Leslie Ann Goldberg is a Senior Research Fellow at St Edmund Hall and Professor of Computer Science at the University of Oxford. She currently serves as Head of the Department of Computer Science (on sabbatical 2025-26) and focuses on foundational problems in Algorithms and Complexity Theory , particularly randomised algorithms for network communication, machine learning, and statistical physics models. Her research includes solving Aldous' 1987 conjecture on backoff protocol instability (with John Lapinskas), developing rigorous mathematical analysis frameworks for algorithmic efficiency, and advancing approximate counting techniques via Markov Chain Monte Carlo methods (with Andreas Galanis and collaborators). Key projects involve graph homomorphisms , Moran process dynamics , and #BIS complexity class analysis. Recent publications (2023-2024) span topics like Sybil defense mechanisms, low-temperature sampling on random graphs, and parameterised subgraph counting modulo 2. Her work demonstrates cross-disciplinary impact in computational biology, statistical physics, and database theory. Scientific Awards include Best Paper Prizes at ICALP 2016, ICALP 2010, and IPEC 2017. She supervises PhD student Paulina Smolarova and collaborates extensively with researchers in Oxford and beyond.
Professor Nidhi Sofat is a Professor of Rheumatology at St George's, University of London, and a Consultant Rheumatologist at St George's University Hospitals NHS Foundation Trust. She leads the NIHR Integrated Academic Programme for Clinical Academic Trainees, overseeing research and training programs such as the PGCert in Research Skills and Methods. She qualified in medicine from University College London (1996) with First Class Honours, completed specialist rheumatology training in 2007, and earned her PhD from the Kennedy Institute of Rheumatology (Imperial College London). Her research focuses on understanding pain and inflammation in musculoskeletal diseases, particularly osteoarthritis and rheumatoid arthritis. Her group pioneered the Osteoarthritis Bone Score (OABS), the first histological scoring system for bone marrow lesions in osteoarthritis. Key research areas include mechanisms of pain sensitization, imaging techniques (MRI), clinical trials (e.g., DUPRO, PAPO), and collaborations with institutions like the University of Nottingham and Royal Veterinary College. She has received awards such as the Michael Mason Prize (2013) and Wellcome Trust Fellowship (2003). Her clinical roles include managing general rheumatology, inflammatory arthritis, and osteoarthritis at the Hotung Centre. She has contributed to national guidelines via the Arthritis and Musculoskeletal Alliance (ARMA) and served on committees like the British Society for Rheumatology's Heberden Committee. Major grants include funding from NIHR, Versus Arthritis, and the Wellcome Trust. Collaborations span academic and industry partners, including Pfizer and Merck. Her translational research facility bridges clinical and experimental work, aiming to improve diagnostic tools and therapies for arthritis.
Dr. Dirk Sudholt is a Full Professor at the University of Passau and a Visiting Professor at the University of Sheffield. He holds a Ph.D. from Technische Universität Dortmund and has held postdoctoral positions at the International Computer Science Institute (ICSI) in Berkeley and the University of Birmingham. His research focuses on randomized algorithms, algorithmic analysis, and combinatorial optimization, with expertise in the theoretical analysis of bio-inspired search heuristics like evolutionary algorithms and ant colony optimization. His work emphasizes rigorous runtime analysis to understand algorithmic performance and design principles. Education: PhD in Computer Science, Technische Universität Dortmund (2008) Diploma in Computer Science, Technische Universität Dortmund (2004) Research Interests: Runtime analysis of evolutionary algorithms Algorithmic design for multimodal optimization Noise robustness in metaheuristics Parallel and distributed evolutionary computation Grants: SAGE: Speed of Adaptation in Population Genetics and Evolutionary Computation (EU FP7, 2014–2016) Teaching: University of Passau: Courses on algorithms, evolutionary computation, and randomized algorithms
Thomas Jansen is an Associate Professor and Head of the Department of Computer Science at Aberystwyth University. His research focuses on evolutionary algorithms, stochastic search heuristics, and theoretical computer science, with particular emphasis on optimization, dynamic environments, and algorithm performance analysis. He has led and contributed to several research projects, including the Wales Randomised Optimisation Algorithms Network (focused on advancing AI and optimization techniques) and the ImAppNIO project (bridging theory and practice in nature-inspired optimization). His academic contributions include foundational work on fixed budget analysis, multi-objective optimization, and the role of populations in dynamic optimization problems. Jansen has edited conference proceedings such as the 2015 ACM Conference on Foundations of Genetic Algorithms, further cementing his role in advancing the theoretical underpinnings of evolutionary computation. Key collaborations include work with researchers like Christine Zarges and Per Kristian Lehre, exploring topics like lexicase selection and immunological algorithms. His research has been presented at major conferences like PPSN and EvoCOP, and he actively participates in organizing workshops on randomized optimization algorithms.
Luca Zanetti is a Research Fellow at the University of Cambridge , affiliated with the Computer Laboratory and Department of Computer Science and Technology . He works under the supervision of Thomas Sauerwald, following his PhD at the University of Bristol with He Sun. Education PhD in Computer Science, University of Bristol His research focuses on spectral graph theory , unsupervised/semi-supervised learning on graphs , randomised and distributed algorithms , and Markov chains . His work bridges algorithm design, machine learning, and mathematical analysis of graphs. Recent publications explore clustering directed graphs , dynamic graph random walks , distributed graph sparsification , and spectral clustering guarantees . These span theoretical computer science , machine learning , and applied mathematics . He has taught advanced courses at Cambridge, including Probability and Computation (Part II/III/MPhil) and Advanced Topics in Machine Learning . He has served on program committees for SPAA 2020 and IJCAI 2020, and delivered talks at major conferences like ESA, ICALP, and Random Structures & Algorithms.
Dr Nathan Bray is a Senior Lecturer in Preventative Health and Lecturer in Healthcare Improvement at Bangor University, affiliated with the School of Health Sciences and the College of Medicine & Health. He leads the Academy for Health Equity, Prevention and Wellbeing (AHEPW) and is actively involved in research, grant leadership, and academic service. PhD in Health Economics, Bangor University (2015) MSc in Public Health and Health Promotion, Bangor University (2013) BSc in Psychology, University of Liverpool (2007) Dr Bray's research centers on public health and disability, with a focus on economic evaluation of assistive technologies and mobility aids. His work aims to improve quality of life measurement for people with mobility impairments, particularly through the development of novel instruments like the MobQoL-7D and WATCh tools. He explores how economic methods can inform equitable healthcare decisions and policy. His recent publications span topics such as cost-effectiveness of early powered mobility for children, patient-centered outcome measures in wheelchair services, and health economics of well-being across the life course. These works reflect a strong trend toward developing and validating tools that capture mobility-specific quality of life and evaluating interventions through economic modeling and systematic reviews. Post-doctoral fellowship by Health and Care Research Wales (2016) Dr Bray has contributed to over £7.5 million in grant capture as lead or co-applicant, with funding from NIHR, Horizon 2020, Health and Care Research Wales, and NHS England. He supervises PhD students and has led major projects like EMPoWER and AdaptQoL. He was Associate Editor for the British Journal of Dermatology (2017–2021) and chaired the International Society of Wheelchair Professionals’ committee (2015–2018). He currently serves on the Health and Care Research Wales Social Care PhD Studentship Committee and is College Lead for Sustainability. He leads the development of key research tools including the MobQoL-7D for measuring mobility-related quality of life and the WATCh/WATCh-Ad instruments for assessing outcomes in pediatric and adult wheelchair users. These tools are used in clinical and research settings to ensure patient-centered care and evaluation.
Patrick Mitchell is a Professor of Neurosurgery at Newcastle University and an Honorary Consultant Neurosurgeon with the Newcastle upon Tyne Hospitals NHS Foundation Trust. His career is anchored in clinical neurosurgery, translational research and multi-centre randomised controlled trials, with over 150 peer-reviewed publications spanning more than two decades. Education and Training Details of undergraduate or postgraduate degrees are not explicitly listed in the supplied text; however, his long-standing academic and consultant appointments at Newcastle imply completion of UK higher surgical training and award of MD/PhD-equivalent research credentials. Research Interests Professor Mitchell’s work clusters into four major domains: Cerebrovascular Surgery & Interventions : natural history and treatment of intracranial aneurysms, arteriovenous malformations, and subarachnoid haemorrhage. Traumatic Brain Injury : decompressive craniectomy, intracerebral haemorrhage evacuation, and imaging biomarkers of outcome. Clinical Trials & Evidence-Based Neurosurgery : leadership roles in STICH (Surgical Trial in Intracerebral Haemorrhage), STITCH(Trauma), RESCUEicp, CENTER-TBI and other international RCTs and observational studies. Human Factors & Patient Safety : surgical error analysis, simulation training, and development of national safety curricula. Publication Themes Across 2020–2024 his papers focus on pandemic-related service reconfiguration, novel imaging metrics for haemangioblastomas, conservative management strategies for lumbar disc disease, and comprehensive scoping reviews on idiopathic intracranial hypertension. Earlier work (2010–2019) concentrated on RCT secondary analyses, surgical decision-making algorithms, and meta-analyses of decompressive craniectomy. Awards & Honours While specific honours are not enumerated in the text, sustained leadership of NIHR-HTA and European Union FP7 funded trials (STICH, RESCUEicp, CENTER-TBI) attests to national and international recognition. Grants & Funding National Institute for Health Research (NIHR) Health Technology Assessment Programme – multiple awards for STICH and STITCH(Trauma) trials. European Union FP7 – funding for CENTER-TBI longitudinal observational study. UK Medical Research Council (MRC) – support for imaging sub-studies within traumatic brain injury cohorts. Laboratory & Clinical Teams Professor Mitchell co-directs the Newcastle Neurosurgery Clinical Trials Unit and collaborates with the Regional Neurosciences Centre at the Royal Victoria Infirmary. He mentors neurosurgical trainees and research fellows within the Northern Deanery and is an active member of the Society of British Neurological Surgeons research committee.
Laura Davies is a Senior Lecturer in Sociology at Leeds Beckett University's School of Humanities and Social Sciences. She serves as Associate Director of the Centre for Applied Social Research (CeASR) and PGR Tutor for CeASR subject groups, while also participating in university-wide Equality, Diversity, and Inclusion (EDI) initiatives through the School EDI Committee. Affiliation: Leeds Beckett University Role: Senior Lecturer, Associate Director (CeASR) Contact: L.A.Davies@leedsbeckett.ac.uk Laura's research examines how policy interventions intersect with service users' lived experiences, particularly focusing on: Fragmented welfare state navigation Policy assumptions vs. user realities EDI implementation in emergency services (Mountain Rescue collaboration) Life-course transitions and care ethics Welfare-to-work dynamics She teaches modules on inequality, class, and the welfare state while supervising dissertation students. Her methodological expertise includes qualitative research, policy evaluation, and secondary data analysis.
Craig Childs is a Senior Lecturer in Biomedical Engineering at the University of Strathclyde , United Kingdom. His research focuses on biomechanics , gait analysis , and assistive technology , with applications in rehabilitation engineering and pedestrian mobility . Research Trends Chronic ankle instability rehabilitation Wearable robotics and gait feedback systems Functional joint modelling for motion analysis Pedestrian safety and shared space accessibility Key Projects Development of the Strathclyde cluster gait model Human-in-the-loop control for ankle-foot robots Portable balance platforms for elderly postural stability PAMELA laboratory for pedestrian environment testing
Dr. Peter Davies-Peck is an Assistant Professor in the Department of Computer Science at Durham University. His research focuses on distributed algorithms, graph theory, and parallel computing. He has held roles on programme committees for major conferences like PODC and ICDCS, and has been an invited speaker at workshops associated with DISC. His research interests include Graph Algorithms, Distributed Algorithms, Randomised Algorithms, and Communications Networks. Notable work involves applying the Lovász Local Lemma to distributed computing challenges and developing efficient message-passing protocols in noisy environments. Recent contributions include advancements in parallel derandomization for graph coloring, optimal message-passing in radio networks, and distributed mean estimation techniques. His work bridges theoretical algorithm design with practical distributed system challenges, emphasizing scalability and resilience. Esteem indicators include Programme Committee membership for PODC 2023, ALGOSENSORS 2022, and ICDCS 2021. His publications span top venues like STOC, SODA, and the Journal of the ACM, reflecting impactful contributions to theoretical computer science and distributed systems.
Dr. Linsay McCallum is an Honorary Clinical Senior Lecturer at the School of Cardiovascular & Metabolic Health, University of Glasgow. She specializes in hypertension research, cardiovascular health, and clinical trials, with a focus on machine learning applications in medicine. Her work includes studies on long-term effects of SARS-CoV-2 on vascular health, genotype-dependent antihypertensive therapies, and patient empowerment via digital health tools. Research Interests: Dr. McCallum’s studies span hypertension pathophysiology, blood pressure variability, and translational research. She leads initiatives like the LOCHINVAR project examining post-COVID vascular impacts and the OPTIMA-BP trial evaluating web-based patient education. Her work integrates clinical data with machine learning techniques to improve diagnostic accuracy and treatment personalization. Grants & Collaborations: She has secured funding from Heart Research UK (2021–2024) for SARS-CoV-2 vascular effects research and the Mason Medical Research Foundation (2018–2020) for studies on hypospadias-related cardiovascular risks. Collaborations include teams at the University of Glasgow and international clinical centers. Labs/Teams: Affiliated with cardiovascular research groups within the School of Cardiovascular & Metabolic Health, focusing on translational hypertension research and clinical trial coordination.
Kim May Lee is a Research Fellow at King’s College London (since 2021), specializing in clinical trial methodology. She previously held roles as Lecturer in Medical Statistics at Queen Mary University of London (2020–2021) and Research Associate at the MRC Biostatistics Unit, University of Cambridge (pre-2020). She earned her PhD in Statistics from the University of Southampton, following an undergraduate degree in Mathematics with Actuarial Science from the same institution. Her research focuses on advancing clinical trial methodologies, particularly adaptive designs, platform trials, and subgroup analysis. Key interests include improving trial efficiency through personalized approaches, handling missing data, and optimizing experimental designs. She also provides statistical consultation for clinical trials and has lectured in medical statistics across multiple institutions. Recent publications emphasize innovative trial designs, sample size calculations, and methodological challenges in adaptive approaches. Notable work includes evaluating the Personalised Randomized Controlled Trial (PRACT) framework and exploring the impact of heterogeneity in platform trials. Her expertise bridges statistical rigor with practical clinical applications, addressing gaps in trial conduct and data quality. Current research trends highlight collaboration with multi-disciplinary teams to enhance methodological solutions for modern clinical challenges.
Philip Brown is a researcher at Newcastle University actively contributing to interdisciplinary studies in medicine, neuroscience, and biomedical engineering. His work focuses on: Real-world gait analysis using wearable sensors Immunotherapy for rheumatoid arthritis Digital mobility outcomes and patient-centered design Neuroimaging and algorithm development for movement disorders Recent publications highlight collaborations with Mobilise-D consortium and advancements in wearable technology validation. While no formal awards or student advising details are listed, his research spans clinical trials, deep learning applications, and sensor-based rehabilitation strategies.
Dr. Thomas Sauerwald is a Senior Lecturer in Algorithms and Probability at the Department of Computer Science and Technology, University of Cambridge. His research focuses on algorithms, probability theory, distributed computing, and graph theory, with particular emphasis on random walks, load balancing, and network analysis. He teaches courses such as 'Introduction to Probability' and 'Randomised Algorithms.' His work explores theoretical foundations of randomized processes in networks, including rumor spreading, balanced allocations, and the robustness of graph structures. He has contributed significantly to understanding the performance of distributed systems and stochastic algorithms in dynamic environments. His research often bridges algorithm design with probabilistic analysis, yielding insights into efficient resource distribution and information dissemination. Dr. Sauerwald's recent studies include analyzing time-biased random walks, coalescence dynamics in graphs, and the impact of noise in allocation processes. His findings have implications for optimizing network protocols, improving load balancing strategies, and modeling real-world information propagation phenomena.
Christl Donnelly CBE is a Professorial Fellow in Statistics at the University of Oxford's Department of Statistics, affiliated with St Peter’s College. She holds dual affiliations with Imperial College London (since 2000) and has held prior roles at the University of Edinburgh (1992–1995) and the Wellcome Trust Centre for the Epidemiology of Infectious Diseases at Oxford (1995–2000). Her academic credentials include a BA in Mathematics from Oberlin College and MSc/ScD in Biostatistics from Harvard School of Public Health (graduated 1992). Her research focuses on infectious disease epidemiology, with expertise in outbreak dynamics, statistical modeling, and public health policy. Key areas include Zika, Ebola, MERS, influenza, and rabies, alongside conservation and animal welfare. She is a leading member of the WHO Ebola Response Team and previously chaired the Independent Scientific Group on Cattle TB, overseeing the Randomised Badger Culling Trial (1998–2007). Her methodological contributions span phylogenetic analysis, epidemic modeling, and AI-driven surveillance. Donnelly has received prestigious recognitions, including Royal Society Fellowship, Academy of Medical Sciences Fellowship, and an Honorary Fellowship from the Zoological Society of London. Her work bridges academic research and real-world policy, emphasizing One Health approaches and interdisciplinary collaboration.
