جست‌وجوی استاد و پژوهشگر

• Probability Theory
• Stochastic Processes
• Mathematical Biology
• +۵ مورد دیگر

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.

Tim Janssenمشاهده پروفایل

استادیار

• Substance Use Initiation
• Adolescent and Young Adult Behavioral Health
• Momentary Assessment Methods
• +۴ مورد دیگر

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.

• Statistical Physics
• Complex Systems
• Mathematical Physics
• +۵ مورد دیگر

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.

Cassandra Pattinsonمشاهده پروفایل

پژوهشگر ارشد

• Sleep Research
• Circadian Rhythms
• Child Health
• +۴ مورد دیگر

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 Chenمشاهده پروفایل

استاد

• Machine Learning
• High-Dimensional Estimation
• Nonconvex Optimization
• +۹ مورد دیگر

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 .

• Pain Medicine
• Radiculopathy
• Neurosciences
• +۵ مورد دیگر

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 Witteمشاهده پروفایل

استاد

• Suicidal Behavior
• Clinical Psychology
• Psychopathology
• +۱۲ مورد دیگر

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.

• Probability theory and stochastic processes
• Random differential equations
• Uncertainty quantification
• +۶ مورد دیگر

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 Colderمشاهده پروفایل

استاد

• Developmental Psychology
• Adolescent Substance Use
• Child and Adolescent Aggression
• +۸ مورد دیگر

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 Yangمشاهده پروفایل

استادیار

• Mobile Computing
• Healthcare Information Systems
• Incentive Design for Health Behaviors
• +۳ مورد دیگر

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.

David Foxcroftمشاهده پروفایل

استاد

• Behavioral Health
• Prevention Science
• Public Health
• +۲ مورد دیگر

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.

Alexander Heinleinمشاهده پروفایل

استادیار

• Numerical methods for partial differential equations
• Scientific computing
• Domain decomposition methods
• +۶ مورد دیگر

Dr. Alexander Heinlein is an Assistant Professor in the Numerical Analysis group at the Delft Institute of Applied Mathematics (DIAM), Faculty of Electrical Engineering, Mathematics & Computer Science (EEMCS), Delft University of Technology (TU Delft). His work bridges scientific computing and machine learning through scientific machine learning (SciML) , focusing on domain decomposition methods and multiscale approaches for solving complex partial differential equations on modern hardware like GPUs. Research interests include: Developing high-performance computing algorithms for nonlinear PDEs with applications in fluid-structure interaction and photonic crystals Advancing physics-aware machine learning techniques for groundwater heat transport and post-burn contraction prediction Creating parallel preconditioners like FROSch for challenging problems in computational mechanics Building hybrid numerical-ML frameworks with domain decomposition for multi-physics applications His recent publications highlight a 128-235x speedup in biomedical simulations through deep operator networks , and keynote presentations on geometric challenges in machine learning-based surrogate models at international conferences like CASML 2024. Scientific awards include: 2025 NWO Open Technology Programme grant for the RAPID-Wind project on offshore wind turbine foundations Students and collaborations involve: Yuhuang Meng (PhD candidate, 2024) Jing Zhao (co-supervisor) Prof. Jun Zou (Chinese University of Hong Kong collaboration, 2024) He leads software development for COMSOL and Trilinos extensions while maintaining open-source reproducibility standards.

• Computational Mechanics
• Machine Learning
• Inverse Problems
• +۷ مورد دیگر

Assad Anshuman Oberai is a Professor at the University of Southern California's Viterbi School of Engineering . His research spans computational mechanics, inverse problems, and machine learning applications in nuclear engineering and biomedical imaging. Key Research Areas: Multi-fidelity modeling, Bayesian inference in mechanics, conditional GANs for posterior estimation, ultrasonic sensing of nuclear fuel canisters, mechano-microscopy for tumor elasticity imaging Methodological Contributions: Novel operator network architectures, dimension-reduced Bayesian frameworks, active noise cancellation techniques, and error estimation in variational multiscale methods Recent work focuses on non-invasive nuclear fuel inspection using ultrasonic sensing and machine learning, achieving significant signal-to-noise ratio improvements with active noise cancellation. In biomedical domains, his team develops cGAN-enhanced elasticity imaging for cancer differentiation, outperforming traditional algebraic methods. Methodologically, he pioneered VarMiON (Variationally Mimetic Operator Networks) with rigorous error analysis, demonstrating superior performance over DeepONet in partial differential equation approximations. His publications address high-dimensional inverse problems through generative models, with applications in epidemic modeling (capturing algebraic decay via behavioral feedback), 3D traction microscopy accounting for cell-induced matrix degradation, and compressible phase change simulations using discontinuous finite element methods. Co-authors include researchers from mechanical engineering, biomedical informatics, and nuclear safety domains.

Ivan Papićمشاهده پروفایل

استادیار

• Diffusions and fractional diffusions
• Time-changed stochastic models
• Applied probability
• +۵ مورد دیگر

Ivan Papić is an Assistant Professor at the School of Applied Mathematics and Informatics , affiliated with the Josip Juraj Strossmayer University of Osijek . His research focuses on stochastic processes, particularly fractional diffusions , non-stationary models , and long-range dependence . PhD in Mathematics (2019, University of Zagreb) MSc in Financial and Business Mathematics (2013, University of Osijek) MSc in Mathematics and Computer Science Education (2020, University of Osijek) BSc in Mathematics (2011, University of Osijek) His work bridges applied probability and statistical modeling , with applications in epidemiology (e.g., modeling SARS-CoV-2 spread via stochastic SEIR models) and mathematical finance. Recent publications explore advanced diffusion models like stretched non-local Pearson diffusions and fractional Bessel processes . Projects such as Scaling in stochastic models (2023–2027) and Stochastic models with long-range dependence highlight his expertise. He actively participates in international conferences, including the 9th European Congress of Mathematics (2024), and serves as Erasmus coordinator for MATHOS since 2024. Teaching responsibilities include courses like Stochastic Processes I , Applied Statistics , and Bayesian Statistics at the University of Osijek, with a focus on interdisciplinary applications across departments such as Mathematics, Physics, and Civil Engineering.

• Statistical Modeling
• Longitudinal Data Analysis
• Intervention Evaluation
• +۴ مورد دیگر

Prof. Dr. Axel Mayer is a Professor of Psychological Methods and Evaluation at the Faculty of Psychology and Sports Science, University of Bielefeld. His research focuses on advanced statistical modeling for longitudinal data, causal mediation analysis, and developing user-friendly statistical software packages like lsttheory and EffectLiteR . He investigates intervention effectiveness in psychotherapy and health contexts, particularly fatigue in students and cancer survivors, and contributes to latent state-trait models for experience sampling data. Methodological Expertise: Latent growth curve modeling, causal mediation, structural equation modeling Applied Research: Health-related quality of life, educational development, stress response validation Key projects include involvement in the interdisciplinary InChangE initiative studying individualization processes across disciplines, and contributions to the Deutsche Hodgkin-Studiengruppe cancer fatigue research. His recent publications emphasize software tutorials and comparative studies in mental health, education, and public health interventions. Current trends show focus on digital mental health interventions , cross-cultural comparisons , and ecological momentary assessment methodologies . He actively develops R packages for advanced statistical techniques and investigates mediators in clustered trial designs. Axel Mayer serves as Pro-Dean for Research and chairs committees at Bielefeld University. He's President of the European Association of Methodology (2018-2021) and member of the Psychometric Society.