
As a research fellow of IDSAI since 2022, he works on seedcorn projects and carries on his personal research on Artificial General Intelligence to automate scientific discovery.
His list of publications can be found on his Google Scholar profile.
IDSAI Affiliated Academics
View our A-Z list of affiliated academics or search by theme below.
| Name | Department/College | Profile |
|---|---|---|
| Dr Edmond Awad | Business School (Economics) / IDSAI | Edmond is a Lecturer (Assistant Professor) in the Department of Economics and the Institute for Data Science and Artificial Intelligence at the University of Exeter. He is also an Associate Research Scientist at the Max Planck Institute for Human Development, and is a Founding Editorial Board member of the AI and Ethics Journal, published by Springer. Before joining the University of Exeter, Edmond was a Postdoctoral Associate at MIT Media Lab (2017-2019). In 2016, Edmond led the design and development of Moral Machine, a website that gathers human decisions on moral dilemmas faced by driverless cars. The website has been visited by over 4 million users, who contributed their judgements on 70 million dilemmas. Another website that Edmond co-created, called MyGoodness, collected judgements over 2 million charity dilemmas. Edmond’s research interests are in the areas of AI, Ethics, Computational Social Science and Multi-agent Systems. |
| Dr Federico Botta | Department of Computer Science | Federico is a computational social scientist interested in human behaviour, both at the collective and individual level, urban systems and cities, and complex networks. His background in complex systems, behavioural science and physics allows Federico to work on a range of truly interdisciplinary projects. In his research, Federico often uses novel data streams such as those generated thanks to our interactions with the Internet, social media platforms, and the mobile phone network. Federico is also interested in how our usage of smart phones, apps and tracking sensors can be used to better understand our behaviour and wellbeing. |
| Professor Alan Brown | Business School (INDEX Group) | Alan’s expertise is focused on leading agile approaches to business transformation, and the understanding the relationship between technology innovation and business innovation in today’s rapidly-evolving digital economy. Alan spent almost 2 decades in the USA in commercial high-tech companies leading R&D teams, building leading-edge solutions, and driving innovation in software product delivery. He then spent 5 years in Madrid leading enterprise strategy as European CTO for IBM’s Software group. More recently Alan co-founded the Surrey Centre for the Digital Economy (CoDE) at the University of Surrey where he led research initiatives in 4 EPSRC-funded research projects. Alan’s latest book, published in 2019, is “Delivering Digital Transformation: A manager’s guide to the digital revolution”. |
| Professor Sarah Hartley | Business School (Science, Innovation, Technology, and Entrepreneurship) | Addressing global and societal challenges with science and technology has become a significant priority for European and North American funding organisations and governments. Sarah's research focuses on science and technology governance as a means to address these challenges with a focus on the actors, ideas and institutions in innovation systems. She investigates two research themes through cases of controversial emerging biotechnology and artificial intelligence (AI) innovations: 1] factors that shape innovation trajectories and their impact; and 2] risk regulatory decisions as critical junctures in technology development and the tensions that exist between scientific excellence and efforts to open up risk decisions to a broader range of actors. I work in the UK, USA, Mali, Uganda, Australia, Norway, Brazil and Canada |
| Dr Oliver Hauser | Business School (Economics) | Dr. Oliver Hauser is a Senior Lecturer in Economics at the University of Exeter Business School and a Research Fellow at Harvard University. His research focuses on social and economic inequality (including gender and racial discrimination) and cooperative and ethical behaviour. Oliver joined the University of Exeter’s Department of Economics in July 2018, where he is also the Theme Lead for economics, business and finance at the Institute for Data Science and Artificial Intelligence and a faculty affiliate of the Centre for Leadership. |
| Dr David Lopez | Business School (INDEX Group) | David is an interdisciplinary scientist interested in the application of AI for social and industrial purposes. He has been involved in data-intensive consulting projects for large companies such as Sky, CENTRICA, Santander Bank and The Chronicle. At present time he is applying advanced natural language processing techniques to: (1) mitigate online harms, (2) understand processes of online deliberation. |
| Dr Mohsen Mosleh | Business School |
Mohsen is a Lecturer (Assistant Professor) at the University of Exeter Business School, a Fellow at Alan Turing Institute, and a Research Affiliate at MIT Sloan School of Management. Mohsen was a postdoctoral fellow at the MIT Sloan School of Management and the Department of Psychology at Yale University. Prior to his post-doctoral studies, Mohsen received his PhD from Stevens Institute of Technology in Systems Engineering with a minor in data science. He has five years of prior industry experience as a Software & Systems Integration Lead. Mohsen studies how misinformation and information biases on social media using digital field experiments, linking survey and digital data, and NLP. His work has been published in leading journals such as Nature, Nature Communications, PNAS, and CHI proceedings and has been covered in major media outlets including The Washington Post, the Telegraph and the Financial Times. |
| Dr Zena Wood | Business School (INDEX Group) | Zena is a Computer Scientist interested in collective analysis, movement pattern analysis and applied ontology. Her work has applications in Smart Cities, transportation and urban planning. Her most recent projects include a focus on the challenges of digital transformation. Many of her projects involve collaborations with experts from geography, psychology and business. |
| Name | Department/College | Profile |
|---|---|---|
| Professor Jason Hall | English | Jason is a historian of literature, culture and science, specializing in the period 1800-1930. His background is in English literature, specifically poetics. His work is characterized by interdisciplinary analysis and involves collaborations with colleges in the physical and computer sciences. At present, he is working on a project focusing on large-scale digital rendering and the analysis of unstructured historical datasets. |
| Professor Jose Iriarte | Department of Archaeology | José is an environmental archaeologist whose research focus on the peopling of the Americas, plant domestication, the emergence of agriculture and the rise of complex societies across the Neotropics. He has developed an interdisciplinary approach that combines the palaeo-sciences (archaeology, palaeoecology, palaeoclimate, ancient DNA) with present landscape characterisation (remote sensing, botany) to understand the modern legacy of past human land uses in the Amazon rainforest. He utilises archaeological datasets and GIS tools to estimate past human populations, predict archaeological sites, and modelled coupled human-environment systems. |
| Professor Leif Isaksen | Department of Classics and Ancient History and the Digital Humanities Lab | As Professor of Digital Humanities, Leif's research interests lie in two distant but related fields: the development of geographic thought and representation in Antiquity and the Middle Ages, and the emerging role of the Web as a transformational medium for communicating and connecting complex information. For the former he has undertaken theoretical and digital analyses of specific documents from ancient world, including the Geographike Hyphegesis of Claudius Ptolemy and the Roman Itineraries. In the latter he applies Web-based (and Linked Open Data) technologies to annotate, connect and revisualize geographic aspects of the past through its textual and material culture, most notably as Director of the Pelagios Commons. |
| Dr Ioana Oltean | Department of Archaeology | As a specialist in the archaeology of the Roman Empire, Ioana uses extensively GIS and a range of above-ground remote sensing (aerial photographs, satellite imagery, airborne laser scanning) to analyse ancient settled landscapes and their evolution from the Late Iron Age to the Roman period, and to quantify the nature and extent of their change through Roman imperialist expansion. Moreover, she is interested in developing automated pattern recognition methods for extracting archaeologically-relevant information from large scale datasets, owed to the ever increasing availability, quality and acquisition frequency in remote sensing data. Highly relevant to cultural heritage management and protection agencies in Britain and beyond, these can offer meaningful solutions to protect archaeological heritage globally and fight the rapidly escalating rate of its destruction through development, climate change or conflict. |
| Dr Charlotte Tupman | Department of Classics and Ancient History and the Digital Humanities Lab | Charlotte Tupman is an ancient historian and digital humanities specialist who works on Latin epigraphy (the study of inscriptions, one of our major sources of evidence for the ancient world). She works on commemorative practices and lettercutting techniques, and is currently applying machine learning to the analysis of a dataset of tens of thousands of images of Roman monuments to illuminate the processes involved in creating inscribed texts. |
| Name | Department/College | Profile |
|---|---|---|
| Dr Hugo Barbosa | Department of Computer Science | Hugo Barbosa is a transdisciplinary scientist whose focus is on data-driven methods and models to complex human behaviours and their interaction with social, economic and physical urban systems. He has a background in Computer Science and Engineering with a large experience in bio-inspired computing, complex networks, machine learning, geospatial data analysis and agent-based modelling. He was a postdoctoral associate at the Physics and Astronomy Department of the University of Rochester, NY and is an alumnus of the prestigious Santa Fé Institute. |
| Dr Federico Caprotti | Department of Georgraphy | Federico is an urban geographer interested in urban futures. Over the last few years, he has been working especially at the interface between eco-urban and smart city research with a focus on future city initiatives in the EU and China. He currently leads the SMART-ECO research consortium, funded by EU and Chinese funding agencies, and has co-edited Inside Smart Cities: Place, Politics and Urban Innovation (Routledge, 2018), which makes the case for the need to engage with specific and often ‘second-tier’ cities for understanding future urban trajectories. |
| Professor Peter Challenor | Department of Mathematics | Peter is a mathematician with broad interests; mainly about uncertainty in the natural world. These range from the statistical analysis of complex numerical models (such as those used to simulate climate) to the interpolation of noisy data and the estimation of the amount of renewable energy in the ocean |
| Professor Peter Cox | Department of Mathematics | Prof Peter Cox is a climate scientist who is based within Mathematics at the University of Exeter. He led the team at the Met Office-Hadley Centre that first included vegetation and the carbon cycle in a climate model projection. Of late, Peter has become very interested in finding ‘emergent constraints’ on the uncertain climate-carbon cycle feedbacks identified in that first study, using an ensemble of model projections to find a mapping between current observations and future changes. This approach involves combining big-data from state-of-the-art Earth System Models, with big-data from ground-based and satellite observations. Peter is therefore very interested in contributing to, and using, techniques developed at the IDSAI. |
| Dr Saptarshi Das | Mathematics and the Environment | Saptarshi is an interdisciplinary data and AI scientist with background in control and power engineering. His present research interests include dynamical systems and control theory, big data analytics, machine learning, computational intelligence, signal processing, and fractional calculus in diverse applications in energy, environment, and biomedical engineering. He is interested in quality of data in diverse engineering system design and decisions, statistical methods for analysing both real-world and simulated data from large and complex mathematical and computational models of low and high dimensional dynamical systems. He has co-authored 2 books and more than 100 papers in refereed scientific journals, conferences and book chapters in these areas. |
| Dr Theo Economou | Department of Mathematics | Theo is an applied statistician with experience in applying statistical models to solve problems in a variety of areas, including environmental sciences, hydroinformatics, epidemiology and public health - with emphasis on connections between these, such as weather effects on health. He is particularly interested in developing statistical models for integrating data sources, such as multiple weather forecasts for optimal weather predictions or hospital level and individual level patient data for estimating the underlying disease risk across space |
| Dr Chris Ferro | Department of Mathematics | Assessing the performance of predictions such as weather forecasts or medical diagnoses helps forecasters to improve their predictions and helps recipients to decide how to respond to predictions. My research aims to improve how predictions are assessed. The statistical tools that I develop are applicable to many phenomena but my main interests are in weather forecasting and climate prediction |
| Dr Bram Kuijper | Department of Biosciences |
Bram is an evolutionary biologist with an interest in how life adapts to rapid environmental change. His background is in theoretical biology, and he uses mathematical and computational models to study how organisms combine multiple sources of information when making decisions. He either develops models to provide novel predictions about evolutionary phenomena or he combines simulation models with experimental datasets to inform and improve existing models of biological adaptation. |
| Professor Tim Lenton |
Department of Geography / GSI | Tim and his group are focusing on understanding key events in the coupled evolution of life and the planet, including human-induced global change, developing an evolutionary model of the marine ecosystem, and on early warning of climate tipping points. Tim is Director of Exeter's Global Systems Institute and works closely with the Deputy Vice-Chancellor for Research on the overall environmental research strategy for the University. |
| Dr Markus Mueller |
Mathematics ESI | Markus is a Senior Lecturer in Applied Mathematics a background in mathematical systems and control theory. He is based at the university’s Environment and Sustainability Institute (ESI). Since joining the ESI, he has developed a strong applied focus on robust and optimal management solutions, working on research questions in energy engineering, buildings and infrastructure, the natural environment, quantitative biology and ecology, and human health and well-being. Markus also works very closely with a number of small and medium enterprises to enable transformative processes, for example, the development of a tool to improve resource efficiency of health-care service providers. |
| Dr Mario Recker | Mathematics and the Environment | Mario is a computational biologists working on the evolutionary ecology of various infectious diseases, including malaria and dengue. He employs a wide range of mathematical and data modelling techniques to investigate host-pathogen interactions at different ecological scales, from within-host infection dynamics to population-level spread of disease. His work frequently involves the analysis of large, complex datasets to discover predictive biomarkers of disease and to inform public health relevant models. |
| Professor Gavin Shaddick |
Department of Mathematics | Gavin is a statistician and data scientist who is interested in how data from multiple, diverse sources can be integrated in a coherent fashion to produce the information required for evidence-based decision making. Of particular interest are computational techniques that allow the implementation of complex statistical models to real-life applications where the scope over both space and time may be very large. His research interests are the theory and application of Bayesian hierarchical models and spatio-temporal modelling in a number of fields including epidemiology, environmental modelling, disease progression in rheumatology and demand profiling in the power industry. |
| Professor David Stephenson |
Department of Mathematics | David is Director of the Exeter Climate Systems (XCS) research centre, which has grown impressively since he founded it upon his arrival in Exeter in 2007. His research focuses on the development and novel application of statistical modelling to understand climate processes and predictions. Since 1989, he has published more than 100 well-cited papers and a leading book on forecast verification |
| Professor Stuart Townley |
Mathematics ESI |
Stuart is an interdisciplinary mathematician who draws on a background in dynamical systems, control theory and systems engineering. His research, funding and publications range from fundamental theory to societal applications and span operator theory, mathematical analysis, adaptive and robust control, industrial applied mathematics, energy engineering, neural networks, e-Health, mathematical biology, evolution and population and conservation ecology. |
| Professor Hywel Williams | Department of Computer Science | Hywell’s research interests focus primarily on the analysis of complex data from the Web and social media, with a particular emphasis on environmental issues. This work includes network analysis and text mining to understand online political and environmental debates, modelling/predicting collective attention in social media, understanding social biases in online news consumption, and using Web data to track natural hazards |
| Name | Department/College | Profile |
|---|---|---|
| Dr Hugo Barbosa | Department of Computer Science | Hugo is a transdisciplinary scientist whose focus is on data-driven methods and models to complex human behaviours and their interaction with social, economic and physical urban systems. He has a background in Computer Science and Engineering with a large experience in bio-inspired computing, complex networks, machine learning, geospatial data analysis and agent-based modelling. He was a postdoctoral associate at the Physics and Astronomy Department of the University of Rochester, NY and is an alumnus of the prestigious Santa Fé Institute. |
| Dr Federico Botta | Department of Computer Science | Federico is a computational social scientist interested in human behaviour, both at the collective and individual level, urban systems and cities, and complex networks. His background in complex systems, behavioural science and physics allows Federico to work on a range of truly interdisciplinary projects. In his research, Federico often uses novel data streams such as those generated thanks to our interactions with the Internet, social media platforms, and the mobile phone network. Federico is also interested in how our usage of smart phones, apps and tracking sensors can be used to better understand our behaviour and wellbeing. |
| Dr Chico Camargo | Department of Computer Science | Chico's research concerns the evolution of information. In his work, he develops new computational tools to study the media we produce and consume, the beliefs we hold and stories we tell, our myths and traditions, as well as the opinions, ideas, and narratives we propagate. To do so, he combines tools and approaches from data science, mathematical modelling of complex systems, information theory, evolutionary biology, cultural evolution, cultural sociology, social and cognitive psychology, and broadly speaking, computational social science. |
| Professor Peter Challenor | Department of Mathematics | Peter is a mathematician with broad interests; mainly about uncertainty in the natural world. These range from the statistical analysis of complex numerical models (such as those used to simulate climate) to the interpolation of noisy data and the estimation of the amount of renewable energy in the ocean |
| Dr Fabrizio Costa | Department of Computer Science | Fabrizio's main research interest is in extending Machine Learning techniques to complex and structured data. The application domains of such algorithms range from biotechnology (the prediction of the properties of a drug), to medicine (what is the next gene to study to gain more understanding in the mechanism of a disease), to language processing (given a sentence disambiguate to which noun is a specific pronoun referring to). Recently his interests focused on the development of constructive algorithms, that is programs that can learn how to build new objects endowed with some desired property, for example building novel drugs or novel web site in an automatic way. |
| Dr Saptarshi Das | Mathematics and the Environment | Saptarshi is an interdisciplinary data and AI scientist with background in control and power engineering. His present research interests include dynamical systems and control theory, big data analytics, machine learning, computational intelligence, signal processing, and fractional calculus in diverse applications in energy, environment, and biomedical engineering. He is interested in quality of data in diverse engineering system design and decisions, statistical methods for analysing both real-world and simulated data from large and complex mathematical and computational models of low and high dimensional dynamical systems. He has co-authored 2 books and more than 100 papers in refereed scientific journals, conferences and book chapters in these areas. |
| Dr Riccardo Di Clemente | Department of Computer Science | Riccardo is an interdisciplinary scientist interested in data-driven analysis to understand the relation between human mobility and social interactions that lead to the socio-economic structures in our cities. He worked at MIT on a project funded by the Gates Foundation and the UN to develop new methodologies using Complex Systems and Computational Science tools to analyse credit card data and discover new patterns in peoples’ socio-economic behaviours. He has been awarded of the Newton International Fellowship from the Royal Society to study the digital traces of human mobility. In his recent data4good projects he uses mobile phone data to develop data-driven approaches, for spatial planning and disaster resilience. |
| Dr Anjan Dutta | Department of Computer Science | Anjan is a Computer Scientist interested in Computer Vision and Machine Learning with applications to the broad area of visual information recognition, detection and retrieval. He is interested in developing intelligent machines from limited amount of supervision, which includes the areas of unsupervised representation learning, multi-view representation, low-shot and lifelong learning, graph structured representation etc. |
| Dr Theo Economou | Department of Mathematics | Theo is an applied statistician with experience in applying statistical models to solve problems in a variety of areas, including environmental sciences, hydroinformatics, epidemiology and public health - with emphasis on connections between these, such as weather effects on health. He is particularly interested in developing statistical models for integrating data sources, such as multiple weather forecasts for optimal weather predictions or hospital level and individual level patient data for estimating the underlying disease risk across space. |
| Professor Richard Everson | Department of Computer Science / IDSAI | Previously Head of Department for Computer Science in Exeter, Richard is Professor of Machine Learning and Director of the Institute for Data Science and Artificial Intelligence. His research interests are in machine learning, statistical pattern recognition, multi-objective optimisation and the links between them. Current areas of focus are in optimisation in wireless and mobile networks to maintain quality of service, in automatic analysis of video and accelerometer data for inferring behaviour of animals (funded by NERC and the Open Innovation Platform) and people (with the Royal Devon and Exeter Hospital), and in modelling big data storage systems (with the Met Office). |
| Dr Chris Ferro | Department of Mathematics | Assessing the performance of predictions such as weather forecasts or medical diagnoses helps forecasters to improve their predictions and helps recipients to decide how to respond to predictions. My research aims to improve how predictions are assessed. The statistical tools that I develop are applicable to many phenomena but my main interests are in weather forecasting and climate prediction |
| Professor Jonathan Fieldsend | Department of Computer Science | Jonathan is Associate Professor in Computational Intelligence with specific expertise in developing multi-objective/non-traditional objective optimisation methods, multi-modal optimisation, optimisation with uncertainty, evolutionary approaches to learning, data visualisation, as well as the use of Bayesian classification/modelling techniques. |
| Professor Ed Keedwell | Department of Computer Science | Ed is a Computer Scientist with interests in optimisation and machine learning with applications to bioinformatics and hydroinformatics. He has particular interests in the beneficial combination of optimisation and machine learning both to discover new insight in large-scale biological (e.g. GWAS) and hydrological data sets and to create new approaches to learning optimisation algorithms known as hyperheuristics |
| Dr Lorenzo Livi | Department of Computer Science | Lorenzo is a member of the Computer Science Department at Exeter (0.2FTE). His research interests revolve around machine learning, time-series analysis and complex (networked) dynamical systems, with applications in systems biology and computational neuroscience. Dr Livi’s theoretical research focuses on recurrent neural networks and their dynamics, and change detection on sequences of time-varying graphs. Applications of interest include prediction of epileptic seizures by combining machine learning and complex network methods, and the design of generative models of networks representing protein native structures |
| Dr Chunbo Luo | Department of Computer Science | Chunbo’s research interest mainly focuses on model based and machine learning algorithms to address issues from contemporary networks and UAV networks, as well as the data that are transported by these networks. He received his PhD on the study of high performance cooperative networks, with further investigation on cooperative strategies and spatial-temporal data processing techniques for UAV networks. |
| Dr Daniel Maxwell | Department of Computer Science | Daniel is a lecturer in Computer Science with a background in modelling and forecasting, dataflow programming, and software engineering processes. He is interested, in particular, in making knowledge more usable, building rich two-way communication between research and its applications, crowd-sourcing of knowledge and deliberative decision-making. |
| Professor Ronaldo Menezes | Department of Computer Science | Ronaldo is a Brazilian-American scientist who focuses on the use of data and network science to solve societal problems, and on the development of swarm-based systems and their applicability to real-world problems. His work has been funded by the ONR, NSF and ARO (in the USA). CNPq (in Brazil) and since moving to the UK in 2018 by InnovateUK. His research has been featured in places such as MIT Technology Review and New Scientist. He worked in the USA for 18 years before moving to Exeter where he leads the BioComplex Lab. Ronaldo is the editor-in-chief of the prestigious Applied Network Science journal published by Springer Nature and is also a member of several boards associated with Network Science including CompleNet, NetSci and Lanet. His research ideas have been used to tackle health disparities in minority groups, understanding urban crime regularities, patterns of human migration, socio-economic differences in human mobility, epidemics in cattle, and echo chambers in science, to mention a few. |
| Dr Alberto Moraglio | Department of Computer Science | Alberto's research area is evolutionary computation for optimisation and machine learning. He is the founder of a general geometric theory which unifies evolutionary algorithms across representations and has been used for the principled design of new successful search algorithms, and for their rigorous theoretical analysis, including a widely used form of genetic programming based on program semantics. A recent research interest of his is solving combinatorial optimisation and machine learning problems on quantum computers. |
| Dr Marcos Oliveira | Department of Computer Science | Marcos is a scientist interested in understanding real-world complex systems using data-driven approaches with a focus on cities, human dynamics, and self-organising mechanisms. In particular, he is interested in uncovering how urban crime emerges and exhibits regularities in cities. His research also involves understanding the mechanisms behind inequality in urban areas and social environments. He also investigates how self-organising interactions drive intelligence in swarm intelligence algorithms. He is a Lecturer in City Science & Analytics with the Department of Computer Science. |
| Dr Anastasios Roussos | Department of Computer Science (Honorary) | Anastasios is a Principal Researcher at the Institute of Computer Science, Foundation for Research and Technology - Hellas (FORTH), Greece and Honorary Senior Lecturer in the Department of Computer Science at Exeter. His research specialises in the fields of Computer Vision, Machine Learning, Variational Methods and Partial Differential Equations. The focus of his current research is the development of novel methods for detailed 3D modelling and reconstruction of real-world objects from image data. The main motivation for his work stems from the vision of building robust 3D Computer Vision methodologies that would provide highly-accurate estimations in challenging real-world scenarios. |
| Dr Sareh Rowlands | Department of Computer Science | Sareh is a computer vision scientist interested in computer vision applications such as robotics and medical diagnosis. Her background includes using non-Euclidean geometry in visual recognition and implementing computer vision approaches in robotic scenarios. She uses her expertise to model human actions in order to anticipate or predict an action before it occurs. This facilitates enhanced human-robot collaboration. This is mostly achieved by analysis and learning relevant datasets that capture human actions in a complex task using techniques such as deep learning, graphical models and etc. |
| Professor Gavin Shaddick | Department of Mathematics | Gavin is a statistician and data scientist who is interested in how data from multiple, diverse sources can be integrated in a coherent fashion to produce the information required for evidence-based decision making. Of particular interest are computational techniques that allow the implementation of complex statistical models to real-life applications where the scope over both space and time may be very large. His research interests are the theory and application of Bayesian hierarchical models and spatio-temporal modelling in a number of fields including epidemiology, environmental modelling, disease progression in rheumatology and demand profiling in the power industry. |
| Dr Stefan Siegert | Department of Mathematics | Stefan has an interdisciplinary background in Theoretical Physics, Computational Science and Statistics. His research interests are in predictability of complex systems, particularly the climate system. He is developing new methodology to evaluate the quality of weather and climate forecasts, and statistical modelling methods to improve the predictive performance of numerical simulations. |
| Dr Massimo Stella | Department of Computer Science |
Massimo is a Lecturer in Computer Science (E&R) with research focusing on cognitive data science and complex networks through knowledge representations and language modelling. He has interests in approaches that combine and develop tools from quantitative areas like complex networks, machine learning and social media mining. His data science investigations are guided by a synergy of theoretical models from computational cognitive science, neuroscience and psycholinguistics. Massimo has also founded his own business for scientific consulting, Complex Science Consulting, which collaborates with several international partners and innovative start ups. |
| Professor David Stephenson | Department of Mathematics | David is Director of the Exeter Climate Systems (XCS) research centre, which has grown impressively since he founded it upon his arrival in Exeter in 2007. His research focuses on the development and novel application of statistical modelling to understand climate processes and predictions. Since 1989, he has published more than 100 well-cited papers and a leading book on forecast verification |
| Dr Oliver Stoner | Department of Mathematics / IDSAI | Oliver is an applied statistical data modeller, working primarily in the fields of environment and health. His main strength is using Bayesian hierarchical models, which may involve complex spatio-temporal structures, to estimate relationships and make predictions. He has a data-driven approach to modelling, where methods are considered and developed in the context of real world problems. |
| Professor Danny Williamson | Department of Mathematics | Daniel is a Bayesian statistician whose research interests include uncertainty quantification, decision theory and support, statistical foundations, Bayesian modelling and Bayesian computation. His research develops methods and theory in these areas combining ideas that span from mathematical Analysis to machine learning. His applied work has largely focused on climate models including how they can be calibrated/tuned and in using them to quantify uncertainty for the real climate in combination with data to support decision making. He has also worked on using large public surveys to design interventions to help reduce traffic congestion |
| Name | Department/College | Profile |
|---|---|---|
| Dr Adrian Currie | Department of Sociology Philosophy and Anthropology (Egenis) | Adrian is primarily interested in how scientists successfully generate knowledge in tricky circumstances: where evidence is thin on the ground, targets are highly complex and obstinate, and our knowledge is limited. This has led him to examine the historical sciences – geology, palaeontology and archaeology – and to argue that the messy, opportunistic (‘methodologically omnivorous’) and disunified nature of these sciences often underwrites their success. His interest in knowledge-production has also led him to think about the natures of, and relationships between, scientific tools such as experiments, models and observations, as well as in comparative methods in biology. He also has an interest in how we organize scientific communities, particularly regarding scientific creativity. |
| Professor Sabina Leonelli | Department of Sociology Philosophy and Anthropology (Egenis) | Sabina Leonelli works in the philosophy, history and social studies of data science and AI, and heads the Data Studies research strand within Egenis (the Exeter Centre for the Study of the Life Sciences). Her research investigates the implications of specific ways of managing, mobilising and (re)using data for the knowledge bring produced, with particularly emphasis on the biological and biomedical domains; and the standards, presuppositions, ethics and social concerns involved in sharing data, with reference to the implementation of Open Science and the FAIR principles. She has published widely on data epistemology, governance and ethics, including the books Data-Centric Biology: A Philosophical Study (2016) and The Impact of Big and Open Data on Research (2018). |
| Professor Brian Rappert | Department of Sociology Philosophy and Anthropology (Egenis) | Brian Rappert is a Professor of Science, Technology and Public Affairs. His long term interest has been the examination of the management of information. In particular, he has investigated the social, ethical, and political issues associated with researching secrecy. His work thus often addresses situations in which data is limited and its circulation is curtailed. |
| Dr Niccolo Tempini | Department of Sociology Philosophy and Anthropology (Egenis) | Niccolò Tempini is an interdisciplinary social scientist interested in questions of information, data, technology, organization, value and knowledge. He researches big data research and digital infrastructures, investigating the specific knowledge production economies, organization forms and data management innovations that these projects engender with a focus in their social and epistemic consequences. He studies the practices of data scientists, software developers, researchers and non-professionalised experts, to understand how different forms of knowledge and value intersect with each other when different actors come to grips with new methods and new forms of data, information technology and organization. |
| Dr Hugh Williamson | Department of Sociology Philosophy and Anthropology (Egenis) | Hugh Williamson is a social anthropologist interested in the use and management of data in the biosciences, and plant science in particular. His research uses qualitative methods to look at the political, social and epistemic implications of post-genomic data production, circulation and analysis. He is especially interested in the convergence of quantitative genetics and selection theory with genomic and phenomic technologies in plant breeding, and with understanding how data-driven changes to the organisation of breeding will affect global food systems. |
| Dr Dana Wilson-Kovacs |
Department of Sociology Philosophy and Anthropology (Egenis) |
Dana is a qualitative sociologist interested in occupational dynamics, data management practices and organisational change in relation to the development and use of digital forensic technologies in law enforcement. Her current research explores the transformation of digital trace into evidence and the ways in which such evidence is used in the criminal justice system. She is the Principal Investigator on a three-year ESRC-funded study that examines the development of digital forensics capabilities in police forces in England and Wales (link to the project page: https://www.digital-forensics-in-policing.net/) |
| Name | Department/College | Profile |
|---|---|---|
| Professor Rob Beardmore | Department of Biosciences | Antibiotic resistant microbes are an immense risk for human medicine. I take the perspective that while the discovery of new small molecules is needed, it will not be the only answer. I therefore undertake complementary work on fundamental evolutionary and pharmacological questions. After all, we are here because of a lack of understanding of the rapidity of microbial adaptation so I take a quantitative, mathematical approach and apply it to in-house laboratory data to better understand how might predict, and somehow control, that rapidity. My lab works in close collaboration with engineers, microbiologists and clinicians to address this from a highly inter-disciplinary perspective |
| Dr Fabrizio Costa | Department of Computer Science | Fabrizio's main research interest is in extending Machine Learning techniques to complex and structured data. The application domains of such algorithms range from biotechnology (the prediction of the properties of a drug), to medicine (what is the next gene to study to gain more understanding in the mechanism of a disease), to language processing (given a sentence disambiguate to which noun is a specific pronoun referring to). Recently his interests focussed on the development of constructive algorithms, that is programs that can learn how to build new objects endowed with some desired property, for example building novel drugs or novel web site in an automatic way. |
| Professor Lora Fleming | ECEHH, Medical School | Professor Lora E Fleming is a physician and epidemiologist with expertise in Oceans and Human Health based at the European Centre for Environment and Human Health [www.ecehh.org] (University of Exeter Medical School). The research and training at the European Centre is focused on an interdisciplinary approach to the interactions between the health of both humans and the environment. Prof Fleming is interested in the interactions around big data, communities, and environment and human health. In particular, she has co-organized international meetings and co-edited two textbooks and numerous articles dealing with Oceans and Human Health; and she received the Ocean and Human Awards from Edouard Delcroix Foundation and the IOC Bruun Award. Prof Fleming is leading the H2020 funded BlueHealth Project (https://bluehealth2020.eu) and a new H2020 funded Seas, Oceans and Public Health in Europe (SOPHIE) Project to establish a network and create a strategic research agenda for Oceans and Human Health in Europe and beyond. |
| Professor Tim Frayling | Medical School | Data science in human genetics and health Tim Frayling leads research that aims to understand how the human genome affects health and disease. This research uses tens of millions of pieces of information from our DNA, and 1000s of measurements, including electronic health records, from 100,000s to millions of people. His research focuses on obesity and type 2 diabetes and the data available provides an unprecedented opportunity for making new discoveries of biological and clinical relevance. |
| Professor Mark Kelson | Department of Mathematics | Mark is a statistician with a background in clinical trials. His research focuses on both mental health and physical activity. In particular, he is excited by recent advances in the field of accelerometry data collection and believes data science, underpinned by appropriately rigorous statistical methodology, can be usefully applied in this area to greatly increase our understanding of the impact of activity on health |
| Professor David Llewellyn | Medical School | David is a clinical epidemiologist interested in how data science and machine learning can improve patient and carer outcomes whilst increasing healthcare system efficiency. For example, he has developed a system called DECODE which makes it easier to detect dementia in a timely fashion and is currently being trialled in the NHS. He believes that artificial clinical intelligence has enormous potential to augment existing resources and enhance diagnosis, prognosis and targeted treatments. He is interested in working with healthcare providers and industry to accelerate the application of new discoveries |
| Professor Tom Monks | Medical School / IDSAI | Tom is a methodologist with expertise in applying computer simulation methods, optimisation and machine learning in health service delivery. His work aims to translate Data Science and Operational Research tools to improve the quality and safety of health and social care. |
| Professor Karyn Morrissey | ECEHH, Medical School | Professor Karyn Morrissey is an economist by background but completed her interdisciplinary PhD in a School of Geography. Through her use of various datasets including traditional survey data such as the Census of Population and Health Survey of England, newer web sourced Big Data and administrative data (Hospital records, etc), Karyn’s research cuts across geography, economics and sociology with a particular focus on health and environmental inequalities. Her PhD focused on the estimation of the prevalence of non-communicable diseases at the small area level. Over the last 8 years, Karyn has developed a substantial research profile in applied health statistics and geo-computational methods, particularly spatial microsimulation and small area estimation techniques. Karyn is increasingly interested in the relationship between social and physical environments on health outcomes across the lifecourse. |
| Dr Jonathan Phillips | Department of Biosciences/Living Systems Institute | JJ's research seeks to understand and control the dynamic behaviour of protein molecules to perform biochemical computing. His background is in the advancement of computational and experimental methods to study protein dynamics at high spatial and temporal resolution. Data generation is tightly linked with the construction of statistical mechanics and structural models, in order to describe how information is processed at a molecular level in natural, biomedical and artificial systems. |
| Professor Martin Pitt | IHR | Professor Martin Pitt is Director of PenCHORD - The Peninsula Collaboration for Health Operational Research and Development. PenCHORD (part of the SW CLAHRC in Exeter University: Medical School) is a research team which works in close collaboration with NHS organisations in the south-west of the UK to improve health and care delivery using Operational Research methods. Martin has wide ranging experience in healthcare modelling ranging from economic modelling in health technology assessment to discrete event simulation and operational models for service re-design. His research interests are the application of modelling techniques and data science to improve health and care with a particular interest in the implementation of these approaches to policy and decision making process. He was recently appointed as first President of the Association of Professional Healthcare Analysts (AphA) the organisation which represents health service analysts across the NHS. |
| Professor Krasimira Tsaneva-Atanasova | Department of Mathematics/Living Systems Institute | Krasimira’s research interests lie in the field of applied mathematics for biomedicine and healthcare. Her training in mathematical biology has enabled her to engage in very productive collaborations with biomedical scientists and clinicians working on problems related to endocrinology (e.g. Diabetes, Reproductive system function) and neuroscience (e.g. learning and memory). More recently she has developed an interest in applications at the interface of movement science, psychology and neurology (e.g. Psychosis and Parkinson’s disease) involving modelling and analysis of large, complex data sets capturing movement (e.g. Kinematics and Dynamics) along with measure of (neuro-)physiological activity (e.g. EMG, EEG, etc.) |
| Name | Department/College | Profile |
|---|---|---|
| Professor Susan Banducci | Q step, Department of Politics | Susan is the director of the Exeter Q-Step Centre. Her research interests are in the areas of comparative political behaviour, media and political communication. One of her current research projects is Measuring Information Exposure in Dynamic and Dependent Networks (ExpoNet) which involves extracting, analysing and measuring media content to model the linkages between consumers and producers of media content in complex information networks, and understand co-development of network structures with consumer attitudes/behaviours. |
| Professor Ana Beduschi | Department of Law |
Ana Beduschi is a Professor of Law at the University of Exeter. Her research focuses on international human rights law, technology, digital law, data protection and privacy, and international migration and refugee law. Her recent publications examine the impact of artificial intelligence on human rights and data protection, the opportunities and challenges presented by digital identity, and the implications of big data and artificial intelligence for international migration and human rights law. She has recently led the project COVID-19: Human Rights Implications of Digital Certificates for Health Status Verification, funded by the UKRI/ESRC. |
| Dr Chico Camargo | Department of Computer Science | Chico's research concerns the evolution of information. In his work, he develops new computational tools to study the media we produce and consume, the beliefs we hold and stories we tell, our myths and traditions, as well as the opinions, ideas, and narratives we propagate. To do so, he combines tools and approaches from data science, mathematical modelling of complex systems, information theory, evolutionary biology, cultural evolution, cultural sociology, social and cognitive psychology, and broadly speaking, computational social science. |
| Dr Miriam Koschate-Reis | Department of Psychology | Boundaries between digital technologies and ourselves become blurred as technology is integrated into our work, home, even our bodies. Interdisciplinary research is needed to understand how our sense of self - our psychological identity - affects and is affected by technology use. Miriam extends current research on privacy by considering how our different psychological identities shape what we find acceptable to reveal in different situations. Miriam also develops the capacity to detect psychological identities from naturally occurring digital data (e.g., forum posts, blogs, e-mails). This research will allow us to understand which psychological identity (e.g., parent, addict, criminal network identity) is relevant while a person is communicating. |
| Professor Mark Levine | Department of Psychology | Mark is a Professor of Social Psychology at Exeter University. His research focuses on the role of identities and group processes in pro-social and anti-social behaviour. He is particularly interested in the research possibilities afforded by new technologies and digital data. This has included systematic behavioural analysis of CCTV footage of real life violent incidents in night-time economy zones in British town centres. He has also used immersive virtual environments to study the behaviour of bystanders in violent emergencies. More recently he has been analyzing naturally occurring online text data to study identity and privacy concerns. He is also interested in the utility of tracking and sensing technologies for examining contact in public places, and the effect this can have on social cohesion and intergroup relations |
| Dr Chris Playford | Department of Sociology Philosophy and Anthropology | Chris is a sociologist with interests in education and the occupational backgrounds and destinations of young people. He uses large-scale survey and administrative datasets to answer social science questions. He specialises in the application of statistical models to better understand the educational routes taken by young people. Chris is the director of the MSc Policy Analytics. |
| Name | Department/College | Profile |
|---|---|---|
| Dr Tim Dodwell | Department of Engineering | Tim is an applied mathematician interested in developing new methods for solving mathematical models for large complex systems with data. An overarching theme of his research is to exploit different scales to develop efficient, rigorous and computationally tractable methods for industry-focused problems across the high value manufacturing, geoscience and healthcare sectors. |
| Professor Jonathan Fieldsend | Department of Computer Science | Jonathan is a Professor in Computational Intelligence. His main areas of research are: developing multi-objective/non-traditional objective optimisation methods, multi-modal optimisation, optimisation with uncertainty, evolutionary approaches to learning, data visualisation, as well as the use of Bayesian classification/modelling techniques. |
| Professor Guangtao Fu |
Department of Engineering |
Guangtao’s research interests lie in the development of computer models, optimisation algorithms and data analytics for control and management of water infrastructure systems including water distribution, urban wastewater and green infrastructure. His current research focuses on tackling the water management challenges in leakage, urban flooding, sewer overflow discharges and energy efficiency using new data analytics and artificial intelligence tools |
| Professor Zoran Kapelan |
Department of Engineering |
Zoran Kapelan is Professor of Water Systems Engineering and Academic Lead of the Water and Environment Group. His background is in water engineering and research interests are in developing data analytics, smart water technologies and generally novel methods addressing a wide range of challenges in urban water infrastructure. He works closely with the UK water industry which is now using some of the technologies he has developed. |
| Professor Dragan Savic |
Department of Engineering |
Dragan Savic is Professor of Hydroinformatics, a founder and former co-director of the Centre for Water Systems (www.ex.ac.uk/cws), in the College of Engineering Mathematics and Physical Sciences (CEMPS) at the University of Exeter, which is an internationally recognised group for excellence in water and environmental science research. His research interests cover the interdisciplinary field of Hydroinformatics, which transcends traditional boundaries of water/ environmental sciences, informatics/ computer science (including Artificial Intelligence, data mining and optimisation techniques) and environmental engineering. Applications are generally in the hydro-environmental science/ engineering areas, including water resources management (both quality and quantity), flood management, water & wastewater systems and environmental protection & management. |
| Dr Oleksandr Kyriienko |
Department of Physics and Astronomy |
Oleksandr is a theoretical physicist working in the field of quantum technologies. His interests lie in quantum optics and computing, where he develops algorithms and device proposals for quantum information processing tasks. Recently Oleksandr has been working to advance the emergent area of quantum machine learning. You can find more details on a group page https://kyriienko.github.io/ |
The IDSAI Cornwall Research Hub is led by Dr Saptarshi Das and Dr Bram Kuijper. It focussed on real-world data-driven fundamental and applied research in
- machine learning,
- big data analytics,
- computational statistics and artificial intelligence (AI) methods to solve various challenges arising in control theory and optimisation,
- dynamical systems,
- signal, image and video processing,
- large-scale and computing intensive numerical modelling with diverse application areas in renewable energy, environment, geosciences and mining engineering,
- mathematical and computational biology,
- epidemiology,
- fluid dynamics,
- biomedical engineering,
- AI for industrial innovation and business,
- space plasma physics/space weather.
It aims to facilitate co-ordination of cross-disciplinary theoretical and applied research on data science and AI in the context of regional expertise in Cornwall and internationally, by engaging with local and global industries, small and medium-size business and other stakeholders. We closely work with the colleagues from the Environment Mathematics (Enviro-Math), Environment and Sustainability Institute (ESI), Centre for Ecology and Conservation (CEC), Camborne School of Mines (CSM), Renewable Energy and Energy Policy Group at the Penryn Campus, and the European Centre for Environment & Human Health (ECEHH) at the Truro Campus. In the ESI based data science and AI activities, we apply dynamical systems and control theory to issues in natural and human population demography, resource management, conservation ecology, biodiversity and environmental growth, and cyber-physical systems in the context of health and well-being.
The IDSAI Cornwall Hub aims to bring together diverse complementary expertise using both quantitative and qualitative data from physical, environmental, biological, medical, engineering, economic and social sciences in order to create new transdisciplinary collaborations and novel research project ideas.
Four new MSc applied data science courses
- MSc Applied Data Science and Modelling
- MSc Applied Data Science (Renewable Energy):
- MSc Applied Data Science (Environment and Sustainability)
- MSc Applied Data Science (Ecology and Evolution)
Any informal queries from potential PGT, PGR, Post-doctoral students and industrial collaborators/SMEs can be made to Bram Kuijper and Saptarshi Das.
Turing Fellows are established scholars with proven research excellence in data science, artificial intelligence, or a related field. They contribute to new ideas, drive collaborative projects, secure external funding and provide research expertise which is actively connected with the Institute and its network of universities and industry partners.
The University has created a centralised Research Software Engineering (RSE) group that will assist our research community with complex and bespoke research software needs.
