جست‌وجوی استاد و پژوهشگر

• Behavioural Science
• Behavioural Economics
• Ethical Decision Making
• +۵ مورد دیگر

Zoe Rahwan is a Research Scientist at the Adaptive Rationality research group of the Max Planck Institute for Human Development in Berlin, a position she has held since 2019. Previously, she served as a Visiting Research Fellow at Harvard Kennedy School (2017-2019) and Research Associate at the London School of Economics (2015-2018), with earlier experience as Senior Manager in Economic Research at Dubai Financial Services Authority (2008-2015). Her research spans behavioural science and behavioural economics with concentrated focus on ethical decision-making in AI contexts. She investigates the psychology of honesty, charitable giving, corruption, and deliberate ignorance through field experiments across government, business, and development sectors. Her work includes pioneering serious games like my-goodness.net to study effective altruism obstacles and deep empathy for examining AI-generated disaster imagery's impact on empathy. Recent publications in Nature and Nature Human Behaviour reveal critical insights at the AI-ethics intersection, including dishonesty in human-AI delegation, honesty oath effectiveness, and large language models' influence on collective intelligence. Her methodology consistently employs large-scale field experiments and computational approaches to analyze human behavior under high-stakes conditions. No information on student advising or research grants is available in the provided text. As core member of the Adaptive Rationality research team, she develops innovative experimental tools including mygoodness (studying altruism barriers) and deep empathy (analyzing AI-generated disaster imagery effects). Her work bridges theoretical behavioral research with real-world applications in policy, finance, and humanitarian contexts through government and business field experiments.

• Energy Engineering
• Mechanical Engineering
• Numerical Flow Simulations
• +۴ مورد دیگر

Nhat Nguyen is a Researcher at the Institute for Energy Efficient Buildings and Indoor Climate of RWTH Aachen University . He holds an M.Sc. in Energy Engineering and specializes in optimizing air conditioning systems, machine learning applications for HVAC, and fire safety analysis in complex building geometries. Education: M.Sc. in Energy Engineering (RWTH Aachen University, 2021) Current Role: Research Associate at E.ON Energy Research Center Research Interests : His work combines experimental test benches , numerical flow simulations , and machine learning to advance energy-efficient building systems. Key projects include: Developing a robust evaluation method for smoke extraction systems under uncertain boundary conditions (weather influences) Innovating wet scrubber concepts for enhanced particle removal in ventilation systems Publication Trends : Recent articles focus on fire safety engineering and environmental control systems, emphasizing uncertainty quantification , fluid dynamics , and sustainable HVAC design . Collaborations : Active in international energy cooperation programs, contributing to interdisciplinary research in energy-efficient building technologies.

• Cardiovascular Risk
• Cardiac Magnetic Resonance Imaging
• Pediatric Cardiology
• +۷ مورد دیگر

Liza Toemen is a Researcher at Erasmus MC, affiliated with the Department of Public Health under the Faculty of Medicine. Her work is centered on understanding cardiovascular health in children, with a particular emphasis on structural and functional cardiac changes related to obesity, early-life growth, and ethnic background. Research Interests: Her research spans pediatric cardiology, epidemiology, and medical imaging. She investigates how pericardial adipose tissue, body mass index, and maternal factors during pregnancy influence heart development in school-age children. Using advanced techniques like cardiac magnetic resonance imaging (CMR), she contributes to population-based studies such as the Generation R Study, which tracks health outcomes from fetal life into childhood. Publication Trends: Over the past five years, her publications have focused on cardiac morphology, ethnic disparities in cardiac structure, and the long-term cardiovascular implications of early-life adiposity and maternal metabolic conditions. These works appear in high-impact journals such as European Heart Journal Cardiovascular Imaging and Diabetes Care , reflecting strong interdisciplinary collaboration and clinical relevance. No scientific awards mentioned in the provided text. Advising and Grants: There is no mention of students advised or grants received in the available information. However, her involvement in large-scale cohort studies suggests participation in major funded research initiatives, though specific details are not provided. Labs and Teams: While no specific lab or team name is mentioned, her research is embedded within the Generation R Study and involves collaboration with leading experts in pediatric cardiology and public health at Erasmus MC.

• Radioecology
• Environmental Radiochemistry
• Actinide Chemistry
• +۴ مورد دیگر

Dr. Susanne Sachs serves as Head of the Plants and Rhizosphere research group at Helmholtz Centre Dresden-Rossendorf (HZDR), within the Institute of Resource Ecology's Department of Radiation Research on Biological Systems. With over 25 years of continuous research at HZDR since 1996, she leads investigations into actinide-biological system interactions and radionuclide migration in geological environments. Her academic foundation includes: Diploma in Chemistry from TU Bergakademie Freiberg (1988-1993) PhD jointly awarded by Forschungszentrum Rossendorf (HZDR) and Technische Universität Dresden (1993-1997) Dr. Sachs' research centers on radioecology and environmental radiochemistry, specializing in actinide interactions with humic substances and biological systems including plants, mammalian cells, and diatoms. Her work examines radionuclide transport mechanisms in geological systems, plant uptake pathways under varying environmental conditions, and toxicity mechanisms at cellular levels. Employing advanced techniques like time-resolved laser fluorescence spectroscopy, micro-XANES, and microcalorimetry, she investigates speciation, binding mechanisms, and metabolic impacts of uranium, europium, and other actinides/lanthanides. Analysis of her 15 most recent publications reveals evolving research trends: increasing focus on plant-based model systems (tobacco BY-2 cells, Brassica napus, Daucus carota), expansion into microbial community interactions, and methodological shifts toward multi-omics and in situ spectroscopic approaches. Her work consistently bridges fundamental molecular-scale chemistry with real-world applications in nuclear waste disposal safety and radiation protection policy. As principal investigator for major international projects including TRAVARIS (BMBF, 2022-2026), RadoNorm (EC, 2020-2025), and TRANS-LARA (BMBF, 2017-2021), she secures substantial research funding focused on radionuclide transfer in vadose zones, radiation protection frameworks, and climate change impacts on contaminant migration. Her leadership in the European Radioecology Alliance and German Commission on Radiological Protection demonstrates significant scientific influence. The Plants and Rhizosphere group operates specialized facilities for plant-radionuclide interaction studies, including controlled-environment growth chambers, advanced spectroscopy labs (TRLFS, ATR-FTIR), and radiochemical handling infrastructure. Current work integrates multi-omics approaches with traditional radiochemical methods to develop predictive models for radionuclide behavior in agricultural and natural ecosystems.

• Cognitive Neurology
• Neural Data Science
• Statistical Computing
• +۵ مورد دیگر

Professor Karsten Mueller is a distinguished researcher in cognitive neurology and neural data science at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany. He holds the position of Associate Professor at Leipzig University's Faculty of Medicine and serves as a faculty member at both the International Max Planck Research School on Neuroscience of Communication (IMPRS NeuroCom) and the International Max Planck Research School on Cognitive NeuroImaging (IMPRS CoNI). Additionally, he has been appointed as a Visiting Professor at the First Faculty of Medicine at Charles University in Prague since 2025. His work focuses on advanced neuroimaging techniques to understand brain structure and function in various neurological conditions. Dr. Mueller received his Dr. habil. degree in Cognitive Neurology from Leipzig University's Faculty of Medicine in 2006, the same year he became a Private lecturer (Privatdozent) at the institution. His academic journey includes a postdoctoral position from 1999 to 2008 at the Department of Cognitive Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, under the supervision of D.Y. von Cramon. In 2015, he was awarded the title of Apl.-Professor (Associate Professor) at Leipzig University, recognizing his significant contributions to the field. Professor Mueller's research spans several critical areas in cognitive neuroscience and neuroimaging. His primary focus is on understanding brain connectivity and structure in neurological disorders, particularly Parkinson's disease, frontotemporal dementia, and the effects of deep brain stimulation. He leads the Methods and Development Group for Neural Data Science and Statistical Computing, where his team develops advanced computational approaches for analyzing complex neuroimaging data. His work bridges clinical neurology with cutting-edge data science, creating innovative methods to extract meaningful insights from brain imaging studies. This interdisciplinary approach has led to significant contributions in understanding how neurological conditions affect brain networks and cognitive functions. Analysis of Professor Mueller's recent publication record reveals a strong emphasis on applying advanced computational and machine learning techniques to neuroimaging data. His research consistently explores the relationship between brain structure/function and various neurological conditions, with particular attention to Parkinson's disease, frontotemporal dementia, and stroke recovery. A notable trend is his increasing use of artificial intelligence and deep learning approaches to improve diagnostic accuracy and understand disease progression. His work also demonstrates a growing interest in connecting peripheral biomarkers (like retinal imaging) with central nervous system changes, suggesting a more holistic approach to understanding neurological disorders. The collaborative nature of his research is evident through numerous international partnerships, particularly with institutions in Prague. Professor Mueller leads the Methods and Development Group for Neural Data Science and Statistical Computing at the Max Planck Institute. This team focuses on developing innovative computational approaches for analyzing complex neuroimaging datasets. Their work encompasses statistical modeling, machine learning applications, and the creation of open-source tools for the neuroscience community. The group collaborates extensively with clinical researchers to translate advanced data analysis techniques into meaningful clinical insights, particularly in the areas of movement disorders, dementia, and brain connectivity research.

Marcell Nikolauszمشاهده پروفایل

پژوهشگر

• Microbial Biotechnology
• Anaerobic Digestion
• Biogas Production
• +۳ مورد دیگر

Dr. Marcell Nikolausz is a Scientist at the Department of Microbial Biotechnology of the Helmholtz Centre for Environmental Research - UFZ in Leipzig, Germany, with additional collaboration through the Deutsches Biomasseforschungszentrum (DBFZ). His career at the UFZ spans over two decades, having served in various departments including Environmental Microbiology and Bioenergy before his current position in Microbial Biotechnology since 2024. Dr. Nikolausz's research focuses on microbial communities in anaerobic systems, particularly examining biomethanation processes, hydrogen utilization, and antimicrobial resistance in biogas production. His work bridges fundamental microbiology with practical applications in renewable energy and waste treatment technologies. He has made significant contributions to understanding the functional dynamics of microbial communities involved in biogas production from various feedstocks, including lignocellulosic biomass and organic waste streams. Analysis of Dr. Nikolausz's recent publications reveals a consistent focus on optimizing biogas production processes through microbial community analysis. His research increasingly addresses the integration of renewable energy systems with biological processes, particularly examining Power-to-X applications and hydrogen-based biomethanation. A notable trend is his investigation into antimicrobial resistance within anaerobic digestion systems, which has important implications for environmental safety and public health. Marie Curie Development Host Fellow (Project: BIOISOTOPE, contract: EVK1-CT-2000-56120) Dr. Nikolausz has established extensive collaborations across European research institutions, contributing to numerous projects focused on sustainable biotechnological solutions. His work on microbial protein production from green hydrogen represents cutting-edge research at the intersection of renewable energy and food security. He has been actively involved in developing innovative reactor designs for biomethanation processes and investigating the microbiological aspects of Power-to-X applications. As a member of the Working Group Microbiology of Anaerobic Systems, Dr. Nikolausz contributes to advancing the scientific understanding of complex microbial communities in biogas production systems. His research team investigates the functional relationships within these communities to optimize process efficiency and stability under varying operational conditions.

Frank Aurzadaمشاهده پروفایل

استاد

• Probability Theory
• Stochastic Processes
• Persistence Probabilities
• +۵ مورد دیگر

Prof. Dr. Frank Aurzada is a Professor of Stochastics at the Department of Mathematics, Darmstadt University of Technology (Technische Universität Darmstadt). He serves as Vice Dean and leads the Stochastics Research Group (Arbeitsgruppe Stochastik). His office is located at Schlossgartenstraße 7, 64289 Darmstadt, Germany, in room S2|15 341. Professor Aurzada's research focuses on probability theory and stochastic processes, with particular expertise in persistence probabilities, fractional Brownian motion, Lévy processes, and Brownian motion. His work often examines first passage problems, asymptotic analysis, and path properties of stochastic processes. He has made significant contributions to understanding the behavior of processes under various constraints and conditions, including conditioned Brownian motion and persistence exponents in diverse settings. His recent publications demonstrate a consistent focus on theoretical aspects of stochastic processes with applications spanning from communication networks to interacting particle systems. The research trends show increasing sophistication in handling complex constraints on stochastic processes and developing perturbation methods for analyzing persistence phenomena. Professor Aurzada has organized numerous academic events, including multiple Spring Schools on specialized topics in probability theory dating back to 2014. His most recent and upcoming events include the Spring School on "Extrema of logarithmically correlated random fields and applications" (March 2025) and the Spring School on "Multiplicative chaos and cascades" (February 2024). For teaching, Professor Aurzada offers courses such as "Statistik I für Cognitive Science und Wirtschaftsingenieurwesen" and "Stochastische Prozesse" for the Winter 2025/2026 semester. His research group actively collaborates with institutions worldwide, including universities in Russia, France, and the United States.

• Educational Psychology
• Development under Risk Conditions
• Achievement Motivation
• +۴ مورد دیگر

Dr. Julia Moeller is a Junior Professor of Educational Psychology with a focus on Development under Risk Conditions at the University of Leipzig, while also covering the Professorship for Educational-Psychological Diagnostics and Differential Psychology at the Faculty of Educational Sciences, University of Erfurt. Her work bridges educational psychology, developmental science, and methodological innovation in studying moment-to-moment processes in learning and development. Dr. Moeller's research focuses on educational psychology and developmental processes with particular emphasis on how students experience motivation and emotions in learning situations. Her work employs innovative methodologies including the Experience Sampling Method (ESM) to capture in-the-moment dynamics of achievement motivation. She has developed the DYNAMICS Framework for studying moment-to-moment development in achievement motivation, which represents a significant contribution to person-oriented research in educational contexts. Analysis of Dr. Moeller's recent publications reveals a strong focus on understanding the complex interplay between motivation, emotions, and learning outcomes in educational settings. Her work increasingly incorporates advanced statistical approaches including network analysis and causal inference methods to examine momentary processes. She has made substantial contributions to understanding student emotions during the COVID-19 pandemic and how boredom relates to creativity in educational contexts. Her research consistently emphasizes the importance of studying psychological processes as they unfold in real-time rather than relying solely on retrospective assessments. Dr. Moeller has been actively involved in methodological advancements in psychological science, particularly advocating for within-person approaches that can capture individualized patterns of motivation and emotion. Her work on the DYNAMICS Framework represents an important step toward more nuanced understanding of how students' motivational experiences vary across different learning situations. She has contributed to practical guidance for implementing the Experience Sampling Method through her accepted paper 'So you want to do ESM? Ten Essential Topics for Implementing the Experience Sampling Method.'

• Climatology
• Climate Change
• Environmental Systems
• +۳ مورد دیگر

Armin Hofmann serves as a Researcher at the Institute of Geography and Geology, University of Würzburg, where he has worked since 2024 as a Scientific Employee in the Climatology group. He is actively engaged in the EFRE-funded project "BigData@Geo 2.0" (2023-2027), which develops AI-driven climate adaptation solutions for Northern Bavarian agriculture through spatially detailed resilience strategies. His academic foundation includes a Master of Science in Mathematics (2020-2024) and Bachelor of Science in Mathematics (2016-2020), both completed at the University of Würzburg. These quantitative skills directly support his current work in environmental data analysis. Hofmann's research centers on climatology and environmental systems, with specialized focus on climate change impacts and adaptation mechanisms. He applies data science and mathematical modeling to translate complex environmental data into actionable agricultural resilience measures, particularly addressing regional challenges in Northern Bavaria—a recognized climate change hotspot. His work in the BigData@Geo 2.0 project exemplifies the integration of artificial intelligence with practical climate adaptation needs for small and medium agricultural enterprises. As a core member of the Climatology research team led by Univ.-Prof. Dr. Heiko Paeth, Hofmann contributes to the institute's dual research foci on Climate and Environmental Systems. His current project develops web-based tools to convert environmental risk data into operationally specific adaptation protocols, directly supporting decision-making in land and forestry management under changing climate conditions.

Yuri Artioliمشاهده پروفایل

پژوهشگر

• Marine Ecosystem Modelling
• Climate Change Impacts
• Ocean Acidification
• +۵ مورد دیگر

Dr Yuri Artioli is a Marine Ecosystem Modeller at Plymouth Marine Laboratory (PML), where he has worked since 2008. His research focuses on developing and applying models to study the impacts of global stressors such as climate change and ocean acidification, as well as direct anthropogenic activities including nutrient pollution, fishery, and aquaculture on marine ecosystems. Since September 2020, he has served as the coordinator of PML's Science to Impact Challenge area 'Understanding and mitigating climate change.' Dr Artioli holds several significant professional roles including Chair of the Marine Biogeochemistry modelling Activity group of the UK National Partnership for Ocean Prediction, Associate editor of Frontiers in Marine Science – global change and the future ocean, and member of the Executive committee of the North East Atlantic hub of the Global Ocean Acidification Observing Network. His research spans from fundamental scientific questions about natural variability and ecosystem resilience to practical applications that inform policy development. He actively works to translate scientific findings into actionable information that supports policymakers, regulators, industry, and society in achieving global environmental goals including the Paris Agreement, Sustainable Development Goals, and the Colombo Declaration. Dr Artioli's publication record demonstrates consistent contributions to understanding marine ecosystem responses to environmental change, with recent work focusing on ocean acidification impacts, climate change effects on primary production, and vulnerability of coastal ecosystems to harmful algal blooms under changing climate conditions. His scientific contributions are recognized through his leadership roles in major international initiatives and his active participation in shaping research directions for ocean acidification monitoring and response strategies across the Northeast Atlantic region. As a Principal Investigator and co-Investigator on multiple UK and EU funded projects, Dr Artioli leads research efforts that combine advanced modeling approaches with observational data to provide comprehensive assessments of marine ecosystem health and vulnerability under changing environmental conditions.

• Biomedical Research
• Cystitis, Interstitial
• Drug Delivery Systems
• +۷ مورد دیگر

Darryl T. Martin is an Assistant Professor in the Department of Urology at the Yale School of Medicine and a member of the Yale Cancer Center. His research focuses on understanding the biological factors and molecular determinants that drive cancer progression and metastasis, particularly in urologic cancers. Dr. Martin is affiliated with the Cancer Signaling Networks program and the Janeway Society at Yale, demonstrating his integration into multiple research communities within the institution. Dr. Martin received his PhD from Memorial University of Newfoundland, where he trained as a cancer molecular biologist studying tumor growth and differentiation under the supervision of Drs. Robert Gendron and Hélène Paradis. He then completed postdoctoral training with Dr. Robert M. Weiss at Yale University School of Medicine, focusing on drug delivery and cancer progression, which laid the foundation for his current research program. Dr. Martin's research program investigates three main areas: defining distant metastasis by elucidating biologic factors and molecular determinants; modulating the tumor microenvironment to transform immunosuppressive conditions into immune-activated states; and enhancing tumor targeting using surface-modified nanoparticles. His work combines molecular biology, translational science, and nanomedicine to develop novel approaches for cancer treatment, with particular emphasis on prostate and bladder cancers. Analysis of Dr. Martin's recent publication record reveals a strong translational focus, bridging basic molecular mechanisms with clinical applications. His work spans genomic testing for prostate cancer, treatment optimization for bladder cancer variants, and nanoparticle-based drug delivery systems, demonstrating both breadth and depth in urologic oncology research. Dr. Martin is an active member of several professional organizations: American Association for Cancer Research (AACR) Society for Basic Urologic Research (SBUR) American Society for Biochemistry and Molecular Biology (ASBMB) The Martin Lab is currently funded by Department of Defense (DoD) and foundation grants, supporting research on cancer progression and metastasis. Dr. Martin collaborates extensively with clinical colleagues at Yale, reflecting the interdisciplinary nature of modern cancer research and his commitment to translating laboratory discoveries into clinical applications. Dr. Martin's laboratory focuses on developing practical applications for cancer treatment, particularly through nanoparticle systems that can deliver drugs to malignant tissues with high specificity. His research represents an important bridge between basic cancer biology and clinical oncology, with potential to improve outcomes for patients with urologic malignancies.

Christian Fiebergمشاهده پروفایل

استاد

• Financial Economics
• Risk Management
• Portfolio Management
• +۵ مورد دیگر

Christian Fieberg serves as a Professor of Data Science at Hochschule Bremen (City University of Applied Sciences) in Bremen, Germany, and holds an Affiliate Professor position at Concordia University in Montreal, Canada. He is actively affiliated with the DTX research cluster within the Faculty of Business and Economics at Hochschule Bremen, where his work bridges theoretical modeling with practical financial applications. Professor Fieberg's research spans financial economics with particular expertise in risk and portfolio management, sustainable investments, and data-intensive financial analysis. His methodological approach integrates advanced statistical techniques, machine learning algorithms, and econometric modeling to address complex financial problems. He specializes in working with large datasets and developing practical software tools that translate research findings into actionable insights for financial practitioners. His publication record reveals a strong focus on market predictability, factor modeling, and cross-sectional analysis across various asset classes. Recent work demonstrates increasing attention to cryptocurrency markets and the application of machine learning techniques to international financial markets. His research consistently appears in top-tier finance journals including the Journal of Finance, Journal of Financial and Quantitative Analysis, and Review of Finance, reflecting both methodological rigor and practical relevance. Top 50 most research-intensive economists under 40 years of age in German-speaking countries (Wirtschaftswoche) Professor Fieberg maintains active collaborations with researchers across international institutions, as evidenced by his co-authored publications with scholars from Concordia University, Montpellier Business School, and the University of Bremen. His work with the DTX research cluster emphasizes innovative research approaches and strong academic-industry networking. His current projects include Bond Factor Prediction (2025-2026) and participation in international workshops such as the STARS EU workshop in Sweden. His laboratory work focuses on developing computational tools for financial analysis using multiple programming environments including Matlab/Octave, R, Stata, Python, and Excel/VBA. The research group maintains active data repositories on Harvard Dataverse for replication purposes, demonstrating commitment to research transparency and reproducibility.