جست‌وجوی استاد و پژوهشگر

Fabio Pusateriمشاهده پروفایل

دانشیار

• Partial Differential Equations
• Dispersive and Wave Equations
• Fluid Dynamics
• +۲ مورد دیگر

Fabio Pusateri is an Associate Professor in the Department of Mathematics at the University of Toronto , holding a faculty position since 2022. He previously served as an Assistant Professor at the University of Toronto (2018-2022) and Princeton University (2014-2018), following postdoctoral work at Princeton (2011-2014). His research focuses on Nonlinear Partial Differential Equations , with specialized studies in Dispersive and Wave Equations , Fluid Dynamics , and Harmonic Analysis . Education : PhD in Mathematics from New York University (2011), MSc from Università Roma Tre (2006) Awards : Coxeter-James Prize (2022), Antonio Ambrosetti Medal (2021), ISAAC Award (2019) Research Contributions : Pioneering work on global existence and stability for water wave systems, radiation damping in Klein-Gordon equations, and wave turbulence theory. His research extends to quantum propagation speeds and nonlinear Schrödinger equations with potentials. Grants : NSERC Grant (2018-2025), NSF Grant (2013-2017), Simons Fellowship (2011-2014) Leadership : Co-organizer of the Fields Colloquium in Applied Mathematics and editor for Nonlinear Analysis .

Daniel E. Fordمشاهده پروفایل

استاد

• Coronary artery disease
• Epidemiology
• Depression
• +۷ مورد دیگر

Daniel E. Ford is a Professor of Medicine at Johns Hopkins University School of Medicine with joint appointments in Psychiatry and Behavioral Sciences, and at the Johns Hopkins Bloomberg School of Public Health in Health Policy and Management and Epidemiology. He serves as Director of the Johns Hopkins Institute for Clinical and Translational Research and Senior Associate Dean for Clinical and Translational Research at the Johns Hopkins School of Medicine. Dr. Ford received his MD from State University of New York at Buffalo in 1982 and has been on the Johns Hopkins faculty since then, except for a brief period as a National Institutes of Health fellow. He earned his Master's in Public Health from the Bloomberg School in 1986. He has published more than 120 research papers and book chapters and served as associate editor of the Journal of General Internal Medicine. Dr. Ford is widely regarded as a pioneer in research on the interrelationships between mental disorders and chronic medical conditions. His research interests focus on depression and coronary artery disease, improving care for patients with medical comorbidity, and exploring how information technology can be used to improve care for patients with depression and tobacco abuse. He was one of the first investigators to document depression as a risk factor for myocardial infarction and stroke. His work includes developing web-assisted interventions for tobacco cessation and studying seasonal patterns in mental health information seeking. His research demonstrates strong interdisciplinary connections between mental health, cardiology, epidemiology, and digital health technologies. The publications show a consistent focus on translating research findings into practical clinical applications, particularly through information technology solutions. His work spans clinical trials, epidemiological studies, implementation science, and digital health innovation. David M. Levine Professor of Medicine (2005) Dr. Ford has been instrumental in developing clinical research infrastructure at Johns Hopkins, working closely with personnel who developed e-IRB, an electronic process for submitting research proposals to the Institutional Review Board. He has been principal researcher on a large training grant to develop researchers in general internal medicine and was chosen by the Robert Wood Johnson Foundation to direct the evaluation of its $12 million Depression in Primary Care Initiative. He advocates treating human research subjects as partners in the research process. His laboratory research focuses on understanding relationships between depression and various chronic medical conditions, with recent emphasis on depression and coronary artery disease. The Ford Lab explores how information technology can be used to improve care for patients with depression and tobacco abuse, with interest in moving these interventions into the commercial world.

Yulong Liمشاهده پروفایل

استادیار

• Fractional Calculus
• Fractional Differential Equations
• Fractional Sobolev Spaces
• +۷ مورد دیگر

Yulong Li is an Assistant Professor in the Department of Mathematics at the University of Dayton, part of the College of Arts and Sciences. He is a full-time faculty member with a strong research focus in mathematical analysis, particularly in fractional calculus and related differential equations. His academic journey includes a Ph.D. from the University of Wyoming, postdoctoral experience at the University of Nevada, Reno, and a research fellowship at the Singapore University of Technology and Design. Ph.D., Mathematics, University of Wyoming, 2019 M.S., Mathematical Physics, Capital Normal University, 2015 B.A., Mathematics and Applied Mathematics, Jilin Normal University, 2012 Dr. Li's research centers on fractional calculus , fractional differential equations , fractional Sobolev spaces , singular integral equations , and special functions . His work explores the theoretical foundations of nonlocal operators, boundary value problems, and spectral properties of fractional elliptic equations. He investigates regularity, existence, and uniqueness of solutions in fractional settings, contributing to both pure and applied mathematical analysis. The trend in his recent publications (2019–2025) shows a consistent focus on analytical and functional aspects of fractional diffusion, advection-reaction equations, and nonlocal elliptic operators. His articles frequently appear in specialized journals such as Fractional Calculus and Applied Analysis and Communications on Pure and Applied Analysis , emphasizing rigorous mathematical proofs, integral representations, and spectral analysis. Topics include maximum principles, eigenvalue problems, and solution decomposition in fractional frameworks. Although no scientific awards are mentioned in the provided text, his publication record indicates active scholarly contributions. There is no information available about grants or student advising in the current materials. Dr. Li has been involved in research collaborations, notably with V. Ginting and others, focusing on computational and theoretical aspects of fractional equations. His work bridges abstract analysis with potential applications in physics and engineering, particularly in modeling anomalous diffusion processes.

Brenda Gannonمشاهده پروفایل

استاد

• Health Economics
• Economics of Ageing
• Dementia Research
• +۱۱ مورد دیگر

Professor Brenda Gannon is an international interdisciplinary leader in health economics and social care systems at the University of Queensland. She holds a primary appointment as Professor in the School of Economics within the Faculty of Business, Economics and Law, and is also an Affiliate Professor at the Mater Research Institute and affiliate of multiple health research centers including the Queensland Digital Health Centre and the Centre for Hearing Research. Her work bridges economics, medicine, and social science to develop evidence-based solutions for health systems globally. Professor Gannon's research spans several interconnected domains: health economics of aging and dementia care, mental health services, health equity analysis, and economic evaluations of healthcare interventions across the lifespan from newborns to older adults. Her work particularly focuses on cognitive impairment, physical activity investments, consumer-directed care models, and the social determinants of health. She employs sophisticated econometric methods to analyze big data and test causal hypotheses in healthcare utilization and outcomes. Her 15 most recent publications (2022-2025) demonstrate a strong focus on health equity, cost-effectiveness analyses, and interventions across diverse populations. Her research spans pediatric critical care, women's reproductive health, dementia care, heart failure management, and perinatal mental health. A notable pattern is her application of health economics principles to evaluate interventions across the lifespan, with particular emphasis on vulnerable populations and health disparities. Fellow of the Queensland Academy of Arts and Sciences (2023) Council Member of Queensland Academy of Arts and Sciences (since 2024) Award-winning HDR supervisor with successful mentorship of students into academia and industry Professor Gannon has supervised multiple PhD students as principal and associate advisor, with completed theses focusing on applied health economics, aging, and microeconometrics. Her current research is supported by significant grants from the Australian Research Council, National Health and Medical Research Council, Medical Research Future Fund, EU Horizon 2020, and other international funding bodies. She serves on the International Health Economics Association Student Prize Committee (2025-28) and has advised government at senior levels, including serving on the Medical Services Advisory Committee Evaluation Sub-Committee (2017-2021). As Health Economics and Epidemiology lead for the Queensland Family Cohort Study and member of the QFC Governance Committee, she contributes to major population health initiatives. Her work with clinicians on trials for newborns and interventions for dementia care demonstrates her commitment to translational research that bridges academic findings with practical healthcare applications.

Harry Lahrmannمشاهده پروفایل

دانشیار

• Traffic and Transportation
• Bicycle Traffic
• Traffic Safety
• +۵ مورد دیگر

Harry Lahrmann is an Associate Professor and Research Group Leader at the Department of Construction, Urban and Environmental Engineering within Aalborg University's Faculty of Engineering and Science. He specializes in traffic safety research with a focus on cyclist-pedestrian interactions, vehicle inspection systems, and urban mobility solutions. Key Research Areas: Bicycle traffic, road safety analysis, traffic engineering, and data-driven transportation policy Recent Work Trends: Utilizes ambulance data and self-reporting mechanisms to identify hazardous road locations; investigates impact of vehicle inspection programs and cycling safety technologies Awards: 1994 - First prize in bicycle safety at intersections Advising & Grants: Supervises PhD students and secures funding from institutions like TrygFonden for projects such as "Better Data on Traffic Accidents." Labs & Teams: Leads the Traffic Research Group, collaborating with experts in infrastructure, hydraulic engineering, and environmental technology.

Pierre Nyquistمشاهده پروفایل

دانشیار

• Probability Theory
• Mathematical Statistics
• Applied Mathematics
• +۸ مورد دیگر

Pierre Nyquist is an Associate Professor and docent in the Department of Mathematical Sciences at Chalmers University of Technology and Gothenburg University. His research is sponsored by the Swedish Research Council, the Swedish e-science Research Center (SeRC), and the Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP). He is also an elected member of the Young Academy of Sweden for the period 2024-2029 and has served as a scientific ambassador for EURANDOM since November 2021. Dr. Nyquist's research interests lie at the intersection of probability theory, mathematical statistics, and applied mathematics. His main expertise is in probability theory, with a focus on large deviations theory and stochastic numerical methods. He has a general interest in all aspects of probability theory and much of what is categorized as applied mathematics, particularly questions related to partial differential equations, optimization, and stochastic optimal control. Recently, he has become increasingly interested in the mathematical foundations of complex data analysis and modeling, and the interplay with ideas from physics. His current research interests include large deviations, gradient flows and their generalizations, stochastic numerical methods, statistical learning theory, stochastic processes, and random dynamical systems. Pierre Nyquist has received research funding from several prestigious sources including the Swedish Research Council, the Swedish e-science Research Center (SeRC), and the Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP). His publications demonstrate a consistent focus on theoretical aspects of probability with applications to computational methods and data analysis, showing increasing integration with machine learning techniques in recent years. elected member of the Young Academy of Sweden (2024-2029) scientific ambassador for EURANDOM (since November 2021) Dr. Nyquist is actively involved in mentoring the next generation of researchers. He currently supervises several PhD students including Cinja Arndt (starting Aug. 2025), Niki Wilhemlson (started Aug. 2024), and Viktor Nilsson (started Aug. 2020). He has previously supervised successful PhD students such as Federica Milinanni (Aug. 2020-May 2025) and Carl Ringqvist (Aug 2015-June 2021). He regularly teaches graduate-level courses including "Modern methods of statistical learning" and has supervised numerous MSc theses on topics ranging from deep learning for time-series radar signals to neural network embedding in insurance pricing. His research group is active in both theoretical developments and practical applications, with current projects spanning from mathematical foundations of probability to applications in machine learning and data science. Dr. Nyquist maintains strong international collaborations, as evidenced by his frequent travel for conferences and research visits to institutions such as Brown University and TU Delft.

Simone Brugiapagliaمشاهده پروفایل

دانشیار

• Mathematics of Data Science
• Computational Mathematics
• Numerical Analysis
• +۵ مورد دیگر

Simone Brugiapaglia is an Associate Professor in the Department of Mathematics and Statistics at Concordia University in Montréal, Canada. His academic journey includes a PhD in Mathematical Models and Methods from Polytechnic University of Milan (2016), an MSc in Mathematics from University of Pisa (2012), and a BSc in Mathematics from University of Pisa (2010), all earned cum laude . Prior to his current role, he held postdoctoral positions at École polytechnique fédérale de Lausanne (2016) and Simon Fraser University (2016-2019). Dr. Brugiapaglia's research bridges mathematics, data science, and computational methods. Key interests include: Foundations of deep learning and neural networks Compressed sensing and sparse recovery algorithms High-dimensional approximation theory Numerical methods for PDEs and diffusion equations Physics-informed machine learning Optimization techniques for large-scale problems His work develops rigorous mathematical frameworks for data-driven algorithms. His publications (30+ including two books) consistently focus on high-dimensional computation , featuring recent advances in neural network theory (e.g., generalization bounds, rank collapse), compressed sensing techniques (e.g., greedy algorithms, unrolled networks), and physics-informed learning. A strong trend involves combining traditional numerical methods with deep learning for PDE solutions. Awards & Fellowships: Concordia Research Fellow (2023) Leslie Fox Prize for Numerical Analysis (2nd place, 2019) PIMS Postdoctoral Fellowship (2016-2018) Multiple INdAM scholarships during graduate/undergraduate studies He has supervised over 20 trainees across postdoctoral, graduate, and undergraduate levels. While specific grants aren't detailed, his fellowship history indicates sustained research funding. No explicit research labs or teams are mentioned, but his supervision record and collaborative publications suggest active leadership in research groups focused on computational mathematics.

• Nonlinear Dynamics
• Structural Dynamics
• System Identification
• +۳ مورد دیگر

Dario Anastasio is a Fixed-term Assistant Professor in the Department of Mechanical and Aerospace Engineering (DIMEAS) at Politecnico di Torino. He is affiliated with the College of Mechanical, Aerospace, and Automotive Engineering and actively contributes to both teaching and research activities in mechanical engineering. Dr. Anastasio's research focuses on several key areas within mechanical engineering and dynamics. His primary interests include: Nonlinear dynamics and structural dynamics System identification and modal analysis Energy harvesting, particularly vibration energy harvesting Dynamics of mechanical systems with nonlinear characteristics Pantograph-catenary dynamic interaction in railway systems His work spans both theoretical modeling and experimental validation, with particular emphasis on negative stiffness oscillators, railway contact line dynamics, and nonlinear system identification techniques. Dr. Anastasio applies advanced methodologies including subspace identification, Bayesian model selection, and signal processing to solve complex mechanical engineering problems related to vibration analysis and structural dynamics. Analysis of Dr. Anastasio's publications reveals a strong focus on nonlinear dynamics, particularly in mechanical systems with complex behaviors. His research consistently bridges theoretical modeling with experimental validation across multiple domains including railway systems, energy harvesting devices, and nonlinear oscillators. The publications demonstrate progression from fundamental nonlinear dynamics research toward practical applications in railway engineering and vibration-based energy harvesting systems. Dr. Anastasio has received notable recognition for his work: Quality Award 2019 conferred by Politecnico di Torino, Italy (2020) Dr. Anastasio actively contributes to the academic community through extensive teaching activities across multiple programs. He serves as a Teaching Assistant for "Dynamics and Identification of Nonlinear Systems" and as a Course Collaborator for "Dynamics of Mechanical Systems" and "Vibration Mechanics" at both Master's and Bachelor's levels. His teaching spans from 2019/20 through the upcoming 2025/26 academic year, demonstrating his ongoing commitment to mechanical engineering education. Additionally, he contributes to PhD-level instruction in "Rotordynamics of High-Speed Rotating Machinery." Dr. Anastasio is a key member of the "Dynamics of mechanical systems and identification" research group within DIMEAS. His research integrates multiple ERC sectors including Mechanical and manufacturing engineering, ODE and dynamical systems, Signal processing, and Simulation engineering and modelling. His work aligns with Sustainable Development Goals 7 (Affordable and clean energy) and 9 (Industry, Innovation, and Infrastructure).

Patrick Le Tallecمشاهده پروفایل

استاد

• Computational Mechanics
• Nonlinear Mechanics
• Domain Decomposition Methods
• +۵ مورد دیگر

Patrick Le Tallec is a Professor of Mechanics at École Polytechnique in France, where he currently serves as Dean of the Bachelor Program and is a member of the M3DISIM project. His distinguished academic career spans multiple institutions including Université Paris Dauphine, INRIA (French National Institute for Research in Digital Science and Technology), and international universities such as Stanford University, University of Wisconsin, and Shanghai Jiao Tong University. He has held leadership positions including Vice President for Education and Head of the Laboratory of Solid Mechanics at École Polytechnique. His educational background includes: Graduate from École Polytechnique Ph.D. in Engineering Mechanics from The University of Texas at Austin (1980) Thèse d'Etat in Applied Mathematics from Université Pierre et Marie Curie in Paris (1981) Professor Le Tallec's research focuses on computational mechanics and applied mathematics with expertise in nonlinear mechanics, domain decomposition methods, and multiscale modeling. His work bridges theoretical mathematics with practical engineering applications, particularly in material science and fluid-structure interactions. He has developed advanced numerical methods for elasticity, viscoelasticity, and fluid dynamics with applications in industrial manufacturing and biomedical engineering. His recent publications demonstrate progression from foundational numerical methods to sophisticated multiscale approaches addressing complex engineering challenges in material science. The research shows particular emphasis on rubber mechanics, fatigue analysis, and computational methods for nonlinear structures, reflecting his ongoing commitment to solving real-world engineering problems through mathematical innovation. His scientific honors include: CISI award in Scientific Computing Prize Blaise Pascal of the French Academy of Sciences Chevalier des Palmes Académiques Chevalier de la Légion d'Honneur Officier de l'Ordre National du Mérite Professor Le Tallec has directed over 40 Ph.D. students from 10 different nationalities, demonstrating significant impact in academic mentoring. His research has been supported through extensive collaborations with industrial partners including Michelin, PSA Group, and Dassault Aviation, as well as scientific advisory roles at the French Alternative Energies and Atomic Energy Commission. He has served as president of the French Society of Applied and Industrial Mathematics and held editorial positions with leading journals in his field. His laboratory work centers around computational mechanics research, particularly through the M3DISIM project at École Polytechnique. His research team brings together mathematicians, engineers, and computer scientists to develop innovative solutions for complex problems in material science and structural mechanics, with applications ranging from industrial tire manufacturing to biomedical engineering.

• Electronic Design Automation (EDA)
• Analog/RF Circuit Simulation
• Multi-physics Analysis
• +۲ مورد دیگر

Dr. QUAN Chen is an Associate Professor at the School of Microelectronics, Southern University of Science and Technology (SUSTech), holding this position since May 2025 after serving as Assistant Professor (2019-2025) and Research Assistant Professor at the University of Hong Kong (2012-2018). A Shenzhen high-level overseas talent, he earned his PhD from the University of Hong Kong and conducts cutting-edge research in electronic design automation. His academic credentials include: Ph.D. from The University of Hong Kong (2010) Master's degree from The University of Hong Kong (2007) Bachelor's degree from Sun Yat-Sen University (2005) Dr. Chen's research pioneers advanced EDA algorithms for large-scale analog/RF circuit simulation, post-Moore multi-physics analysis, and AI-assisted design technologies. His work addresses critical challenges in nanodevice modeling and quantum computing circuits, resulting in over 50 publications in top venues like IEEE TCAD and DAC, plus four Chinese patents. Analysis of his recent publications reveals dominant trends in exponential integrator methods for transient simulation, model order reduction techniques, and physics-informed machine learning for reliability analysis. His work bridges numerical mathematics with practical EDA applications across analog circuits, quantum hardware, and emerging memory technologies. Key recognitions include: Wu Wenjun Artificial Intelligence Science and Technology Award, Second Prize (2020) ICCAD Best Paper Award Nomination (2012) Dr. Chen actively recruits Postdoctoral Fellows, Research Assistants, and Graduate Students while leading major funded projects including NSFC key/general programs and Guangdong Provincial R&D initiatives. His industry partnerships with Huawei, Empyrean, and Guowei Group translate theoretical advances into real-world EDA solutions. He directs a specialized research group at SUSTech focused on computational methods for next-generation circuit design, fostering innovation in simulation algorithms and multi-physics analysis through academic-industry collaboration.

• Structural Mechanics
• Nonlinear Dynamics
• Finite Element Analysis
• +۲ مورد دیگر

Dr. NÉMETH Róbert is an Associate Professor and Head of the Department of Structural Mechanics at the Budapest University of Technology and Economics . With a PhD in Civil Engineering (2004), he has contributed significantly to nonlinear structural mechanics, particularly in elastic rod analysis and finite element modeling. Current roles: Associate Professor, Department Head Key affiliations: Budapest University of Technology and Economics, Cornell University (visiting scientist) His research focuses on nonlinear dynamics of elastic systems, with applications to: Nonlinear normal modes Free vibration analysis Seismic response of masonry structures Elastic filament networks Continuum mechanics Finite element modeling Article trends show a consistent exploration of piecewise linear systems and cracked structures across decades, combining analytical and numerical approaches. Scientific awards include: DAAD Scholarships (1999, 2001) Dr. Imre Korányi Civil Engineering Scholarship (2004-2005) He has taught courses in structural dynamics, finite element methods, and mechanics in Hungarian, German, and English, while also serving on university committees.

Jessica Linمشاهده پروفایل

دانشیار

• Partial Differential Equations
• Probability Theory
• Stochastic Homogenization
• +۳ مورد دیگر

Jessica Lin is an Associate Professor in the Department of Mathematics and Statistics at McGill University, holding the Canada Research Chair in Partial Differential Equations and Probability (Tier 2). She specializes in stochastic homogenization, elliptic and parabolic equations, and reaction-diffusion systems. Prior to McGill, she was a Van Vleck Visiting Assistant Professor at the University of Wisconsin-Madison, and earned her Ph.D. from the University of Chicago in 2014 with undergraduate studies at NYU. Her research focuses on partial differential equations and probability, particularly in nonlinear phenomena, stochastic processes, and their applications to mathematical physics and materials science. Key areas include front propagation in stochastic environments, nondivergence form equations, and phase transition models in periodic media. Dr. Lin has contributed to foundational work on quantitative homogenization estimates for elliptic and parabolic equations, asymmetric cooperative motion, and barycentric Brownian systems. Her recent articles explore generalized front propagation, anisotropic surface tensions, and KPZ universality in random growth models. She has been recognized with the Canada Research Chair (Tier 2), and her work spans over 15 peer-reviewed articles since 2013. Her research combines analytical techniques with probabilistic methods, addressing multiscale problems in applied mathematics.

Siegfried Beckusمشاهده پروفایل

مدرس ارشد

• Spectral Theory
• Dynamical Systems
• Operator Algebras
• +۶ مورد دیگر

Siegfried Beckus is a Senior Lecturer and Researcher at the Institute of Mathematics , University of Potsdam, Germany, since 2020. His work focuses on spectral theory of Schrödinger operators on graphs with aperiodic ordered potentials, dynamical systems , and operator algebras . He has also contributed to the study of Delone sets , graph limits , and aperiodic tilings . Education : PhD in Mathematics (2016) and Diploma (2012) from Friedrich Schiller University Jena, Germany. Research Interests : Spectral theory of quantum systems, aperiodic order, groupoids, C*-algebras, and applications to quasicrystals. His recent publications address operator families defined by dynamical systems , Sturmian Hamiltonians , and symbolic substitution systems on non-abelian groups. These works establish spectral continuity , Lipschitz/Hölder estimates , and periodic approximation techniques . Scientific Awards include Postdoctoral Fellowships at Technion (Haifa) and Research in Pairs scholarships at Oberwolfach. He has supervised several theses on topics like non-Euclidean estimates , Delone dynamical systems , and primitive substitutions .

• Multiphase flow in porous media
• Flow in petroleum reservoirs
• Reservoir/aquifer characterization
• +۵ مورد دیگر

Prof. Avinoam Rabinovich is a faculty member at the School of Mechanical Engineering within The Fleischman Faculty of Engineering at Tel Aviv University. His research focuses on flow phenomena in subsurface formations, particularly related to oil and gas reservoirs, groundwater systems, and CO 2 storage in saline aquifers. His educational background includes dual B.Sc. degrees in Mathematics and Geophysics and Planetary Sciences (both Magna Cum Laude) from Tel Aviv University (2003-2007), followed by an M.Sc. in Geophysics (Magna Cum Laude) with a thesis on "Vorticity inversion and action-at-a-distance in stably stratified shear flow instability" (2007-2009), and a Ph.D. in Mechanical Engineering with research on "Heat and mass flow in heterogeneous media - characterization and effective properties" (2010-2014). Prof. Rabinovich's research interests span multiple areas of subsurface flow physics. His work primarily investigates multiphase flow in porous media , with specific focus on effective properties , upscaling for numerical flow simulations , core characterization , capillary heterogeneity effects , and oscillatory flow . His research approach is predominantly theoretical but incorporates experimental data analysis, with emphasis on developing practical tools for engineers while advancing fundamental understanding of flow mechanics. His publication record demonstrates consistent contributions to understanding subsurface flow phenomena, particularly in the areas of CO 2 storage modeling, effective properties in heterogeneous media, and oscillatory flow applications. His work bridges theoretical fluid mechanics with practical petroleum engineering and environmental applications, showing particular expertise in analytical solutions and upscaling techniques for complex flow scenarios. Prof. Rabinovich teaches graduate-level courses at Tel Aviv University including "Flow in Oil and Natural Gas Reservoirs" and "Reservoir Engineering - Basics of Natural Gas and Oil Production," contributing to the education of future engineers in this specialized field.

Jos Kraalمشاهده پروفایل

استادیار

• Health Technology
• Behavioral Health
• Public Health
• +۴ مورد دیگر

Dr. Jos Kraal is an Assistant Professor in the Department of Human-Centered Design at Delft University of Technology's Faculty of Industrial Design Engineering. His work focuses on developing personalized eHealth interventions to improve health behaviors, particularly for vulnerable populations such as those with lower socioeconomic statuses. He leads projects like CapriXpress , an app supporting cardiac patients during rehabilitation waiting periods, and contributes to the ALIVE initiative, promoting lifestyle changes through interdisciplinary collaboration. Kraal emphasizes user-centered design, advocating for approaches that connect deeply with community needs. He received the 2024 Rehabilitation Year Award for his contributions to cardiac rehabilitation innovation. His research bridges gaps between healthcare, science, and design, ensuring interventions address real-world challenges through participatory methods. Research Interests: Behavioral health, eHealth technology, health disparities, human-centered design, and cardiac rehabilitation. Kraal collaborates with institutions like Medical Delta and Erasmus MC to create inclusive solutions. His projects prioritize personalized approaches, such as community engagement through participatory design, ensuring interventions resonate with target demographics. Awards: Rehabilitation Year Award 2024, Dutch Congress of Rehabilitation Medicine Key Contributions: CapriXpress: Tailored eHealth support for cardiac patients during rehabilitation waiting periods. ALIVE: Interdisciplinary program addressing complex health challenges via design-driven solutions. Advocacy for user-centric design in healthcare, emphasizing trust-building and contextual understanding.