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LIDA Development Programme Advisory Group (LIPAG) Members

LIPAG is made up of a diverse membership of academic, technical and professional staff from across the University of Leeds and it reports directly to LIPAG Chair, Prof Michelle Morris. Its remit is to support the delivery of the Programme’s operations, as well as formulating the Programme’s research strategy. It provides the opportunity, not only for senior, but also for junior academic, technical and professional staff at the University of Leeds to support the training and development of early career Data Scientists through robust academic assurance of this Development Programme.

Prof Michelle Morris, LIPAG Chair

Dr Michelle Morris is a Professor of Data Science for Food, in the School of Food Science and Nutrition at the University of Leeds. Michelle is based in the Leeds Institute for Data Analytics where she leads the Nutrition and Lifestyle Analytics team. Her research investigates how novel consumer data can be utilised to better understand population diet and activity behaviours. Michelle is an interdisciplinary researcher in data science with a background spanning; nutritional epidemiology, health informatics and health geography.

Prof Nick Malleson, LIPAG Deputy-Chair

I am a Professor of Spatial Science at the Centre for Spatial Analysis and Policy at the School of Geography. Most of my research focuses on the development of computer models that help us to understand social phenomena. I have a particular interest in simulations of crime patterns and in models that can be used to describe the flows of people around cities. More recently, I have become in interested in how we can use ‘big data’, agent-based modelling, and smart cities initiatives to reduce the impacts of phenomena like pollution or crime.

Dr Sajid Siraj, Equity, Diversity & Inclusion Chair

Dr Siraj is an active researcher in the field of decision support systems. He started his career as electrical engineer working on microchip designing and developing device drivers. He also worked in the telecom sector for many years working on machine learning tools to identify potential frauds. He did his PhD in Computer Science from University of Manchester, focusing on the use of Multi-objective Optimisation in Multi-criteria Decision Making. Dr Siraj developed a decision support software tool, called PriEsT, which has been downloaded more than fifty thousand times around the globe and has been used in numerous businesses applications. Dr Siraj has published in quality journals in the fields of Operational Research and Decision Support Systems. His main research interests are in the field of explainability and fairness in decision support systems, primarily focusing on the machine learning algorithms.

Dr Boshuo Guo

Boshuo is Lecturer of Digital Fashion Marketing in the School of Design at the University of Leeds. Boshuo’s research focuses on applying advanced data analytical techniques to analyse online data, aiming to understand how consumers’ experience is influenced by choice overload as well as scarcity. Boshuo’s recent project, funded by Consumer Data Research Centre, investigates how cost-of-living crisis (financial scarcity) and supply-chain disruptions (product scarcity) influence consumer experience and wellbeing, through analysing extensive datasets of online word-of-mouth.
Boshuo completed her PhD in Management Research (major in Marketing) at Imperial College Business School, Imperial College London.

Dr Dan Birks

Dr Dan Birks is Associate Professor of Quantitative Policing and Crime Data Analytics in the School of Law, and a Turing Fellow at the Alan Turing Institute. He joined Leeds in 2018, having previously held research and teaching roles at Griffith University (Brisbane) and University College London. His research focuses on how data science methods and tools can be responsibly used to derive actionable insights from administrative criminal justice data to support understanding, prevention and responses to crime problems. He has over 15 years’ experience working with criminal justice practitioners and policy makers in UK and Australia. To date, his research has been supported by over £1.4m of research income, and he currently leads an EPSRC funded project exploring how computer simulations can help police better understand supply and demand dynamics.

Associate Professor Aulona Ulqinaku

Aulona is Associate Professor of Marketing and Programme Director for MSc Consumer Analytics and Marketing Strategy in the Marketing Department at Leeds University Business School, University of Leeds. Her research interests cover the effect of psychological and financial threats on individuals and their consumption preferences and choices and how marketing activities can help threatened consumers. Aulona did her PhD in Business Administration and Management (major in Marketing and minor in Organization) in Bocconi University in Milan. She also holds a MSc in Marketing Management and a Bachelors Degree in Business Administration and Management from Bocconi University.

Dr. Mingwen Bai

I am a Lecturer at the School of Mechanical Engineering and a UK Chartered Engineer (CEng) with over a decade of experience in surface engineering aimed at protecting metals from environmental degradation such as oxidation, corrosion, and wear. My work has broad applications in power generation, including aerospace gas turbines, biomass-fired power plants, and nuclear reactors. I earned my BEng in Materials Science and Engineering from Shanghai Jiao Tong University in 2011 and completed my PhD in Materials at the University of Manchester in 2015. Before assuming my current role, I served as an Assistant Professor at Coventry University from 2020 to 2023. I have also held postdoctoral positions at the University of Sheffield (2018-2020) and the University of Nottingham (2016-2018), contributing to two large EPSRC-funded projects (EP/R001766/1 and EP/M01536X/1).

Dr Rebecca Birch

Rebecca is a Research Fellow specialising in healthcare inequalities with projects including the relationship between diabetes and cancer outcomes, the treatment of older patients and the use of routine data to assess comorbidity. Principally using large scale, linked population level, healthcare datasets to examine the characteristics, treatments and outcomes for cancer and quantify variation.

Dr Charlotte Sturley

Charlotte is a Research Fellow in Health Data Analytics in the Survivorship and Multimorbidity research group, based in the Leeds Institute for Data Analytics. Her research investigates geographic variation in health using national electronic health care records, clinical registry data, census and survey data. She is currently looking at geographic variation in incidence of disease in patients following a myocardial infarction (heart attack).

Charlotte completed her PhD at the University of Leeds in 2022, which examined social and spatial variations in bowel cancer incidence and survival. Charlotte also has an MSc in Geographical Information Systems from the University of Leeds.

Prior to starting her PhD, Charlotte was among the first cohort of Data Scientists on the LIDA Data Science Development Programme, during which she undertook projects using smartphone data to better understand commuting patterns and analysing supermarket transaction data to quantify the impact of discount retailers.

Dr Dave Riley

Dave is Research Manager for Partnership, Creativity, and Impact at the Leeds University’s Horizons Institute. Before joining Horizons in January 2024, Dave worked for over three years at Leeds Institute for Teaching Excellence (LITE), where he helped to develop early-stage research in the field of Teaching and Learning.
Dave’s focus throughout his career has been on building communities, partnerships, and networks within Higher Education between and among students, academic staff, professional staff, and external stakeholders. In 2020, Dave won the overall partnership award for the Faculty of Environment, and the university-wide Partnership Award for Innovation as a result of his work on Mentoring Schemes within the faculty.
Prior to joining the University of Leeds in 2018, Dave was awarded a PhD in Diplomatic History at Cardiff University and has worked in many roles in HE including within student employability, student experience, residences, and graduate schools.

Francesca Pontin

Fran is a Senior Research Data Scientist at the Consumer Data Research Centre and a Lecturer in the School of Geography at the University of Leeds. As a member of the Institute for Spatial Data Science, her research focuses on applying advanced data science techniques to explore the spatial, temporal, and demographic determinants of health, with the goal of reducing inequalities. She is particularly interested in leveraging both open and commercial secondary data to understand behaviours and identify barriers faced by diverse population groups.
Her work is strongly policy-oriented, collaborating with stakeholders to transform research informed insights into actionable strategies. Recent projects include the development of data-driven tools to assess food insecurity risk across the UK and initiatives aimed at enhancing the safety of women and girls in public parks. Fran’s research not only advances academic knowledge but also directly informs policies that aim to improve public health and social equity.

Professor Jonathan Benn

Jonathan Benn is Associate Professor in Healthcare Quality and Safety at the School of Psychology, University of Leeds, and theme lead for Safety Intelligence within the NIHR Yorkshire and Humber Patient Safety Research Collaboration. Jonathan has worked in health services research since 2005, applying quantitative and qualitative research methods and theory from behavioural science, including implementation science and safety science, to address a range of challenges in health care organisation, design and delivery. He completed his undergraduate study in Psychology, followed by a PhD in Human Factors in Systems Engineering. Prior to taking up his post at Leeds in 2018, he was Lecturer in Quality Improvement in Healthcare in the Department of Surgery and Cancer at Imperial College London. Jonathan is particularly interested in applications of organisational psychology, data science and human factors in a health service context. Specific interests include:
• Sociotechnical evaluation of safety intelligence solutions, including monitoring and feedback interventions.
• Learning from whole-system integrated data, with specific focus on patient safety inequalities
• Capture, sensemaking and use of soft intelligence in a health service context
• Workforce wellbeing and teamworking climate in healthcare
• Human factors and the design of clinical work systems

Dr Jonathan Ward

Jonathan Ward is a lecturer in applied mathematics at the University of Leeds. He has a Physics and Astrophysics MSci and a PhD in engineering mathematics, both from the University of Bristol. Jonathan moved to Leeds as a lecturer in 2013 after post-doctoral positions at the Mathematics Applications Consortium for Science and Industry at the University of Limerick in Ireland, and at the University of Reading. Jonathan’s research interests relate to mathematical modelling of human behaviour, in particular methods to approximate dynamical phenomena and calibrate agent-based models using data. He has worked on a range of applications, including vehicular and pedestrian traffic models, and dynamical processes on networks, such as epidemics models and opinion dynamics. Jonathan also actively engages in work with industry, for example through short-term study groups and industry supported PhD supervision.

Associate Professor Marlous Hall

I am an Associate Professor of Epidemiology and lead the Survivorship and Multimorbidity Epidemiology Research Group in the School of Medicine. My research focusses on developing a deeper understanding of the long term survival trajectories for individuals with chronic disease, in particular the role of concomitant disease and multimorbidity for individuals with cardiovascular disease. I have a strong methodological foundation in advanced statistical techniques and health data analytics, and use a range of national electronic health care record data to underpin my research. The research group is based within the Leeds Institute for Data Analytics (LIDA), and is part of the Clinical and Population Sciences Department in the Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM).

Dr Patricia Dallagnollo

Patricia is a Research Software Engineer, focusing on Computational Mechanics, working within the Research IT team at the University of Leeds. She has a PhD in Theoretical Physics and a master’s degree in Condensed Matter Physics. She has experience on the development of computational models that help to understand complex systems; initially focusing on phenomena such as the behaviour of fluids at nanoscales and lately modelling emergence in spatio‐social systems. Previously, she worked as a Researcher in Simulating Urban Systems at the School of Geography (2019-2021), and before joining the University of Leeds, Patricia also worked as a physics undergraduate professor at Federal Institute Catarinense-Brazil (2018-2019).

Dr Rachel Oldroyd

Rachel is a Lecturer in Spatial Data Science based at the Centre for Spatial Analysis and Policy within the School of Geography. Her research is centred around food access, safety, and inequalities, with particular interest in employing machine learning and spatial data analytics to further understand out-of-home food environments. Rachel is passionate about addressing underrepresentation within Higher Education and is involved in several widening participation initiatives, she is committed to equality, diversity and inclusivity and is the Academic Lead for Inclusive Pedagogies within the School of Geography.

Professor Serge Sharoff

I'm Professor of Language Technology at the School of Languages, Cultures and Societies. Artificial Intelligence and more specifically Large Language Models, such as ChatGPT, have recently made a profound impact on how we interact with computers. Fundamental research in this area is at the core of my expertise, I've been doing this since my own PhD in the 1990s on the topic of developing a language model for Information Extraction. Language models were small at the time, but that was the same idea of linking language to meanings. Since then, I've been doing research on better understanding of representative corpora automatically collected from the Web, as well as on using them to improve language technology for translators and everyday users. On a more general level I am interested in interpretability of language models with the aim of determining whether a model makes the right decisions for the right reasons.

Dr Susan Lee

Dr Susan Lee is a Research Fellow based in the Consumer Data Research Centre and employed by Leeds University Business School. She is an experienced multi-disciplinary researcher with a background in environmental science. Her research interests encompass dietary change, sustainable food systems, urban resource flows and the natural environment. Her current research investigates behavioural changes in meat consumption, the sustainability of healthy foods in terms of carbon emissions, water use, costs and biodiversity and the development of eco-labelling.

Dr Vikki Houlden

Dr Vikki Houlden is a Lecturer in Urban Data Science in the School of Geography, a member of the Centre for Spatial Analysis and Policy (CSAP), and a Turing Fellow at the Alan Turing Institute. Through her research, she aims to understand the ways in which spaces and places embody inequalities, and the social structures influencing how people relate to their environment. She is particularly interested in how urban landscapes impact health and wellbeing. She approaches urban challenges, such as accessibility, mental health, and social peripheralisation, through geospatial methods and theory which draws on her interdisciplinary background in urban science, data analytics, engineering, and geography. As well as quantitative spatio-temporal analysis, she works with community groups, practitioners, and local government, to understand and improve individual experiences of the built environment.

Marc de Kamps

Marc de Kamps is a Lecturer in the School of Computing whose interest is computational neuroscience and machine learning. He has a great interest in the workings of the brain and has been a PI in the EU funded Human Brain Project (2015-2020). He has run the activities of EU funded Thematic Network nEUro-IT.net. Starting from neural network models of attention processes in visual cortex, he now is supervising PhD students in AI for Medical Diagnosis and Care, collaborating on the analysis of Electronic Healthcare Records, and modelling neural process in spinal cord.