Prof. Dr. Alexander Lindner is a Professor at the University of Ulm's Institute of Financial Mathematics. His research focuses on stochastic processes, Lévy processes, time series analysis, mathematical finance, and risk theory. He has authored influential works like Continuous-parameter time series and contributed to statistical methods for stochastic processes. Education: Habilitation in Financial Data Modelling (2004, TU Munich); Doctorate in Mathematics (1999, Erlangen-Nürnberg). Teaching: Specializes in financial mathematics, time series analysis, stochastic calculus, and measure-theoretic probability. His research spans infinitely divisible distributions, CARMA processes, and applications in finance. He has supervised numerous PhD students and published extensively in top journals. Lindner served as an associate editor for Statistics and Probability Letters , Methodology and Computing in Applied Probability , and Journal of Time Series Analysis . He advises on bachelor/master theses in areas like option pricing, risk theory, and stochastic processes. Current PhD students include Michael Stanek and Maximilian Strobel.
Dan Ralescu is a Professor of Mathematics at the University of Cincinnati since 1980, affiliated with the Department of Mathematical Sciences in the College of Arts and Sciences. He holds editorial roles in 10 journals and has delivered plenary lectures globally. His research focuses on probability theory, fuzzy sets, and uncertainty modeling, with applications in finance, engineering, and decision theory. Education: PhD in Statistics (Indiana University, 1980), M.A. Mathematics with Honors (University of Bucharest, 1972), and additional M.A. in Mathematics/Statistics (Indiana University, 1979). Research interests include limit theorems for random sets, mixed uncertainty models, Bayesian robustness, and large data set management. His work bridges statistical methodologies with fuzzy logic systems, particularly in financial modeling and risk analysis. Key contributions include the Liu Process in uncertainty theory, portfolio optimization models using fuzzy time series, and risk index frameworks for uncertain systems. Awards include the 2014 Lifetime Achievement Award from China’s Society for Uncertainty and IFSA Fellowship. Active in grants since 1985, including NSF-funded projects on decision-making under uncertainty and collaborative efforts with international institutions like Tokyo Institute of Technology. He has supervised numerous research collaborations and publishes extensively in top-tier journals.
Nicholas D. Myers is a Professor in the Department of Kinesiology at Michigan State University (MSU), with an appointment in the Measurement and Quantitative Methods program within the Department of Counseling, Educational Psychology and Special Education. He serves as the program director for the MS in Kinesiology and Kinesiology PhD programs. His research integrates latent variable modeling with psychosocial aspects of sport and physical activity, focusing on behavioral interventions, self-efficacy measurement, and methodological advancements in quantitative analysis. Dr. Myers holds a Ph.D. from MSU and is affiliated with the College of Education. His interdisciplinary work bridges kinesiology, psychology, and statistics, emphasizing rigorous quantitative methods such as structural equation modeling, meta-analysis, and causal inference. He has contributed to eHealth intervention studies targeting physical activity promotion, particularly in populations with obesity, and has explored cultural and contextual factors influencing athlete performance and well-being. Key areas of research include the development and validation of measurement tools (e.g., self-efficacy scales, emotional regulation questionnaires), the analysis of causal pathways in intervention outcomes, and the application of modern statistical techniques (e.g., bifactor models, directed acyclic graphs). His work often addresses practical and methodological challenges in sport science and public health.
Professor Eugene Lytvynov is a mathematician affiliated with Swansea University's School of Mathematics and Computer Science. He holds the academic rank of Professor in the Mathematics department. His research focuses on infinite-dimensional analysis, point processes, noncommutative probability, and umbral calculus. Recent work explores non-Abelian anyon quasiparticles and basis-free umbral calculus. He is available to supervise postgraduate students and maintains active research collaborations through platforms like ORCID, ResearchGate, and Google Scholar. His expertise spans advanced mathematical fields including stochastic processes, quantum probability, and operator algebras. Key research areas include the analysis of Radon measures, quasi-free states, and commutation relations in multicomponent systems. He has contributed extensively to the study of determinantal point processes, particle-hole transformations, and Fock space representations. Professor Lytvynov's publications reflect a strong emphasis on theoretical frameworks, with notable work on Segal-Bargmann transforms, Stirling operators, and Meixner-class orthogonal polynomials. His research often bridges pure mathematics and quantum physics, addressing topics like anyon statistics and non-Gaussian white noise calculus. He is accessible via email at e.lytvynov@swansea.ac.uk and can be reached at the Computational Foundry, Bay Campus. His academic contributions include over 50 peer-reviewed articles, with a focus on advancing analytical tools in infinite-dimensional spaces and quantum systems.
Alexandru Hening is an Associate Professor in the Department of Mathematics at Texas A&M University, affiliated with the College of Arts & Sciences. His research focuses on probability theory, stochastic processes, and mathematical biology, with an emphasis on population dynamics, ecological modeling, and optimal control strategies. He holds a Ph.D. from UC Berkeley (2013) under advisor Steve Evans, and has held positions at Tufts University, Imperial College London, and Oxford University. His research interests include stochastic population dynamics in discrete/continuous time, random dynamical systems, optimal harvesting strategies, and numerical analysis of invariant probability measures. He explores long-term behavior of Markov processes, coexistence/extinction mechanisms in ecological communities, and control problems in fluctuating environments. He co-organizes the Mathematical Biology Seminar at Texas A&M and serves as an Associate Editor for the Journal of Mathematical Biology and Journal of Biological Dynamics . His work is supported by an NSF CAREER grant. Notable contributions include studies on stochastic SIQRS epidemic models, population size dynamics in multi-patch systems, and classification of stochastic ecological systems' dynamics. He actively contributes to interdisciplinary projects involving evolutionary stability of patch-selection strategies, quasi-stationary distributions, and numerical methods for stochastic processes. His research bridges theoretical probability with applications in ecology, epidemiology, and resource management.
Dr. Tim Janssen is an Assistant Professor (Research) in Brown University's Department of Behavioral and Social Sciences, affiliated with the Center for Alcohol and Addiction Studies. His work focuses on understanding mechanisms driving adolescent and young adult alcohol use initiation and escalation, leveraging momentary assessment techniques and structural equation modeling to bridge laboratory findings with real-world contexts. Education: PhD from University of Amsterdam; Postdoctoral Fellowship at Brown University's Center for Alcohol and Addiction Studies. Research emphasizes advancing analytical methods for improving empirical accuracy in substance use research, particularly through developmental modeling of risk factors. Current grants include NIH/NIAAA K01AA026335 and R21AA025716. His work addresses pandemic impacts on healthcare access for opioid use disorders and evaluates parenting interventions (e.g., Parent SMART) for adolescents in residential treatment. Key themes include media influences (e.g., movie alcohol content), social media's role in drinking behaviors, and implementation strategies for evidence-based treatments. Publications span over 15 years, with recent focus on cross-substance effects, technology-assisted interventions, and pandemic-related behavioral health challenges. No awards explicitly listed, but his NIH-funded projects reflect recognition of methodological rigor and public health relevance.
Javier Cristin Redondo is a researcher in the Department of Physics with an active publication record through 2024 and an h-index of 31. His work appears in high-impact journals including Physical Review, Journal of Physics A, and Scientific Reports, demonstrating his standing in the physics research community. His research focuses on mathematical modeling of complex systems, particularly examining discrete Laplacian thermostats, random walks on lattices, and entropy-based phenomena. His work spans statistical physics, mathematical modeling, and applications to biological systems such as ant foraging behavior and human decision-making processes. The research often bridges theoretical physics with real-world complex systems. Analysis of his recent publications reveals a consistent focus on developing mathematical frameworks for understanding collective behavior through discrete models. His work on discrete Laplacian thermostats represents innovative approaches to modeling conserved dynamics in spin systems and flocking behavior, while his research on entropy thresholds provides physical explanations for cognitive phenomena. Dr. Redondo maintains active collaborations with researchers including Cavagna, Giardina, Veca, Méndez, and Campos, indicating strong network connections within the physics research community. His work shows evidence of both theoretical developments and applications to biological systems, suggesting interdisciplinary impact.
Dr. Cassandra Pattinson is a Senior Research Fellow at the Child Health Research Centre within the Faculty of Health, Medicine and Behavioural Sciences at the University of Queensland. She is also affiliated with the ARC Centre of Excellence for the Digital Child and the ARC Centre of Excellence for Children and Families Over the Lifecourse. Her research focuses on exploring the effects of sleep and circadian rhythms on health, wellbeing, and recovery across the lifespan. Dr. Pattinson holds a Doctor of Philosophy from Queensland University of Technology. Her research has been supported by major funding bodies including the Australian Research Council (ARC), National Health and Medical Research Council (NHMRC), National Institutes of Health (NIH), and the Defence Science and Technology Group (DSTG). Her work spans diverse populations including children, adolescents, military personnel, and athletes. She employs multiple methodologies such as longitudinal studies tracking large child cohorts (>2000 children), physiological measurements (actigraphy, spectrometry), and biological analyses (hormones, proteomic, genomic). Dr. Pattinson is particularly known for her research on sleep practices in childcare settings, environmental light exposure effects on children's health, and the relationship between sleep, digital technology, and wellbeing across the lifespan. Analysis of Dr. Pattinson's recent publications reveals a strong focus on sleep health across different populations and contexts. Her research examines sleep patterns in children, adolescents, young adults, and vulnerable populations including those experiencing homelessness. She investigates the impact of environmental factors (light exposure, digital technology), traumatic events (flooding), and military service on sleep quality and health outcomes. Her methodological approaches span from population-based studies to biomarker identification and wearable technology applications. ARC Discovery Early Career Award (2025) Dr. Pattinson has an active supervision record, currently advising on 'The Role of Heart Rate Variability in Fatigue Assessment: A Multimodal Approach' and having recently completed supervision of PhD projects on 'Improving sleep health in young adults' and 'Sleep, plasticity, and non-invasive brain stimulation.' Her current funding includes the ARC Discovery Early Career Researcher Award project 'Understanding Light, Technology, and Environments of Children' (2025-2028) and the ARC Discovery Projects grant 'The developmental significance of sleep transition in early childhood' (2020-2025). At the Child Health Research Centre, Dr. Pattinson is part of the Community Sleep Health Group, which collaborates on issues related to sleep and technology, sleep and the environment (including disasters), mental health and wellbeing, pain, disability, and new technologies and approaches.
Yuxin Chen is a Professor at the Wharton School, University of Pennsylvania , appointed in both the Department of Statistics and Data Science and the Department of Electrical and Systems Engineering . He previously served as an Assistant Professor at Princeton University (2017–2021) and a Postdoctoral Scholar at Stanford University (2015–2017). Education: Ph.D., Electrical Engineering, Stanford University, 2015 M.S., Statistics, Stanford University, 2013 M.S., Electrical and Computer Engineering, UT Austin, 2010 B.S., Microelectronics, Tsinghua University, 2008 His research spans high-dimensional estimation , machine learning theory , nonconvex optimization , and statistical signal processing , with applications in medical imaging and computational biology . Recent work focuses on diffusion models , large language models (LLMs) , and reinforcement learning (RL) . His 15 most recent publications emphasize diffusion models (generalization, sampling efficiency, scientific applications), reinforcement learning (sample complexity, convergence theory), and nonconvex optimization (implicit regularization, statistical guarantees). Scientific Awards: Alfred P. Sloan Research Fellowship, 2022 Princeton SEAS Junior Faculty Award, 2021 Princeton Graduate Mentoring Award, 2020 ICCM Best Paper Award (Gold Medal), 2020 ARO Young Investigator Program (YIP) Award, 2020 AFOSR YIP Award, 2019 SIAM Activity Group on Imaging Science Best Paper Prize IEEE Transactions on Power Electronics Prize Paper Award (first place) He mentors PhD students and leads interdisciplinary research projects funded by agencies like the Army Research Office and Air Force Office of Scientific Research . His team develops frameworks such as LOCO Edit for controllable diffusion model editing and MagNet for power magnetics modeling .
Wouter Van Bogaert is a postdoctoral researcher at Vrije Universiteit Brussel (VUB) within the Physiotherapy, Human Physiology and Anatomy department. He holds roles as a UZB Researcher in Physical Medicine and Rehabilitation and is affiliated with the Pain in Motion Interuniversity Centre and Health Economics Research institute. His work focuses on chronic pain mechanisms, radiculopathy, and patient education interventions. Research interests include pain neuroscience, sex differences in pain outcomes, and the mediating roles of cognition and quality of life in chronic spinal pain. Notable projects include the FWOSB108 randomized controlled trial evaluating pain neuroscience education efficacy for lumbar radiculopathy patients. He has published 20 peer-reviewed articles (2019–2025), with recent focus on perioperative interventions, structural equation modeling of pain interactions, and health economic analyses of lifestyle interventions. Awards include the IASP Financial Aid Award (2022) and FWO grants supporting conference participation. Active in collaborative projects and has presented at 50+ academic events including workshops on directed acyclic graphs and pain science conferences. His work spans both clinical trials and methodological advancements in pain research.
Tracy Witte is a Professor in the Department of Psychological Sciences within the College of Liberal Arts at Auburn University. She serves as the Director of Clinical Training and leads the clinical psychology PhD program. Her research focuses on understanding and preventing suicidal behavior, with secondary interests in psychopathology such as PTSD, eating disorders, and alcohol use disorders. She also develops brief, accessible mental health interventions using both qualitative and quantitative methods. Dr. Witte received her education from top-tier institutions: a BS in Psychology from The Ohio State University (2004), followed by an MS (2006) and PhD (2010) in Clinical Psychology from Florida State University. She completed her pre-doctoral internship at Brown University Training Consortium. Her research spans multiple domains including suicide epidemiology, intervention development, digital mental health, and interdisciplinary work in veterinary mental health. She has published extensively on topics such as insomnia and suicide, social media behavior, means restriction, and cultural adaptation of interventions. Her work often employs advanced statistical methods like network analysis and latent modeling. Dr. Witte has mentored numerous graduate students, many of whom are co-authors on her publications. She teaches courses in psychopathology, ethics, clinical research methods, and structural equation modeling. She is actively involved in community outreach, including leading student initiatives at Circles Opelika and advocating for improved childcare infrastructure for academic staff through the American Association of University Professors. Director of Clinical Training, Auburn University Leader of the Suicidal Behavior and Psychopathology Lab Member, EAGLES Committee (2024–present) Lead researcher on multiple studies involving veterinary professionals’ mental health She has not received any explicitly mentioned scientific awards in the provided text, but her publication record in high-impact journals such as Psychological Review , American Psychologist , and Journal of the American Veterinary Medical Association reflects significant scholarly recognition.
Ana Navarro Quiles is an Associate Professor in the Department of Statistics and Operations Research at the Faculty of Mathematics, University of Valencia, Spain. She is a member of the PROMEDyA research group, focusing on prediction and optimization under uncertainty using dynamic stochastic models. PhD : Universitat Politècnica de València, 2018 Thesis : Computational Methods for Random Differential Equations: Theory and Applications Supervisors : Dr. Juan Carlos Cortés López, Dr. Rafael Villanueva Micó, Dr. María Dolores Roselló Ferragud Her research centers on probabilistic solutions of random differential equations, uncertainty quantification in biological and epidemiological models, and stochastic control systems. She employs advanced techniques such as the Random Variable Transformation (RVT) method and Karhunen-Loève expansion to analyze systems with random parameters. Her work bridges theoretical mathematics with real-world applications in public health, chemistry, and engineering. She has published extensively in journals like Journal of Computational and Applied Mathematics and Chaos, Solitons & Fractals . The recent publications reveal a strong trend toward modeling complex dynamical systems under full parametric uncertainty, particularly in biological growth (Gompertz, logistic) and disease spread (SIR-type models). Her methodological focus lies in deriving complete probabilistic solutions using transformation techniques and functional expansions, moving beyond mean-value approximations to capture full distributional behavior. No scientific awards are mentioned in the provided texts. Ana Navarro Quiles collaborates extensively with researchers from the Universitat Politècnica de València and other institutions. While no specific grants are listed, her sustained output suggests active funding support. She has not been explicitly mentioned as an advisor to students in the provided material, but her role in a PhD thesis as a supervisor's co-supervisee indicates strong mentoring experience. She is affiliated with the PROMEDyA research group (Prediction and Optimization under uncertainty: dynamic stochastic models and applications), which conducts interdisciplinary research on modeling uncertain dynamical systems with applications in science and engineering.
Craig Colder is a SUNY Distinguished Professor and Director of Graduate Studies in the Department of Psychology at the University at Buffalo, part of the State University of New York system. He is based in the College of Arts and Sciences and leads the Child and Adolescent Family Development Laboratory. His work integrates developmental, clinical, and cognitive perspectives to understand risk and resilience in youth. His research focuses on the development of adolescent substance use and aggression, examining influences at multiple levels: individual (e.g., temperament, personality), family (e.g., parenting styles, parent-adolescent communication), and community (e.g., neighborhood disadvantage). He employs advanced longitudinal modeling techniques, including bifactor models and within-person analyses, to disentangle complex developmental pathways. Colder’s recent publications span topics such as the validation of new assessment tools like the Parenting Styles Circumplex Inventory (PSCI), neurocognitive correlates of executive functioning in adolescence, and the role of effortful control in mitigating alcohol-related consequences. His work frequently appears in high-impact journals in developmental psychology, addiction science, and cognitive neuroscience. SUNY Distinguished Professor He mentors graduate students as Director of Graduate Studies and has been involved in numerous clinical and community-based studies, including interventions targeting hazardous drinking during the transition to parenthood and bystander approaches to reduce sexual assault risk. His research often incorporates ecological momentary assessment and multi-informant designs to capture dynamic processes in real time.
Alan Yang is an Assistant Professor of Information Systems at the University of Nevada, Reno (UNR), where he serves as the Director of the MSBA Program. His research focuses on mobile computing, healthcare information systems, and mechanisms for incentivizing healthy behaviors. He actively engages in teaching innovation, exploring technology-enhanced methods to improve student outcomes. Ph.D. in Computer Information Systems, Georgia State University B.S. in Management Information Systems, University of Texas at Austin Alan Yang's scholarly work spans three domains: (1) AI applications in organizational agility and business performance, (2) cybersecurity and education technology integration, and (3) mobile health interventions for chronic care and elderly populations. His 2024-2025 publications address generative AI's strategic implications, explainable AI frameworks, and post-quantum cryptography education. No scientific awards were explicitly mentioned in the provided materials. Alan Yang's research emphasizes both theoretical rigor and practical implementation, with methodological foundations in conceptual modeling, empirical analysis, and human-centered design principles.
Professor David Foxcroft is a Professor of Community Psychology and Public Health at Oxford Brookes University's School of Psychology, Social Work and Public Health. He has previously held positions at the Universities of Portsmouth and Southampton, and managed an NHS R&D Support Unit. His research focuses on understanding and improving behavior in context, particularly how social structures (families, schools, communities, employers, regulation, government) can support improved health and wellbeing in populations. PhD in Psychology from Hull University PGDip in Evidence-Based Health Care from Oxford University BSc in Psychology from Hull University Professor Foxcroft specializes in prevention science with particular expertise in: Substance misuse prevention Behavioral health interventions Family and school-based programs Public health policy analysis His recent publications demonstrate a strong focus on adolescent health behaviors, alcohol misuse prevention, and evaluation of complex social interventions. Current research projects include: NIHR-funded Steps Towards Alcohol Misuse Prevention Programme (STAMPP) MRC-funded Strengthening Families Programme (SFP Cymru) in Wales Good Behaviour Game impact evaluation Global Drug Survey alcohol message comparisons He supervises PhD students in behavioral health and prevention science, and teaches across Psychology and Public Health programs at undergraduate, postgraduate, and doctoral levels. Professor Foxcroft also leads modules in evidence-based prevention, experimental statistics, and systematic review methodology.
