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Dr. Sarah A.M. Loos is a Research Fellow at the Department of Applied Mathematics and Theoretical Physics (DAMTP) at the University of Cambridge and a Research Fellow at Corpus Christi College, Cambridge. She holds a PhD in Physics (summa cum laude) from TU Berlin (2020), with postdoctoral research at ICTP (Trieste) and Leipzig University. Her research focuses on stochastic thermodynamics, non-Markovian processes, and nonreciprocal systems. She has received major awards including the Royal Society of Chemistry Early Career Award (2024) and Marie Skłodowska Curie Fellowship (2023). Education: PhD in Physics (2020, TU Berlin), Master's in Physics (2015, TU Berlin), Bachelor's in Physics (2012, TU Berlin). Research interests include entropy production in nonreciprocal systems, active matter, and control theory. She has organized workshops on adaptive dynamical systems and contributed to KITP programs on active solids. Publications span topics like optimal control at microscale, PT symmetry in non-Hermitian systems, and nonreciprocal heat transfer. Her work bridges statistical physics and nonlinear dynamics, with applications in biological and nanoscale systems. Awards: 8 major prizes including DPG and RSC recognitions Grants: MSCA Fellowship (€200k), DFG Walter-Benjamin Fellowship Labs/Teams: Active Matter Group at DAMTP, collaborations with Édgar Roldán and Klaus Kroy

• Stochastic Thermodynamics
• Non-Markovian Processes
• Nonreciprocal Systems
• +۵ مورد دیگر

Dr. Sarah Loos is an independent postdoctoral researcher at the Department of Applied Mathematics and Theoretical Physics (DAMTP), University of Cambridge, and a Research Fellow at Corpus Christi College. Her work focuses on theoretical descriptions of nonequilibrium systems, integrating statistical physics, thermodynamics, control theory, and nonlinear dynamics. PhD in Statistical Physics (TU Berlin, 2020) Marie-Curie and DFG Walter-Benjamin Fellow Key research areas: stochastic thermodynamics, non-Markovian processes, active matter, nonreciprocal systems Her research explores entropy production, time-reversal asymmetry, and collective dynamics in active matter. She has received multiple awards, including the Royal Society of Chemistry's Early Career Award (2024) and Springer Thesis Award (2020). Recent publications emphasize nonreciprocal interactions, optimal control protocols, and memory effects in complex systems. Scientific Awards: Early Career Award (2024) Marie-Skłodowska-Curie Fellowship (2022) DFG Walter-Benjamin Fellowship (2022) SKM Dissertation Prize (2021) Carl Ramsauer Preis (2020) EPL Poster Prize (2019) Her work has been supported by the Joachim-Herz Stiftung (2022) and Studienstiftung des Deutschen Volkes (2013-2015). Collaborations span institutions like ICTP Trieste, Leipzig University, and Duke University.

• Stochastic Thermodynamics
• Non-Markovian Processes
• Active Matter
• +۴ مورد دیگر

Dr. Lorenzo Pellis is a Research Fellow at the University of Manchester, holding the Sir Henry Dale Fellowship, and a Visiting Fellow at the University of Warwick's Mathematics Institute and Zeeman Institute. He is also an Honorary Research Associate at the Medical Research Council (MRC) Centre for Outbreak Analysis and Modelling, within the Department of Infectious Disease Epidemiology at Imperial College London. His research bridges applied mathematics and epidemiology, focusing on developing models that inform public health decisions. He earned his Doctoral degree in Mathematical Biology from Imperial College London in 2009, with a dissertation titled Mathematical models for emerging infections in socially structured populations: the presence of households and other social structures II: Comparisons and implications for vaccination . Pellis's research interests include the development of novel deterministic and stochastic methods to model infection spread dynamics, particularly in human populations with complex social structures. He focuses on directly transmitted infections and the impact of co-infections on epidemiological and evolutionary outcomes. His work emphasizes multi-scale models integrating within-host and between-host processes, with applications to antimicrobial resistance, HIV-TB co-infections, and respiratory syncytial virus (RSV) transmission in Kenya. He also explores model comparison techniques to assess the utility of simple models in public health decision-making. His recent articles collectively explore mathematical modeling in infectious disease dynamics, with a focus on network-based approaches, multi-strain infections, and the integration of within-host and between-host processes. They highlight challenges in metapopulation and network models, as well as the evolutionary dynamics of HIV and TB co-infections. Sir Henry Dale Fellow , funded by the Wellcome Trust and Royal Society His grants include support for his Sir Henry Dale Fellowship, which funds research on co-infections and multi-scale models. He collaborates with Prof. Matt Keeling and Dr. Thomas House at Warwick and Prof. James Nokes on RSV studies in Kenya. His work also involves improving epidemic dynamics approximation methods on networks. He is affiliated with the applied Mathematics group at Manchester's School of Mathematics, the Zeeman Institute at Warwick, and the MRC Centre at Imperial College. His interdisciplinary collaborations span institutions and disciplines, including applied mathematics, epidemiology, and public health.

• Infectious Disease Epidemiology
• Mathematical Modeling
• Epidemiology
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Andrea Rocco is an Associate Professor in Physics and Mathematical Biology and Head of the Quantum Sciences Research Group at the University of Surrey. He holds affiliations with the School of Mathematics and Physics and the Centre for Mathematical and Computational Biology. Rocco earned his PhD in Physics from the University of North Texas (1998) and held postdoctoral positions at the University of Barcelona, University of Rome La Sapienza, CWI (Netherlands), and the University of Oxford. His research bridges theoretical physics (quantum mechanics, open systems, decoherence) and biological physics (stochastic dynamics in living systems, gene networks). Educations: BSc in Physics, University of Pisa (1994) PhD in Physics, University of North Texas (1998) Research Interests: His work explores quantum-classical transitions, quantum thermodynamics, and noise-induced phenomena in biological systems. Recent grants include a US$3M award for studying time and life. He is a Fellow of the Royal Society of Biology and the Higher Education Academy. Awards: Member of the Institute of Physics (MInstP) Fellow of the Higher Education Academy (FHEA) Fellow of the Royal Society of Biology (FRSB) Advising & Grants: Rocco leads the Quantum Sciences Group and has supervised postdoctoral researchers like Thomas Guff. His grants include major funding for interdisciplinary quantum-biological research. Labs/Teams: Head of the Quantum Sciences Research Group at Surrey, integrating theoretical physics and computational biology.

• Theoretical Physics
• Quantum Mechanics
• Biological Physics
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Professor Sergei Fedotov is a Professor of Applied Mathematics in the Department of Mathematics at the University of Manchester. He holds a PhD from Ural Federal University (1986) and has held academic positions in London, Aachen, Wuppertal, and Berlin before joining Manchester in 1998. His research focuses on random walk theory, reaction-transport systems, and anomalous transport phenomena with applications to biophysics, nanotechnology, and cancer biology. His expertise includes non-Markovian models, fractional calculus, and interdisciplinary collaborations in areas such as intracellular transport, nanoparticle dynamics, and DNA repair. Fedotov has led major grants, including EPSRC-funded projects on nanoparticle transport in radiotherapy and FAPESP-UoM collaborations on correlated memory in biological systems. He has supervised PhD students including Anna Gavrilova, Daniel Han, and Helena Stage, and collaborates with institutions globally, such as Universitat Autònoma de Barcelona and The Christie Hospital. Key research themes include stochastic models of subdiffusion/superdiffusion, fractional partial differential equations, and the application of statistical mechanics to biological systems. His work contributes to sustainable development goals through advancements in medical physics and environmental modeling. Recent publications explore heterogeneous transport in C. elegans, stochastic water flow dynamics, and the modeling of radiation-induced DNA damage. Fedotov’s team develops novel frameworks to bridge theoretical mathematics with experimental biology, emphasizing the role of memory effects and non-equilibrium processes. Grants managed include the EPSRC £702k project on improving radiotherapy via nanoparticle transport modeling (2021–2025) and the FAPESP-UoM study on correlated memory in biological systems (2018–2022). His work integrates mathematical rigor with experimental validation, addressing challenges in cellular logistics and disease mechanisms.

• Random Walk Theory
• Reaction-Diffusion Systems
• Non-Markovian Processes
• +۳ مورد دیگر

Víctor Rivero is a Professor in the Department of Probability and Statistics at the Center of Research in Mathematics (CIMAT) in Guanajuato, Mexico. He previously served as Director of CIMAT from January 2017 to December 2022 and spent a sabbatical year (August 2023-July 2024) at the Probability Group of the Department of Statistics at the University of Warwick, UK. Starting in 2025, he will serve as Editor of ALEA - Revista Latinoamericana de Probabilidad y Estadistica and is part of the Scientific Committee for the 11th International Conference on Lévy Processes to be held in Sofia, Bulgaria in 2025. He also serves on the steering committee of the CIMAT-UNAM-Warwick-Bath research platform for UK-Latin America engagement in probability. Rivero's research focuses on probability theory and stochastic processes, with particular expertise in Lévy processes, Markov processes, and self-similar processes. His work spans fluctuation theory of real-valued Lévy processes and Markov additive processes, stable processes, excursion theory, local times as stochastic processes, branching processes, and regenerative sets. He has developed deep connections between these areas, often using the Lamperti transform to relate self-similar Markov processes to Lévy processes. An analysis of his recent publications reveals a continued focus on foundational aspects of probability theory with applications to various mathematical models, particularly examining how scaling properties and self-similarity manifest in complex systems with increased attention to multidimensional settings and connections to biological models. Rivero actively mentors graduate students at institutions including CIMAT, University of Warwick, and University of Bath, frequently collaborating with other researchers like Andreas Kyprianou on student supervision. He has been a frequent visitor to leading probability research centers worldwide, including institutions in France (Université Sorbonne Paris Nord, Angers) and the UK (Bath, Warwick, Manchester). His teaching includes courses on Lévy processes and self-similar Markov processes, with lecture notes available for students. He is also part of the Network of Creative Teaching in Mathematics, which aims to promote mathematics as an activity that stimulates creative, conceptual, and emotional development.

• Probability Theory
• Stochastic Processes
• Lévy Processes
• +۵ مورد دیگر

David Stainforth is a Professorial Research Fellow at the Grantham Research Institute on Climate Change and the Environment at the London School of Economics and Political Science (LSE) and an Honorary Professor in the Department of Physics at the University of Warwick. A physicist by training, he co-founded the climateprediction.net project at Oxford University and has focused on climate modeling, uncertainty quantification, and decision-making under deep uncertainty. Primary Affiliation: Grantham Research Institute on Climate Change and the Environment, LSE Honorary Professor: Department of Physics, University of Warwick Research Interests : Stainforth investigates uncertainty in climate modeling , nonlinear dynamical systems , and climate economics . His work bridges climate science and policy analysis , emphasizing the challenges of linking climate projections to societal decision-making . He critiques the use of probability distributions in climate projections and advocates for restructuring academic research to better address climate change’s interdisciplinary challenges. Scientific Contributions : His recent work focuses on parametric uncertainty in climate models , economic damages from temperature variability , and assessing regional climate information . Key trends in his articles include nonlinear climate responses , integrated assessment models , and innovative approaches to adaptation planning . Scientific Awards : Lloyds Science of Risk Prize 2021 for research on temperature variability and economic damages NERC Research Fellowship Tyndall Research Fellowship Advising and Grants : Stainforth collaborates extensively with researchers like Raphael Calel, Suraje Dessai, and Erica Thompson on climate policy , economic assessments , and uncertainty frameworks . His projects often involve interdisciplinary grants and large-scale climate modeling experiments . Labs and Teams : He co-founded and led the climateprediction.net project, the world’s largest climate modeling experiment. He contributes to initiatives like the UK Climate Projections (UKCP09) and decision-making under uncertainty frameworks.

• Climate Modeling
• Climate Economics
• Uncertainty Quantification
• +۵ مورد دیگر

Dr. Philip Brabazon is a Senior Lecturer at the University of Portsmouth, affiliated with the School of Organisations, Systems and People and the Centre for Operational Research & Logistics. His work focuses on operational research, logistics, and mass customization in industries such as automotive and manufacturing. He has published extensively on topics including order fulfillment systems, supply chain management, and production economics. Dr. Brabazon is currently accepting PhD students and has supervised 7 theses. His research explores themes like automotive order-to-delivery processes, virtual build-to-order systems, and the application of simulation in operational systems. He has contributed to understanding mass customization strategies, risk analysis in offshore operations, and safety case frameworks. His work bridges theoretical models with practical industry applications, particularly in optimizing supply chains and production systems. Notable publications include analyses of automotive logistics, long-tail retail dynamics, and Markovian approximations in fulfillment systems. His research has been cited over 100 times in key journals like the European Journal of Operational Research and Production and Operations Management.

• Operational Research
• Logistics
• Mass Customization
• +۵ مورد دیگر

Andrew Titman is a Professor in the School of Mathematical Sciences at Lancaster University . His research focuses on survival analysis and multi-state modeling with applications in medical statistics and quantitative methodology. Primary Affiliation: School of Mathematical Sciences, Lancaster University Contact: a.titman@lancaster.ac.uk Research Interests include: Development of non-Markov multi-state models for complex survival data Latent variable modeling for health-related quality of life questionnaires Methodology for informative observation times in clinical trials Health economic decision modeling applications Survival analysis with misclassification and time non-homogeneity Recent Publications demonstrate expertise in: Bayesian state-space models for sports analytics Multi-state model diagnostics and goodness-of-fit testing Medical applications in endocrinology and hematology Simulation methodology with input uncertainty quantification Scientific Contributions include: Development of R packages: nhm, CIFresolve, miscIC Creation of the MarkovTest GitHub repository for multi-state model validation Methodological frameworks for non-homogeneous Markov models

• Survival Analysis
• Multi-State Modeling
• Medical Statistics
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Dr. Robert Lieck is an Assistant Professor in the Department of Computer Science at Durham University. He holds a PhD from the Machine Learning and Robotics Lab (now Learning and Intelligent Systems Lab) in Stuttgart/Berlin, Germany, and completed a postdoctoral position at the Digital and Cognitive Musicology Lab at EPFL, Switzerland. His research focuses on interdisciplinary applications of machine learning and artificial intelligence, with particular emphasis on cognitive modelling, music cognition, and ethical AI. Education: PhD in Machine Learning and Robotics, Stuttgart/Berlin, Germany (2012–2017) MSc Physics and Philosophy, Freie Universität Berlin Research Interests: Probabilistic Modelling (Bayesian inference, graphical models) Neuro-Symbolic Modelling (differentiable parsing algorithms) Structure Learning (feature discovery, hierarchical systems) Applications in music analysis, medical imaging, and autonomous systems Ethical implications of AI in policy and legislation Publications: Recent work includes advancements in deep reinforcement learning for diabetes management, recursive Bayesian networks, and computational models of musical expectancy. His research bridges theoretical AI with practical applications in musicology and healthcare. Students: Supervising four postgraduate students: Ishaq Ibrahim, Megan Finch, Ningxiang Xie, Xiaotang Zhang Labs: Active contributor to the Digital and Cognitive Musicology Lab (EPFL) and Durham's Computer Science research groups.

• Machine Learning
• Artificial Intelligence
• Probabilistic Modelling
• +۱۰ مورد دیگر

Prof. Selin Damla Ahipasaoglu is a Professor in Operational Research at the University of Southampton's School of Mathematical Sciences . She serves on the management team of the UKRI CDT SustAI (Artificial Intelligence for Sustainability) as Senior Tutor and Co-Lead for the Transportation and Logistics Theme . Her work bridges mathematical optimization with practical applications in sustainability, finance, and transportation systems. Research Interests : Convex Optimization Robust Optimization Discrete Choice Theory Experimental Design Machine Learning Current Research : Focused on robust optimization and its applications in discrete choice modeling, portfolio optimization, and transportation systems. She explores theoretical frameworks alongside real-world implementations, particularly through interdisciplinary projects like the UKRI CDT SustAI. Teaching : In the 2025/2026 academic year, she teaches MATH3017: Mathematical Programming and MATH2013: Operational Research II . She supervises PhD students in Mathematical Sciences, including Kexin Lai, Samuel Jericho Ward, and others.

• Operational Research
• Convex Optimization
• Robust Optimization
• +۵ مورد دیگر

Professor Dan Crisan is a Professor of Mathematics at Imperial College London and Director of the EPSRC Centre for Doctoral Training in the Mathematics of Planet Earth. He holds a PhD in Mathematics from the University of Edinburgh and an MSci in Mathematics from the University of Bucharest. His research focuses on Stochastic Analysis, Stochastic PDEs, Fluid Dynamics, Nonlinear Filtering, and Data Assimilation. He leads the Stochastic Transport in Upper Ocean Dynamics (STUOD) project, supported by an ERC Synergy Grant, exploring stochastic models in geophysical fluid dynamics. His academic roles include directing the MPE CDT and teaching advanced courses like Stochastic Calculus with Applications to Non-Linear Filtering. He collaborates extensively with researchers globally on topics including stochastic fluid dynamics, particle methods, and Bayesian inference. His work bridges theoretical advancements with applications in climate modeling and environmental systems. Education: PhD (University of Edinburgh, 1996), MSci (University of Bucharest, 1992). Professional roles include Director of MPE CDT (2013–present), Professor at Imperial College (2011–present), and prior academic appointments at the University of Cambridge and Imperial College. His research emphasizes stochastic processes in fluid dynamics, with projects funded by EPSRC and EU grants. Current PhD supervision opportunities are available in areas like stochastic fluid dynamics and data assimilation. Key achievements include foundational contributions to particle filtering, numerical methods for stochastic PDEs, and stochastic transport models. His work on the Camassa-Holm equation and rotating shallow water models demonstrates expertise in nonlinear wave dynamics and stochastic parametrization. He actively engages in international collaborations and serves on editorial boards for leading journals in stochastic analysis.

• Stochastic Analysis
• Fluid Dynamics
• Stochastic Partial Differential Equations (SPDEs)
• +۶ مورد دیگر

Professor Jonathan Keeling is Head of the School of Physics and Astronomy at the University of St Andrews, where he leads research in theoretical condensed matter physics with a focus on quantum phenomena. His work bridges fundamental quantum theory with potential applications in quantum technologies and materials science. His educational background includes a PhD from the University of Cambridge (2005) and a Master of Natural Science from Cambridge (2002). Prior academic positions include EPSRC Career Acceleration Fellow at Cambridge, Drapers' Junior Research Fellow at Pembroke College, and Lindemann Fellow at MIT. Keeling's research centers on open quantum systems and non-equilibrium phase transitions, with particular emphasis on light-matter interactions in systems like microcavity polaritons and cold atoms in optical cavities. His group explores how quantum coherence behaves out of equilibrium and how it can be dynamically controlled, with applications spanning quantum simulation, quantum information processing, and novel materials. Key research strands include cold atoms in optical cavities, exact numerical methods for phase transitions in open systems, and strong matter-light coupling with complex materials like organic molecules. His recent publications (2023-2025) reveal a strong focus on non-Markovian quantum dynamics, quantum spin glasses, polariton-mediated energy transfer, and computational methods for open quantum systems. The work shows increasing integration of theoretical frameworks with experimental implementations, particularly in cavity QED systems and quantum simulation platforms. Outstanding Referees Program, American Physical Society (2015) Keeling has supervised numerous PhD students and postdocs who have gone on to careers in academia and industry. His research is supported by multiple grants including an EPSRC-funded project on Multimode Cavity QED (2025-2027), previous EPSRC grants on understanding and engineering dissipation in quantum devices, and projects funded by The Royal Society and The Leverhulme Trust. He collaborates extensively with groups at Stanford, Cambridge, Aalto University, and other international institutions. The Keeling Group at St Andrews maintains active research programs in quantum simulation with cold atoms in cavities, theoretical modeling of organic polaritons, and development of numerical methods for non-Markovian quantum dynamics. The group contributes to the Centre for Designer Quantum Materials and maintains strong connections with experimental groups working on cavity QED implementations.

• Open quantum systems
• Non-equilibrium phase transitions
• Light matter interactions
• +۷ مورد دیگر

Professor Ian Melbourne is a Professor of Mathematics at the University of Warwick's Mathematics Institute. His research focuses on ergodic theory, dynamical systems, and their links with probability and stochastic analysis. He holds editorial roles at *Ergodic Theory and Dynamical Systems* and *Probability Theory and Related Fields*. His work explores complex systems such as fast-slow dynamics, Lévy processes, mixing rates, billiards, and statistical limit laws. Research Interests: Ergodic theory, dynamical systems, stochastic processes, Lévy processes, mixing rates, billiards, and statistical laws. His contributions span theoretical frameworks for deterministic homogenization, superdiffusive limits, and large deviations in non-equilibrium systems. Publications highlight advancements in understanding systems with singularities, such as Lorentz gases and intermittent maps. His recent work emphasizes convergence to Lévy processes and polynomial decay of correlations in nonpositively curved surfaces. He has advised numerous PhD students (not listed here) and contributes to the academic community through editorial work and collaborative research. No specific grants or labs are detailed in the provided texts.

• Ergodic Theory
• Dynamical Systems
• Probability Theory
• +۶ مورد دیگر

Mateusz Majka is an Assistant Professor in Stochastics at the School of Mathematical & Computer Sciences, Heriot-Watt University, Edinburgh. His research focuses on probability theory, stochastic analysis, numerical analysis, optimization, optimal transport, computational statistics, and machine learning. He holds a PhD from the University of Bonn (2017) and has held postdoctoral positions at the University of Warwick and King's College London. Education: PhD in Applied Mathematics, University of Bonn (2017) Research Fellow, University of Warwick (2018–2020) Research Associate, King's College London (2017–2018) Research Interests: Stochastic differential equations Mathematical foundations of machine learning (mean-field optimization, optimal transport, stochastic gradient algorithms) Lévy processes Ergodicity of Markov processes Monte Carlo methods (MCMC, Multi-Level Monte Carlo) Recent Research Trends: His work emphasizes algorithmic development for stochastic systems, including mean-field games, Wasserstein geometry, and convergence analysis of numerical schemes. Notable contributions span Lévy processes, Euler schemes, and coupling techniques for Markov chains. Awards: None explicitly listed. Advising & Grants: Supervises PhD students Linshan Liu (since 2021) and Razvan-Andrei Lascu (since 2022). Active in securing research funding through collaborative projects. Labs/Teams: Engaged in cross-disciplinary collaborations in computational statistics and stochastic analysis at Heriot-Watt University.

• Probability Theory
• Stochastic Analysis
• Numerical Analysis
• +۷ مورد دیگر