Meet the ART-AI team and read about their research interests and backgrounds.
Marina De Vos
Brent W Kiernan
Eamonn O’Neill
Emma Carmel
Alan Hunter
Charles Larkin
Ben Metcalfe
Julian Padget
Özgür Şimşek
Andrew Barnes
Maria Battarra
Neill Campbell
Xi Chen
Iulia Cioroianu
Hilde Coffé
Darren Cosker
Damien Coyle
Nello Cristianini
Carmen Domene
Katharine Fraser
Alinka Gearon
Gosia Gocłowska
Matthew Grayson
Tom Haines
Ralph Hertwig
Janina Hoffmann
Olga Isupova
Edmund Keogh
Lisa Maria Kreusser
Banafshé Larijani
Hugh Lauder
Ron Lavi
Furong Li
Wenbin Li
Anthony Little
Alexander Lunt
Christof Lutteroth
Gregory Maio
Uriel Martinez-Hernandez
Polly McGuigan
Ben Metcalfe
Subhadip Mukherjee
Vinay Namboodiri
Linda Newnes
Nick Pearce
Elise Pegg
Karin Petrini
Michael Proulx
Paulo Rocha
Sandipan Roy
Elena Seminati
Pranav Singh
Alexandra de Sousa
George Stothart
Harish Tayyar Madabushi
Mike Tipping
Araxi Urrutia
Dingguo Zhang
Jie Zhang
Christina Squire
Mark Townsend
Marina is a senior lecturer in the Department of Computer Science working in the area of artificial intelligence.
Her research area is knowledge representation and reasoning, using answer set programming, a logic-based declarative programming language, to model human/agent decision-making.
Currently, her work focuses on the modelling, the explanation and the verification of normative and policy-based reasoning in the areas of legal and socio-technical systems. In these systems participants, human and computational agents’ behaviour is guided by a set of norms/policies that describe expected behaviour. Non-compliance can be monitored and penalised while compliance is rewarded. Through a formal model, and corresponding implementation, the behaviour of the entire system can be proven and explained.
Beyond normative modelling, she is interested in the software development for AI systems in general and logic-based systems more specifically and their use in wider society.
Marina has supervised and co-supervised more than 10 PhD students. Within her research field she has organised a number of Doctoral Consortia and has been involved in mentoring PhD students from different institutions.
She is always keen to hear from committed students working in her broad research areas. She is more than happy to discuss ideas and work with potential students to flesh out their ideas and plans.
Symbolic artificial intelligence in knowledge representation and reasoning.
Modelling the knowledge or expertise available in a system rather than extracting information from large collections of data.
Verifiable, explainable AI.
Normative and policy-based reasoning in the areas of legal and socio-technical systems.
Combining symbolic and statistical AI.
Brent has worked at the universities of Cambridge, Nottingham, Sheffield, Leicester and Warwick. At Warwick, he was involved in the administration and management of the Systems Biology Doctoral Training Centre and the EPSRC Centres for Doctoral Training in Integrated Magnetic Resonance and Diamond Science and Technology. He moved to the University of Bath in 2017, firstly as manager of the EPSRC Centre for Doctoral Training in Digital Entertainment. He has been Centre Manager of ART-AI since its foundation.
Eamonn is Professor of Computer Science and Head of the Department of Computer Science. Current projects include investigating potential feedback loops between human and machine learning, and understanding perception, salience and attention in virtual environments. He has led large interdisciplinary projects and technology transfer activities over many years. Examples include the Cityware project involving Bath, Imperial, UCL and companies including HP, Vodafone and Nokia. He was Academic Coordinator of the EPSRC/Mobile VCE Research Programme in User Interactions for Breakthrough Services, involving the universities of Bath, Bristol and Glasgow, the London School of Economics, HMGCC and companies including Alcatel-Lucent, BBC, Fujitsu, Huawei, NEC, Nokia Siemens Networks, Orange, Thales, Toshiba, Turner and Vodafone. He has held a Royal Society Industry Fellowship and an EPSRC Knowledge Transfer Fellowship with Vodafone Group R&D, producing UK, European and US patents on intelligent, interactive mobile services, and is currently working with commercial, academic and other partners.
Eamonn’s research covers the range of technological, cognitive and social challenges and opportunities that interactive and intelligent systems offer. His main research interests are in developing, evaluating and understanding innovative forms of human-technology interaction and technology-mediated human-human interaction. Key topics involve innovative forms of human-technology interaction and technology-mediated human-human interaction, including interaction with intelligent machines and software. Current projects include investigating potential feedback loops between human and machine learning, and understanding perception, salience and attention in virtual environments.
Emma works at the intersection of sociology, politics and political economy to investigate how social and political order is imagined, produced and contested in a range of empirical contexts.
There are three strands to her current work. First, theorising governance and governance analysis as regimes of governing practices. Second, she has a new strand of research investigating the socio-political implications of emerging digital statehoods and the use of digital and algorithmic tools as governing practices. Third, she continues her long-standing work on how governance of migration shapes social relations and political economy in/beyond Europe. Emma has particular methodological expertise in qualitative comparative research.
Emma has supervised and co-supervised more than 10 PhD students, and has twice been nominated for a university prize for excellence in doctoral supervision. She is always keen to hear from committed students working in her broad research areas.
Governance analysis: society, politics and policy.
Digital statehoods: AI and automation as governing practices and their implications.
Migration governance and the production of socio-political order(s) in the EU and beyond.
Alan was born in New Zealand and studied at the University of Canterbury (NZ), obtaining a BE (Hons I) degree in electrical and electronic engineering in 2001 and a PhD on synthetic aperture sonar (SAS) in 2006. He left New Zealand for Europe in 2007.
For the next three years, Alan was a research associate at the University of Bristol, where he worked with ultrasonic arrays for non-destructively inspecting engineering components. Here, he developed auto-focusing algorithms for imaging the interiors of objects with complex geometries and material properties.
In 2010, he moved to the Netherlands and spent four years as a defence scientist at TNO (Netherlands Organisation for Applied Research) in The Hague. At TNO, he developed underwater technologies for the Royal Dutch Navy, including sub-sediment imaging sonar, diver detection sonar, and autonomous naval mine-hunting systems.
Before returning to England in 2014, Alan spent three months in La Spezia, Italy, as a visiting scientist at the NATO Centre for Maritime Research and Experimentation (CMRE). During this time, he developed precision micro-navigation algorithms for SAS imaging of the seafloor over repeated passes.
His research interests are in underwater acoustics, signal processing, imaging, and machine intelligence. He is particularly interested in applications in underwater remote sensing using sonar and marine robotics.
Charles Larkin, (Discip. Schol.) B.A., Ph.D. [TCD] is Director of Research at the Institute for Policy Research at the University of Bath. Between 2011 and 2020 he was special advisor to the Chairman of the Oireachtas Committee on Health, Dr Michael Harty, TD (Ind.) and to Senator Sean Barrett (Ind.) of the Irish Senate.
Dr Larkin is an adjunct assistant professor at Trinity College Dublin, Johns Hopkins University and the Institute of Public Administration (Dublin). At Johns Hopkins he teaches Global Political Economy as part of a suite of programmes in the Advanced Academic Programs department. At the IPA (Dublin), he teaches a series of masterclasses on economic thought and regulation.
Dr Larkin is the Chair of the Governing Authority of Technological University Dublin and has been a member of that body since July 2019. He holds an additional non-executive director position on the board of Accounting Technicians Ireland since May 2020.
Dr Larkin has authored several items of Irish legislation and over 60 scholarly articles, most especially in the areas of finance, cryptocurrencies and public policy economics. His academic papers can be found here.
Public Policy.
Cryptocurrencies.
Economic History.
History of Economic Thought.
Health/Education Policy.
Ben is Head of the Department of Electronic & Electrical Engineering, Deputy Director of the Institute for the Augmented Human, Deputy Director of the Centre for Biosensors, Bioelectronics and Biodevices and Vice-President (Academic) of the Institute of Physics and Engineering in Medicine.
Ben is a biomedical engineer with expertise in wearable and implantable neural interfaces for both rehabilitation and enhancement. His work is funded by the EPSRC and the NIHR and covers the spectrum from speculative research to clinical trials and product development. His core skills are in signal processing and both animal and human electrophysiology.
Advanced neural interfaces.
Biologically inspired autonomous systems.
Biomedical signal processing for both in-vivo and ex-vivo applications.
Neuronal modeling and computing.
Julian started programming as a teenager, sending punch cards by post to Imperial College, which lead to doing Computer Science at Leeds and then a PhD at Bath. Initially, his research was in symbolic computation, computer algebra and parallel and distributed systems. His focus shifted to AI, specifically intelligent agents and virtual institutions in the mid 1990s, which currently takes the form of policy modelling, legal reasoning and the safety and transparency of symbolic and statistical AI systems.
Multiagent systems.
Agent architecture; agent-based simulation; norm representation and reasoning; distributed ledgers; fusing symbolic and statistical AI; policy modelling; security and privacy; models of narrative.
Özgür Şimşek is a Professor of Artificial Intelligence at the Department of Computer Science, where she is Deputy Head of Department and the Head of the Artificial Intelligence and Machine Learning Research Group. Earlier, she served as Deputy Director at Bath’s Institute for Mathematical Innovation.
Before joining the University of Bath in 2017, Özgür was a research scientist at the Center for Adaptive Behaviour and Cognition at the Max Planck Institute for Human Behaviour in Berlin, Germany. She received her PhD in Computer Science in 2008 from the University of Massachusetts Amherst.
Her research spans a broad range of areas in machine learning, including reinforcement learning, supervised learning, learning from small data sets, and bounded rationality. Her applied and theoretical work in machine learning has appeared in leading venues, including Proceedings of the National Academy of Sciences, KDD, ICML, and NeurIPS. She is one of the authors of the book Classification in the Wild: the Science and Art of Transparent Decision Making (MIT Press, 2021).
Machine learning.
Artificial intelligence.
Reinforcement learning.
Bounded rationality.
Network science.
Andy is a Lecturer in Artificial Intelligence in the Department of Computer Science at the University of Bath.
Originally graduating from the University of Plymouth with a degree in Computer Science, Andy went on to work as a data and software engineer for several years. Following this, he completed his PhD at the University of Bath focussing on the development of novel deep learning architectures for the forecasting and post-processing of meteorological data. This then led him back to industry where he worked in machine learning operations at both CGI and the Ministry of Defence.
Andy’s primary research interests are in the operational aspects of machine learning, specifically in terms of governance, deployment and maintenance of machine learning applications.
Alongside this, Andy’s focus is on the applications of deep learning and the adaptation of architectures and learning routines to specific application domains (for example, flood prevention, rainfall forecasting, OSINT and data drift detection).
Maria Battarra is a Professor in Operations Research at the School of Management. She studied Industrial Engineering and her PhD is in Operations Research from the University of Bologna. Her research focuses on solving large scale optimisation problems arising from industrial applications, like vehicle routing and scheduling, transportation and humanitarian logistics.
Maria has taught in many departments (Industrial and Computer Engineering, Mathematics and Management), in many countries (Italy, Turkey and UK) and at all levels of education (from BSc to PhD and MBA level). She has closely interacted with industry and she enjoys finding the best possible solution methods which suit the needs of the relevant application. The methodologies she most commonly deploys are exact integer and mixed integer linear programming models, and metaheuristic algorithms, but she is a great believer in continuous learning and data-driven decision making.
Maria is very keen to work with motivated PhD students who are passionate about their research and willing to share an exciting learning journey.
Operations research
Algorithms
Mathematical modelling
Metaheuristic algorithms
Transportation
Vehicle Routing
Scheduling
Humanitarian Logistics
Neill is a Royal Society Industry Fellow and works in the Department of Computer Science as a Professor in Visual Computing and Machine Learning. He is an investigator in the CAMERA research centre and the Visual Computing Group as well as a co-director of the university’s research centre in Mathematics and Algorithms for Data.
Neill is interested in the modelling of shape and the use of machine learning techniques applied in the domain of computer vision (processing images from the real world) and graphics (creating and manipulating new images). Shape is such a fundamental component of graphics and vision that research in this field unifies the two subjects and there is obviously a great advantage to solving problems in both areas simultaneously since they help one another. His latest ongoing research aims to learn automatically models of both man-made and natural shapes, and produce intelligent systems that make it easier to process, create and manipulate images.
Prior to joining Bath, Xi worked primarily as a Research Associate in the Cavendish Laboratory at the University of Cambridge, supervised by Prof. Mike Hobson. He also worked as a Research Scientist in the Shell Technology Centre Amsterdam led by Chief Scientist of Computation and Data Science Prof. Detlef Hohl, working on statistical machine learning R&D for quantitative modelling and uncertainty quantification with applications in the oil/gas industry. Currently he holds a guest researcher position in the Cavendish Laboratory.
Bayesian inference and modelling.
Machine learning/deep learning.
Statistical signal processing.
Monte Carlo numerical methods.
Sampling techniques.
Dr Iulia Cioroianu is a Lecturer (Assistant Professor) in the Department of Politics, Languages and International Studies. She joined the University of Bath as a Prize Fellow in the Institute for Policy Research. She holds a PhD in political science from New York University and an MA in political science from Central European University. Before joining the IPR, she was a research fellow in the Q-Step Centre for quantitative social sciences at the University of Exeter, and a pre-doctoral fellow in the LSE Department of Methodology.
Iulia is a social data scientist who studies the effects of social media and online information exposure on political competition and polarization using natural language processing and quantitative text analysis, machine learning and survey experiments.
Hilde has been a Professor in Politics at the University of Bath since September 2018. She previously held positions at the Free University of Brussels (VUB), Utrecht University and Victoria University of Wellington. She has also been a visiting scholar at various institutions, including the University of California Berkeley and Irvine, the University of Sydney, the Åbo Akademi University and the Leuphana University of Lüneburg. Hilde is associate editor of Gender and Politics.
Hilde’s main research interests include political behaviour, public opinion, political representation, and gender and politics. One strand of her current work investigates citizens’ support (in New Zealand and Germany) for initiatives to increase the political representation of women and ethnic minorities, e.g. through the introduction of quotas. She is also involved in an international research project looking at intraparty competition: https://www.helsinki.fi/en/researchgroups/intraparty-competition. Within the scope of this project, Hilde (together with Iulia Cioroianu) is looking at political candidates’ social networks and (with Åsa von Schoultz) at the effect of candidates’ characteristics on voters’ support for candidates. Other research projects focus on political representatives, with one study (together with Louise Davidson-Schmich) examining gender and political ambition and another study (together with Åsa von Schoultz) investigating the way that political candidates campaign and how that affects their electoral success.
Darren is a Professor in Computer Science at the University of Bath (since 2017) and a Principal Scientist at Microsoft (since 2021). Previously he was a Lecturer (Assistant Prof./US) in Computer Science at the University of Bath from 2012, and a Reader (Associate Prof./US) from 2014. He has been fortunate enough to be awarded two previous Research Fellowships: Royal Academy of Engineering, 2007-2012, and Royal Society Industry Fellowship (with Double Negative Visual Effects), 2012-2016.
He was the Director of the Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA) between 2015 and 2021, funded by EPSRC/AHRC, with partner contributions from The Imaginarium, The Foundry, British Skeleton, Ministry of Defence and British Maritime Technologies.
His research interests are in the convergence of computer graphics, animation, computer vision and psychology. He is particularly interested in applying these fields to the development of virtual humans, human realistic facial animation, motion planning and behavioural modelling.
Prof Damien Coyle is a Professor of Neurotechnology, Director of the Bath Institute for the Augmented Human, University of Bath and a UKRI Turing AI Acceleration Fellow 2021-25, and was previously director of the Intelligent Systems Research Centre, Ulster University (2017-2022). He has published over 190 research papers in AI, bio-signal processing, computational neuroscience, neuroimaging, neurotechnology and brain-computer interface (BCI) applications and has won a number of prestigious international awards including the 2008 IEEE Computational Intelligence Society (CIS) Outstanding Doctoral Dissertation Award, the 2011 International Neural Network Society (INNS) Young Investigator of the Year Award and the IET and E&T Innovation of the Year Award 2018. He was an Ulster University Distinguished Research Fellow in 2011, a Royal Academy of Engineering/The Leverhulme Trust Senior Research Fellow in 2013, a Royal Academy of Engineering Enterprise Fellow in 2016-2017 and an Ulster Senior Distinguished Research Fellow in 2021. He secured over £20m external grant income and has managed several industry-led data analytics projects. He has supervised 22 PhD researchers (11 completed). He is a founding member of the International Brain-Computer Interface Society, an IEEE Brain Steering Committee member, advisory board member for the UK Neurotechnology Innovation Network, and chairs the IEEE Computational Intelligence Society (CIS) UKIreland chapter. He is Founder and CEO of NeuroCONCISE Ltd, an award-winning, AI-enabled, wearable neurotechnology company.
Damien’s research focuses on developing AI to address challenges associated with translating electrophysiological signals into control signals for brain-computer interface (BCI) based neurotechnology and trialling neurotechnology on a large scale. He focuses on wearable neurotechnology for measuring neural signals and enabling movement-independent communication/interaction through brain-computer interfaces, targeting assistive and augmentative communication devices, cognitive and physical rehabilitation technology and human augmentation.
Nello Cristianini is a professor of Artificial Intelligence at the University of Bath. His interests range from the statistical theory of machine learning to natural language processing, including also data science, computational social science, digital humanities. Recent work has focussed on the social impact of artificial intelligence.
Carmen Domene is a Professor in Computational Chemistry in the Department of Chemistry at the University of Bath since August 2017. Previously from 2012 to 2017, she was a Reader in the Department of Chemistry at King’s College London, and from 2003 until 2011, she held a Royal Society University Research fellowship in the Physical and Theoretical Chemistry Laboratory at the University of Oxford. Her research uses computational techniques to study the structure and function of biological systems. Her aim is to understand chemical and biophysical processes from a microscopic perspective and thereby aid in interpreting and devising experiments. Matching methods to problems is necessary and requires development, implementation, and optimization of novel simulation tools. Pursuit of this has taken her into several branches of chemistry/biochemistry and biophysics including quantum chemistry, the theory of electronic structure and intermolecular interactions, statistical mechanics, ab initio and classical computer simulation and spectroscopy. She has employed and implemented techniques including but not limited to classical and ab initio molecular dynamics, free energy methods (e.g. umbrella sampling, free energy perturbation, metadynamics and its variants, adaptive biasing force etc.), Markov state and coarse-grained modelling. Her research interests span protein dynamics, protein-lipid interactions, enzymatic catalysis, drug discovery and high-performance computing.
Dr Katharine Fraser is a senior lecturer in the Department of Mechanical Engineering. Following an MPhys at the University of Oxford, and PhD at the University of Edinburgh, Katharine did postdoctoral research in the Artificial Organs Lab at University of Maryland, Baltimore, in the field of Mechanical Circulatory Support. Katharine used her computational fluid dynamics skills to analyse the blood flow through a range of rotary Ventricular Assist Devices (VADs). In 2011 Katharine was awarded a Marie Curie International Incoming Fellowship to work on arterial permeability and blood flow in the mouse aorta, at Imperial College London. Katharine now leads a research group focussed on cardiovascular engineering, focussing on mechanical circulatory support as well as the prediction and measurement of haemodynamics. Katharine is also a core member of the Centre for Therapeutic Innovation. Katharine has over 50 publications, including 27 peer-reviewed journal papers and has been invited to speak at international conferences including the Assisted Circulation Gordon Research Seminar, the International Biofluid Mechanics Symposium and the European Society for Artificial Organs. Katharine collaborates with leading research groups around the world; her research has led to consultancy work for, and ongoing projects with, several artificial heart companies, and has been used by the US Food and Drug Administration.
Katharine’s research interests are in cardiovascular bioengineering, specifically haemodynamics, cardiovascular devices and arterial diseases. Katharine uses both numerical and experimental techniques in her research, but is best known for her work on computational modelling of blood damage in artificial hearts.
Alinka is an Associate Professor in Social Work at the University of Bath, specialising in child trafficking and child protection social work.
She is a member of the Global Association of Human Trafficking scholars. Her research is cross-disciplinary analysing policy and practice responses to child protection and modern slavery, and exploring children and young people’s experiences of services.
Prior to this she gained extensive experience in social work practice with children and families, specialising in child protection, child abuse and exploitation.
She supervises a wide range doctoral students on projects that explore child migration, child protection and child welfare. She is willing to supervise topics that may include child abuse and trauma, exploitation, trafficking, migration and modern slavery.
Her research in child trafficking and modern slavery is a crosscutting social issue, relevant to policy areas of child protection, child migration, criminal justice, immigration, social policy and human rights. This research engages with how children experience contemporary childhood and adolescence in a globalised world and considers the cross-national contexts of separated children, migrating across borders. Her interests lie in qualitative child-focused research exploring children’s worlds, child protection and children’s rights.
Gosia Gocłowska is a lecturer in psychology and a member of the Social and Cultural Cognition group at Bath Psychology. She received her PhD from the University of Kent and worked as a Marie-Curie research fellow at the University of Amsterdam (Netherlands) and at the University of Rochester (USA).
Gosia’s research looks at the psychological underpinnings of open-mindedness, at epistemic emotions (e.g., interest, awe, confusion) and at the psychological processes that lead to creativity. She has also conducted research on women’s resistance of gender stereotypes.
After an undergraduate degree in Natural Sciences at Cambridge, Matt obtained his PhD at Cambridge in 2014 with Jonathan Goodman. In 2014, he took up an independent Girton College Research Fellowship at Cambridge. As a recipient of a Lindemann Trust Fellowship, Matt conducted postdoctoral research at UCLA (Houk group) during the full calendar year of 2015 before returning to Cambridge to continue his fellowship.
In July 2018, Matt joined the faculty at the University of Bath as a Lecturer (Assistant Professor). Matt was awarded a University of Bath Doctoral Recognition Award in 2021 for his dedication to doctoral supervision. In January 2022, Matt was promoted to Senior Lecturer (Associate Professor). thegraysongroup.co.uk.
Animal testing has historically dominated chemical safety assessment but more cost-effective, rapid and ethical alternatives are required.
If machine learning models are to replace animal testing, they need to be accepted by a diverse range of stakeholders (chemical industry, regulators and toxicologists). To reach acceptance, they must be transparent and provide clear insight into how and why predictions are made. Matt’s research focuses on combining computational simulations and machine learning to develop transparent models which are intelligible to all stakeholders.
Tom did his PhD at the University of York, where he worked on combining multiple images and shading information to generate 3D models of objects. He then moved to Queen Mary to apply machine learning techniques from natural language processing to CCTV footage to find unexpected behaviour. After that he worked in graphics at UCL, in particular replicating the specific handwriting of individuals. He is now a lecturer in machine learning at the University of Bath.
Tom applies machine learning to a wide selection of problems, and has substantial experience with interdisciplinary projects, particularly using ML for science. Also works on computer vision, graphics and natural language processing.
He has technical expertise that lends itself towards integrating modelling constraints into machine learning models, constructing models that adapt their complexity to the weight of evidence, and models that can actively seek out the information they need to learn. Areas of interest include Bayesian inference, ML Ops, causality, and scaling non-parametric methods to big data.
Ralph Hertwig is the Director of the Center of Adaptive Rationality (ARC) at the Max Planck Institute for Human Development in Berlin. He received his Ph.D. in Psychology from the University of Konstanz, Germany, in 1995. In the same year, he joined Gerd Gigerenzer’s research group at the Max Planck Institute for Psychological Research in Munich; in 1997, the group moved to the Max Planck Institute for Human Development in Berlin. In 2000, Hertwig received a fellowship from the German Research Foundation, which supported his research at Columbia University for three years. Hertwig obtained his Habilitation qualification from the Free University of Berlin in 2003, and in the same year became Assistant Professor for Applied Cognitive Science at the University of Basel, Switzerland. In 2005, he was appointed Full Professor of Cognitive and Decision Sciences.
Among other topics, he has examined models of boundedly rational decision strategies, smart methods to foster good decisions (“boosts”), and learning and experienced-based decision making. He has published in Science, Psychological Review, Psychological Bulletin and Psychological Science and numerous other journals.
Models of bounded and ecological rationality.
Decisions from experience.
The psychology of risk.
Lifespan development of decision making.
Evidence-based public policy (Boosting).
Dr. Janina Hoffmann joined the Department of Psychology at the University of Bath as a lecturer in Decision Science in 2019. She received her diploma in psychology from the University of Mannheim, Germany, and a PhD from the University of Basel, Switzerland. Before joining the University of Bath, she worked as an assistant professor at the Graduate School for Decision Sciences at the University of Konstanz.
Janina is a decision scientist with a strong background in cognitive science, experimental design, and cognitive modelling of behaviour. Her work aims to understand how humans evaluate, weight, and combine different pieces of information to make a judgment, decide between options or form an opinion. In doing so, she draws upon key insights from cognitive science and incorporates those insights into psychologically informed formal theories of human decision making. In future, this work will allow us to identify ways to improve human decision making.
Olga is a Lecturer (Assistant Professor) in Artificial Intelligence at the University of Bath.
Prior to this she was a postdoctoral researcher in the machine learning group at the University of Oxford.
She completed her PhD degree at the University of Sheffield. In 2017 her PhD thesis was selected for the Springer Thesis series. This series brings together a selection of the very best PhD theses from around the world and across the physical sciences. This thesis was then published as a book by Springer in 2018.
She has a specialist degree (equal to MS) in Applied Mathematics and System Programming from Lomonosov Moscow State University.
Unsupervised machine learning: anomaly detection, topic modelling, sparse modelling, representation learning.
Bayesian statistics and Bayesian nonparametrics.
Machine learning for environmental protection and conservation.
Ed is Professor of Psychology in the Department of Psychology at the University of Bath. He is also Deputy Director of The Bath Centre for Pain Research.
His main area of research is the psychology of pain. He has an interest in sex and gender differences in pain, with a particular focuses on psychosocial mechanisms (e.g., emotions, coping). He is currently interested in nonverbal communication, and whether there are sex differences expressions of pain.
A second interest is in the role that cognitions and emotions play in the experience of pain and pain-related behaviours. For example, he has interests in the links between attention and pain, with a focus on understanding how pain can have a disruptive effect on performance. He is also interested in the cognitive biases that may occur within those with a fear of pain.
Lisa has been a Lecturer (Assistant Professor) in Applied Mathematics since 2021. Prior to that, she completed her PhD in Mathematics at the University of Cambridge (2015-2019) and was a Junior Research Fellow at Magdalene College, University of Cambridge (2019-2021).
Lisa’s research is at the interface of partial differential equations, data analysis and mathematical formulations for machine learning. Lisa is interested in combining modelling, analysis, partial differential equations, applied dynamical systems and numerical analysis to nonlinear problems with applications in biology, climate modelling, engineering and industry.
Banafshé Larijani is the Director of the Centre for Therapeutic Innovation (CTI), and was the co-founder, Director and CSO of FASTBASE Solutions from 2015 to 2021.
Her laboratory, Cell Biophysics, is currently bridged between the Department of Pharmacy and Pharmacology at the University of Bath and The Biophysics Institute (Instituto Biofisika) at the University of the Basque Country, Spain. From 2002 she was Head of the Cell Biophysics Laboratory at Cancer Research UK, was appointed Senior Scientist in 2012 and in 2014 was awarded an Ikerbasque Research Professorship where she moved her laboratory to the Biophysics Institute and the Research Centre for Experimental Marine Biology and Biotechnology (PiE), Bilbao, Spain. She holds adjunct professorships with Stony Brooks University NY and University of Massachusetts, Amherst MA (USA).
Her laboratory investigates the role of phosphoinositides and their metabolites, both as second messengers and as modulators of membrane morphology. The outcomes of her fundamental research involving the application of quantitative imaging (FRET-FLIM) for investigating molecular mechanisms of phosphoinositide-modifying and phosphoinositide-dependant enzymes have resulted in their application to various clinical objectives.
Hugh has been a Professor of Education and Political Economy at the University of Bath since 1996. He is a fellow of the Academy of Social Sciences (FAcSS), and has eleven books published. His latest book is: The Death of Human Capital, Its Failed Promise and How to renew it in an Age of Disruption, New York, Oxford University Press (2020).
Since 2005 he has given keynote presentations in over 17 countries, including World Bank in Washington, International Labour Office in Geneva, and European Commission in Brussels.
He is a visiting Professor at the University of Witswaterand, UCL Institute of Education, London University, the University of Turku, and at the Centre for Skills, Performance and Productivity Research, Institute for Adult Learning/Workforce Development Agency, Singapore. He is a former editor of the Journal of Education and Work, and a former chair of the UK Forum for International Education and Training.
Hugh was the director of the Institute for Policy Research, University of Bath, from 2014 to 2016, and has a long track record of successful doctoral supervision.
Globalisation, technology and the political economy of skill formation.
Educational policy.
Political economy of education.
School effectiveness.
Education, Globalization & Social Change
Capitalism and Social Progress
High Skills: Globalization, Competitiveness, and Skill Formation
Ron Lavi is a reader (associate professor) at the economics department, University of Bath. His research focuses on subjects on the border of economics and computation, mainly algorithmic game theory, auction theory, and the efficient design of economic mechanisms. He completed his doctoral studies in computer science at the Hebrew University, Israel, and his post-doctoral studies at the California Institute of Technology. His research papers represent a successful integration of economics and computer science and are published in top economics journals as well as in the top computer science conferences and journals including AI conferences and journals like AAAI, IJCAI, NeurIPS, and JAIR. In the past he was a consultant / academic visitor at Google, Microsoft Research, and Yahoo! Labs. He has received an outstanding paper award at the 10th ACM conference on Economics and Computation, an Award for Research Cooperation and High Excellence in Science (ARCHES) from the Federal German Ministry of Education and Research, and a Marie-Curie fellowship from the European Commission.
Economics and computation, auctions and online auctions, electronic commerce, game theory and algorithmic game theory, algorithm design, the design of efficient economic mechanisms and protocols.
Furong’s research is concerned with fundamental development of new analysis tools, algorithms, economic theories to inform next generation of grid operation and planning and market economics, and quantification of whole-system value of low carbon technologies and network flexibility. Her research has three strands: i) Smart grid modelling, control, operation, planning and pricing, ii) Whole-system approach to business models and business cases for new technologies and economic incentives, iii) Big data analyses for smart grid and smart metering data to substantially improve grid and market operating efficiency.
Wenbin is a Senior Lecturer (Associate Professor) in Robotics, and a member of AI&ML, and Visual Computing groups. He was a Research Associate at Imperial SRL and leading research on autonomous drones. He also worked as a Research Associate at UCL and conducted autonomy for professional capture. He received his PhD from Bath, his MSc at Imperial College London, and his BEng at Xidian University.
Wenbin’s research interests lie in autonomous systems and their applications in manufacturing and professional capture, including the topics in multi-sensory based localization and mapping, dynamic motion capture, as well as uncontrolled scene understanding and fabrication. Those topics are broadly relevant to the fields of Robotics, Computer Vision, Graphics and Machine Learning.
Anthony started studying faces as an undergraduate at the University of Durham (1995-1998) where he examined the accuracy of personality judgements to faces from an evolutionary perspective. He continued his interest in face perception during an MSc at the University of Stirling (1998-1999) and then a PhD at the University of St Andrews supervised by David Perrett where he worked on evolutionary approaches to judgements of facial attractiveness and sexual selection (1999-2004). Anthony lectured for 2 years at the University of Liverpool in the school of biological sciences where he taught biological and evolutionary psychology before being awarded a Royal Society University Research Fellowship in 2005. He held a Royal Society University Research Fellow (2005-2013) at Liverpool and then moved to the University of Stirling to the School of Natural Science. Anthony moved to the University Bath in 2016 is currently a reader in the Department of Psychology.
Anthony is broadly interested in perception, especially faces and the information we extract from them. His work covers aesthetics and mate preferences, social cognition, cognition, and individual differences.
Dr Alexander J G Lunt is a lecturer in the Materials and Structures Centre within the Department of Mechanical Engineering at the University of Bath.
Alexander completed his MEng, PhD and first lectureship in engineering science at Christ Church, University of Oxford. Upon the completion of his PhD he took up a senior fellowship at CERN, where established their first dedicated micromechanical testing laboratory
Dr Lunt started his lectureship at Bath in 2019, and has established a diverse research network in the fields of composites, additive manufacture, advanced materials and biomechanics. He is currently affiliate lead for the University’s CMS affiliation, and has strong collaborative connections with a broad range of academic and industrial partners.
Alexander’s main research interests are on the development of microscale mechanical experimental techniques using microscopy and non-destructive techniques. This research topic offers the potential to improve substantially our understanding of material mechanics at the micro-to-nanoscale and has arisen from the significant advances in these technologies in recent decades. He has published widely in the field and has significant experience in the micromechanical characterisation of a broad range of materials and systems including ceramics, biomaterials, polymers, metals and composites. In particular he has developed methods to characterise microscale variations in residual stress, fracture toughness and yield strength. He performed a significant amount of FEA and analytical modelling in order to understand better these systems. AI has the potential to enhance material performance through advanced material design and characterisation, and this approach is currently being explored by Alexander and his students.
Christof is a Senior Lecturer in Human-Computer Interaction. He is Director of REVEAL, the REal and Virtual Environments Augmentation Labs, which is the VR/AR research centre at the University of Bath.
Christof’s main research interests are in the fields of Human-Computer Interaction, with a focus on VR/AR and sensors such as for eye gaze tracking. He is interested in applications of VR/AR technology in training, learning and mental and physical health. He is also interested in assistive technology such as systems that allow users to control computers with eye gaze.
Greg examines diverse topics in social psychology, including international projects on the following issues:
These and other projects have led to diverse articles and chapters and two books, The Psychology of Values, and The Psychology of Attitudes and Attitude Change (with Geoff Haddock and Bas Verplanken), now in its 3rd edition.
Uriel Martinez Hernandez is a Lecturer in the Department of Electronic & Electrical Engineering, and in addition to ART-AI is also affiliated to the Centre for Biosensors, Bioelectronics and Biodevices (C3Bio), the Centre for Autonomous Robotics (CENTAUR), and the Electronics Materials, Circuits & Systems Research Unit (EMaCS).
He completed his PhD at the University of Sheffield, where he remains a Visiting Researcher. His early training was at the Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV) in Mexico.
Robotics, autonomous systems and machine learning, with particular interest in:
Tactile and vision perception for autonomous robotics
Learning and sensorimotor control in autonomous robotics
Multimodal human-robot interaction and collaboration
Intent recognition for wearable assistive robotics
Wearable robots for telepresence and telecontrol
Polly is a Biomechanist interested in muscles and tendons in human and animal locomotion, injury prevention and performance enhancement.
Polly’s research focuses on how the neuromuscular system powers and controls locomotion in humans and animals, how it changes with age and injury, and ways in which its performance can be enhanced through training and technology. This research is multidisciplinary in nature and has applications in many spheres of medicine, physiotherapy, veterinary, sports science and engineering. Specific current projects include:
Understanding muscle-tendon interaction and motor control in demanding dynamic tasks to prevent injury.
Changes in muscle architecture, mechanics and recruitment with age.
Technologies to assist in the rehbilitation of musculoskeletal injuries.
Preventing long term complications of lower limb amputation.
Ben is Head of the Department of Electronic & Electrical Engineering, Deputy Director of the Institute for the Augmented Human, Deputy Director of the Centre for Biosensors, Bioelectronics and Biodevices and Vice-President (Academic) of the Institute of Physics and Engineering in Medicine.
Ben is a biomedical engineer with expertise in wearable and implantable neural interfaces for both rehabilitation and enhancement. His work is funded by the EPSRC and the NIHR and covers the spectrum from speculative research to clinical trials and product development. His core skills are in signal processing and both animal and human electrophysiology.
Advanced neural interfaces.
Biologically inspired autonomous systems.
Biomedical signal processing for both in-vivo and ex-vivo applications.
Neuronal modeling and computing.
Subhadip is an Assistant Professor (Lecturer) at the Department of Computer Science, University of Bath, and a visiting researcher at the Dept. of Applied Mathematics and Theoretical Physics (DAMTP), University of Cambridge.
Subhadip works in the area of deep learning and inverse problems in imaging. His research objective is to develop novel, computationally efficient, and provably convergent algorithms for challenging image analysis problems by combining model- and data-driven approaches.
Prior to joining Bath, he was a postdoc with Prof. Carola-Bibiane Schönlieb at the Cambridge Image Analysis (CIA) group, DAMTP, University of Cambridge. He was a member of the AI and image analysis team for the all-in-one cancer imaging project conducted by a group of mathematicians, computer scientists, and radiologists at the University of Cambridge.
Before joining Cambridge, he worked with Prof. Ozan Öktem as a postdoc in the imaging group at the Dept. of Mathematics, KTH, Sweden. He completed his PhD in September 2018, at the Indian Institute of Science (IISc.), Bangalore, under the supervision of Prof. Chandra Sekhar Seelamantula.
Visit his Google Scholar profile to see a complete list of published articles. A detailed CV can be found here.
Machine learning
Optimization
Computational imaging
Vinay is currently a lecturer in the Department of Computer Science at the University of Bath. Previously he worked in the engineering department of the Indian Institute of Technology, Kanpur, as well as Bell Labs Antwerp. He was also a Postdoctoral Fellow in KU Leuven with Prof. Luc Van Gool and obtained a PhD while being guided by Prof. Subhasis Chaudhuri.
Visual Recognition with Scarce Supervision.
Multi-modal Deep Learning.
Explainable AI.
Adversarial and Probabilistic Deep Learning.
Professor Newnes gained her PhD from Loughborough University where she worked as a full-time researcher in their Department of Manufacturing Engineering whilst studying part-time. She joined the University of Bath in 1991.
Most of her research is industry focussed and her impacts have created benefits and value to – among others – the aerospace and defence sectors, medical device design, the oil and gas industries, green technologies, and utilities.
Linda’s research focus is on whole life value analysis – economic, environmental, and societal costs – from concept design through to the in-service/in-use/re-use phases. Core to determining value is her work in engineering design and manufacturing, with a particular focus on ‘people’ and ‘skills’.
She leads a £1.8M Engineering and Physical Sciences Research Council grant on TRansdisciplinary ENgineering Design (TREND), which aims to remove the barriers between different disciplines and job functions and in doing so fundamentally change how 21st century products are designed. She also leads the £5 million Centre for People-Led Digitalisation which is focused on increasing uptake, and maximising the benefits, of digital technologies by understanding how people interact with them. The Centre is funded by the Made Smarter Innovation programme delivered by UK Research and Innovation.
Nick is Professor of Public Policy and Director of the Institute for Policy Research (IPR) at the University of Bath. He has extensive experience in policy research and government policymaking and writes on a wide range of issues, from contemporary British politics, public service and welfare state reform, to Britain’s place in the world. His recent publications include Britain Beyond Brexit and Shadows of Empire: The Anglosphere in British Politics. He is currently Subject Editor of Science, Society and Policy, Royal Society Open Science, published by The Royal Society.
Before joining the University, Nick was the Director of Institute for Public Policy Research (IPPR), and between 2008 and 2010, Head of the No10 Downing St. Policy Unit, with responsibility for the formulation of policy advice to the Prime Minister. He led and managed the work of the Prime Minister’s 13 policy advisers.
Nick has also worked as special adviser in the Home Office, Cabinet Office and former Department for Education and Employment. He was formerly chair of the advisory board to the UK Chief Scientist’s Foresight Programme and served on the Equalities Review and the Teaching and Learning 2020 Review. In 2019/20, he was Chair of the Democracy and Civic Participation Commission for the London Borough of Newham.
Nick is currently Chair of Trustees at both Tavistock Relationships and the Early Intervention Foundation. He serves on the advisory boards of the Wales Centre for Public Policy and the Higher Education Policy Institute. He is a Fellow of the Academy of Social Sciences and an Honorary Fellow of the Royal Institution of British Architects.
Nick’s current research interests include:
The political economy of welfare state reform.
The idea of ‘Anglosphere’ in British history and politics.
British politics, including political parties, age divides in voting, and the politics of Britain’s relationship with the EU.
Dr Elise Pegg is a Senior Lecturer in the Department of Mechanical Engineering, and her research work is at the interface of biomechanics and biomaterials. After completing her doctorate at the University of Nottingham, Elise worked as a research engineer for an orthopaedic manufacturer for three years. She decided to return to academia in 2011 and moved to the University of Oxford to become a post-doctoral researcher in the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences. Now at the University of Bath, Elise lectures on solid mechanics and materials topics, as well as being the Director of Studies for the MSc in Engineering Design.
Dr Pegg’s research applies engineering tools to address clinical questions and improve clinical treatment in the field of orthopaedics. Her work focuses mainly on joint replacement devices (hip, knee and ankle), but also healthy joint function. Elise is a materials engineer by background and much of her research has involved creating and testing new materials for use in medical applications, but also in the design of implants. Elise uses a combination of mechanical testing and numerical simulation (FEA) to assess the safety and clinical effectiveness of implant designs and/or materials. Elise has supervised three PhD students through to graduation of their studies and currently supervises a further 2 postgraduate students. Her experience in industry, clinic and academia gives her a unique perspective on the translation of research into the medical device industry.
Karin Petrini a Senior Lecturer/Associate Professor in Experimental and Cognitive Psychology at the University of Bath and an Honorary Senior Researcher at University College London. Her main interest is in understanding how we combine multisensory cues (e.g., vision, audition and touch) throughout the lifespan (e.g., from childhood to adulthood) and how this process is affected by experience, expertise, sensory deprivation, and developmental disorders. Her interest in multisensory research expands to social cognition and emotion, and she uses a combination of methods and techniques (e.g., psychophysics, neuroimaging, neurophysiology, virtual reality) to study the underlying brain mechanisms. Another main focus of her research concerns how music practice and experience can shape our behaviour and brain functions/structure and how music can be used as a viable and effective intervention. Finally, other areas of interest include spatial cognition and navigation and assistive technologies.
Multisensory integration
Expertise and long-term practice effects
Cognitive and perceptual development
Emotion and social cognition/perception
Auditory perception
Visual perception and cognition
Spatial cognition
Developmental disorders and sensory restoration
Biological motion
Music
Virtual reality
Assistive Technologies
Dr Michael J. Proulx is a Research Scientist at Meta Reality Labs Research, and Reader in Psychology and Director of the Crossmodal Cognition Lab at the University of Bath. He is also co-founder of the Real and Virtual Environments Augmentation Labs (REVEAL Research Centre).
He received his BS in Psychology from Arizona State University and his MA and PhD in Psychological and Brain Sciences from Johns Hopkins University. Michael was a postdoctoral research fellow in Duesseldorf, Germany, and a Lecturer in the School of Biological and Chemical Sciences, and Visiting Lecturer in Electronic Engineering and Computer Sciences, at Queen Mary University of London before moving to Bath. He is now in the Seattle area at Reality Labs Research, home of Oculus and now a part of Meta.
He is an elected Fellow of the Society for Experimental Psychology and Cognitive Science of the American Psychological Association, Associate Fellow of the Royal Institute for Navigation, and the recipient of a New Investigator Award in Experimental Psychology: Human Perception and Performance from the APA. He was also honoured as a torchbearer for the London 2012 Paralympic Games for his research and applied work on visual impairments.
His main research interests are in the cognitive science of interactive technology and human behaviour, with particular interests in eye tracking applications and multisensory cognition. This includes using methods from psychology and neuroscience to study augmented and virtual reality, evaluate assistive technology for sensory impairments, and to model sensory processing. He is also passionate about privacy implications for sensor data in VR/AR and responsible AI.
Paulo Rocha is an Associate Professor in Bioelectronics, ERC Starting Grant Laureate and a Group Leader of the Bioelectronics & Bioenergy Research Lab at CFE – Centre for Functional Ecology, Department of Life Sciences of the University of Coimbra. He is currently an Editorial Board Member for Scientific Reports from the publisher Nature and iScience from Cell Press.
In 2014, he obtained his PhD in Electrical Engineering with the highest honours (Cum Laude) with a science scholarship from the Dutch Polymer Institute (DPI) in The Netherlands, and in close collaboration with Philips research. As a PhD researcher, he started developing the science of biocompatible materials, circuits and their interaction with living organisms. In 2014, he started his post-doctoral research in the field of Bioelectronics at the Max Planck Institute for Polymer (MPIP) research in Mainz, Germany. In 2016, Paulo joined the Department of Electronic and Electrical Engineering, University of Bath, as an Assistant Professor, was appointed as the Departmental Research Staff Coordinator and started his independent research group, (with an exceptional team of students and collaborators) and a state-of-the-art low noise characterisation laboratory, specifically designed for bioelectric and bioenergy applications.
Paulo’s passion for unconventional approaches and blue sky research ideas have been funded and supported by highly competitive and world leading research industries as well as national and international funding agencies, amassing over 3 million euros.
Dr. Sandipan Roy is a lecturer (equivalent to Assistant Professor in the US) in Statistics at the University of Bath. He did his BSc and MStat in Statistics at Presidency College and the Indian Statistical Institute in India respectively. He received his PhD from University of Michigan in 2015. He was a post-doctoral research associate at UCL before joining the University of Bath in 2018.
Sandipan’s core research is at the intersection of statistics, machine learning and optimisation methods. His current research is focussed on modelling data with complex high dimensional network structure and provides methodology for estimating the corresponding structure using tools from nonparametric statistics, graphical models and high dimensional inference. The emphasis is placed on application of theoretical techniques and computational tools to many real-world problems, including biomedical and social science research, where network modelling and analysis plays an exceedingly important role.
As a mathematical statistician, Sandipan is also interested in high dimensional inference in regression models and understanding the theoretical insights in the modern “big data” framework. The development of novel algorithms along with concrete theoretical results would enable practitioners to use them in many complex real-world problems. Recent interests include different optimization methods and especially understanding distributed/parallel computing with large heterogeneous data. These also include fast choice of tuning parameters in optimization algorithms and their implications in the proposed inference.
Sandipan’s research group currently has 5 PhD students working on a range of topics covering graphical models, dimension reduction, network models, spatio-temporal analysis and differential privacy. Sandipan is currently serving as the chair of the Royal Statistical Society (RSS) Avon local group and a member of the computational statistics and machine learning section of RSS.
Statistics, Doctor of Science, University of Michigan: 2015
Statistics, Master in Science, Indian Statistical Institute, Kolkata: 2010
Statistics, Bachelor of Science, University of Calcutta: 2008
Elena is a biomedical engineer with a PhD in Human Physiology. She joined the University of Bath in 2014 as a research associate within the Sport, Health and Exercise Science Research Group. In 2016 she joined the ‘Centre for the Analysis of Motion, Entertainment Research and Applications’ (CAMERA), as a research associate working on the rehabilitation research area of the centre. Her main focus has been always on biomechanics with different applications in the field of rehabilitation and assistive technologies, but also sport and injury prevention. In September 2018 she was appointed as a lecturer in Clinical Biomechanics within the Department for Health.
Elena is interested in the biomechanics of human motion, especially for clinical, sport and injury prevention applications. Her previous research has been focused on the relation between energetics and mechanics of different forms of locomotion and sports. She has been working on shoulder injury prevention in volleyball players, biomechanics of cycling and pathological locomotion in osteoarthritis affected patients and cervical spine injury prevention in rugby activities. Her current research is focused on lower limb amputee prosthesis assessment and design and pathological locomotion. Her research approach includes both experimental sessions and musculoskeletal modelling of human motion, in order to establish risk factors, prevent injuries/illness and improve performance.
Pranav Singh is a Lecturer (Assistant Professor) in Numerical Analysis and Scientific Computing at the Department of Mathematical Sciences. Previously he was a Junior Research Fellow (JRF) in Mathematics at Trinity College and Mathematical Institute, University of Oxford. He holds a PhD and an MASt in Applied Mathematics from the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge, and a BTech and an MTech in Computer Science and Engineering from IIT Delhi (India). He spent two years as a research assistant in Computer Vision at ETH Zürich and has spent four years working in industry at Adobe, Philips Research, Medtronic SNT and DIMTS.
Pranav’s research interests lie broadly at the intersection of computational methods and quantum mechanics. His current research involves the development of computational techniques for simulation, optimal control and design of quantum technologies such as quantum computers, NMR/MRI, quantum biology, optical fibres, solar cells, atomic and molecular systems. A particular theme of interest is the intersection of traditional numerical algorithms with optimisation and machine learning techniques, leading to hybrid algorithms and architectures that are not only fast but come with theoretical guarantees.
Dr Alexandra de Sousa has a BA in Anthropology from Arizona State University, USA, and a PhD in Hominid Paleobiology (Evolutionary Neuroscience) from The George Washington University, USA, for which she conducted research at the C&O Vogt Institut für Hirnforschung, Germany. She has a far-reaching and interdisciplinary approach to understanding the evolutionary basis of brain function. Her research has been funded by the NSF (USA), the FCT (Portugal), the VWStiftung (Germany), as well as Atkins Global (industrial partner). She has built a strong track record in evolutionary neuroscience, in particular by investigating the brain organisation of understudied primate species. She develops procedures for quantifying complex aspects of brain structure and function including cytoarchitecture and cortical organisation. She champions the use of a phylogenetic approach in order to i) translate from animal-models and ii) test relationships between structure and function. She has also proposed a framework linking brain size organisation to cognitive function with fundamental implications for understanding species-specific variation in brain organisation.
Dr de Sousa founded the European Network for Brain Evolution Research to unite researchers across disciplines, and Brain Evolution in the News to improve the visibility of her field. She directs the Comparative Crossmodal Cognition Collective, through which she is developing new research directions for evolutionary neuroscience by linking it to applications in the built environment and technology development.
Alexandra’s research examines the relationship between human behaviour and brain structure. As an evolutionary neuroscientist, she approaches behaviour from “deep” anatomical and evolutionary frames of reference. Alexandra researches the emergence of human cognition from fossil, archaeological, and genetic records. Most recently she has focused on the neuroanatomical and comparative basis of cognition and its implications for well-being and inclusivity in the built and unbuilt environment.
She is keen to supervise self-motivated PhD students and postdoctoral researchers with similar research interests
George joined the Department as a Lecturer in 2017. Prior to that he completed his PhD and post-doctoral research at the University of Bristol, using electroencephalography (EEG) to examine sensory and attentional processing in dementia patients and healthy older adults. His undergraduate degree was in Psychology at Swansea University.
George teaches on the MSc Applied Clinical Psychology course, runs the EEG laboratories and leads the Neurostim research group. He is also an Early Career Co-ordinator for Alzheimer’s Research UK.
George’s motivation as a researcher has always been to translate the findings of cognitive neuroscience into useful tools for clinicians and the wider world. His primary research focus is the development of a new EEG technique, known as Fast Periodic Visual Stimulation, for assessing cognitive deficits in dementia. In partnership with his collaborators George has developed a free toolbox https://gstothart.github.io/Fastball/ allowing anyone to download and conduct their own Fast Periodic Visual Stimulation experiments.
In 2015 George was nominated for the Erik Kandel Young Neuroscientist Prize by Prof. Risto Näätänen of the University of Helsinki.
Dementia.
Electroencephalography.
Ageing.
Neurological disorders.
Dr Tayyar Madabushi’s long term research goals are focused on investigating methods of incorporating high-level cognitive capabilities into models. In the short and medium term, his research is focused on the infusion of world knowledge, common sense and reasoning into pre-trained language models to improve performance on complex tasks such as multi-hop question answering, conversational agents, and social media analysis.
Dr Tayyar Madabushi completed his PhD in AI, focusing on automated question answering at the University of Birmingham in 2019 and began his current post as Lecturer in Artificial Intelligence at the University of Bath in 2022. His research has been influential in the area of combining construction grammar and pre-trained language models, as he conducted the first exploration in this field, paving the way for further developments. He has also worked on evaluating language models’ ability to capture non-compositional multiword expressions (MWEs), which have traditionally posed a challenge for computational models. Furthermore, he organized the SemEval 2022 Task on MWEs as the principal organizer.
Publication record on Google Scholar.
Mike Tipping is Professor of Machine Learning in the Department of Computer Science at the University of Bath. Before joining the University, Mike spent several years in industry: eight years at Microsoft Research, six years running an independent statistical consultancy and two years as Director of Science at Featurespace. He has also worked with a number of start-ups, including Babylon Healthcare, Ninety Percent of Everything, Homelink Technologies and Propflo.
Combining interests in both theory and application of AI, Mike is known for the introduction of the “probabilistic PCA” data science framework, the invention of the “relevance vector machine” predictive model, the origination of the “Drivatar AI” concept behind Microsoft’s “Forza Motorsport” Xbox franchise, and the development of an award-winning machine learning-based payment fraud prevention system.
Mike’s early research centred on neural and probabilistic methods for data visualisation, and later broadened to include more general machine learning methodology and Bayesian statistical inference. In particular, he focused on how Bayesian methods could be exploited to derive parametrically sparse, meaningfully parsimonious, models of data. Currently his interests include the application of sparse Bayesian models to inverse problems, probabilistic approaches to solution and algorithm discovery, explainable tree-structured classification methods, and techniques for the intelligent automation of large-scale data analysis.
Dr Araxi Urrutia is a senior lecturer at the Milner Centre for Evolution, Department of Life Sciences at the University of Bath.
Araxi’s research is focused on uncovering the genomic basis of complex phenotypes such as brain function, behaviour and longevity and lifespan.
Araxi’s work has been published in top journals including Nature and PNAS and has a record of PhD supervision with 11 graduated PhD students.
Araxi joined the University of Bath in 2007 as an academic with a Royal Society Dorothy Hodgkin Research Fellowship and a L’Oreal Women in Science Research Fellowship. Before this she was a postdoctoral assistant at Arizona State University after finishing her PhD at the University of Bath.
Dr Dingguo Zhang is a Reader in Robotics Engineering in the Department of Electronic & Electrical Engineering at the University of Bath. He is the Director of the Centre for Autonomous Robotics (CENTAUR). His research interests include rehabilitation robotics, human-machine interfaces, and brain-computer interfaces. He serves as an Associate Editor for IEEE Trans. Medical Robotics and Bionics, IEEE Trans. Human-Machine Systems, IEEE Access, Scientific Reports, Frontiers in Neuroscience, and Frontiers in Neurorobotics. He is a senior member of IEEE (EMBS, RAS, SMC), and serves in three technical committees (BioRob, TST, BMI) of EMBS and SMC societies, respectively. He was a Board Member of International Society of Functional Electrical Stimulation (IFESS) and a Youth Commission Member of International Society of Bionic Engineering (ISBE). He was the winner of the Delsys Prize 2011 for achievements on EMG, and a finalist of BCI Award in 2015, 2020 and 2021. He attracted large grants from the National Natural Science Foundation of China (NSFC) and the Ministry of Science and Technology (MOST) when he worked in Shanghai. He has authored over 200 papers, and some were published in high-profile biomedical or robotic journals including TNSRE, TBME, TMECH, TMRB, JBHI, JNE, SORO, NeuroImage. He has filed 30 patents/software copyrights.
His research interests include brain-computer interfaces, rehabilitation robotics, robotic exoskeletons, and neural technologies.
Dr. Zhang’s research situates at the interface between computer science and economics. He is interested in understanding and characterizing the incentives of self-interested agents in competitive and cooperative environments. He analyses agents’ decision-making processes and aligns their incentives with the objectives of a system designer by analytical methods. Ultimately, he evaluates and improves system performance in their equilibrium stages, under worst-case guarantees and beyond worst-case scenarios. As sole investigator, he has been awarded research grants by the Leverhulme Trust and EPSRC.
Game theory
Mechanism design
Digital economy
Blockchain technology
Since graduating from Loughborough University, Christina has worked in the Events Industry for most of her career to date. More recently she worked as a Demonstrator in Events Management at Bournemouth University where she obtained a PG Cert in Education Practice and Fellowship to the HEA. She has now moved to the University of Bath and joined the ART-AI team as Events Co-ordinator and Public Engagement Officer.
Mark joined the ART-AI team at the University of Bath as a Research Software Engineer (RSE) in 2023. After graduating with an Electronic & Software Engineering degree from Leicester, he was immediately drawn to the world of software development. Mark brings a wealth of experience to his role having worked in industry for over 25 years in a diverse range of sectors. In his free time, Mark loves to contribute to Tech4Good projects, running targeted sessions for young people with an interest in a software careers, playing chess and cycling.
