جست‌وجوی استاد و پژوهشگر

Cheuk Wai Taiمشاهده پروفایل

پژوهشگر

• Structure-Property Relationships
• Functional Materials
• Electron Microscopy
• +۶ مورد دیگر

Cheuk Wai Tai is a Senior Staff Researcher at Stockholm University's Department of Environmental and Materials Chemistry since 2009. He manages the transmission electron microscopes and sample preparation equipment at the Electron Microscopy Center and serves as Section Editor for the Journal of Electronic Materials. His work focuses on quantitative structure characterization in functional materials research, particularly within nanoscience and nanotechnology contexts. Education: Ph.D. in Applied Physics, The Hong Kong Polytechnic University, 2004 M.Phil. in Applied Physics, The Hong Kong Polytechnic University, 2001 M.Sc. in Physics, The Chinese University of Hong Kong, 1998 B.Sc. (Hons) in Engineering Physics, The Hong Kong Polytechnic University, 1997 Dip. in Mechanical Engineering (Computer Aided Engineering), Institute of Vocational Education (formerly Haking Wong Technical Institute), Hong Kong, 1992 His research centers on structure-property relationships in functional materials through advanced electron microscopy techniques. Current specializations include Pair Distribution Function (ePDF) & Diffuse Scattering, Energy Materials characterization, and EM sample preparation methodology development. The group maintains strong focus on translating structural data into functional performance metrics for nanomaterials. Recent publications (2013-2019) demonstrate consistent emphasis on electron microscopy applications for energy storage materials (batteries, photocatalysts) and functional ceramics. Key trends include structural disorder analysis in piezoelectrics, development of quantitative TEM methods like SUePDF, and nanoscale characterization of electrocatalyst surface phases. His work bridges materials chemistry with advanced imaging techniques. Scientific recognition includes: Fellow of The Royal Microscopical Society (U.K.) Senior Member of IEEE Marie Curie Fellowship (2007-2009) from European Commission Sir Edward Youde Memorial Fellowship (2003/2004) from Hong Kong S.A.R. Government He teaches Solid State Chemistry (KZ7003) and leads Introduction to Analytical Electron Microscopy (KZ8009), having previously taught Advanced Transmission Electron Microscopy (KZ8010) before 2011. Major grants supporting his work include: "Quantitative structural characterisation using 3D electron-based pair distribution function" (Swedish Research Council) "A Multidimensional Toolkit for Modern Electron Microscopy" (Swedish Foundation for Strategic Research) "Mitigating Ni-rich Li-ion cathode side-reactions" (Swedish Energy Agency, Co-applicant) He leads the Cheuk-Wai Tai group within Stockholm University's chemistry department and oversees operations at the Electron Microscopy Center, where his team develops and applies advanced characterization techniques for functional materials research.

• Learning Engineering
• Technology-Enhanced Learning
• Question-Based Learning
• +۱۲ مورد دیگر

Olof Bälter is a Professor in Computer Science at KTH Royal Institute of Technology, affiliated with the Division of Media Technology and Interaction Design within the School of Electrical Engineering and Computer Science. He is the founder of the Technology-Enhanced Learning research group and holds a focus on learning engineering and human-computer interaction. His research interests center on technology-enhanced learning , question-based learning , learning analytics , AI in education , and inclusive pedagogy . A consistent theme in his work is improving efficiency in education and daily life through digital tools. He developed the Pure Question-Based Learning (Pure QBL) methodology, a digital Socratic approach that enhances student engagement and learning outcomes. His work extends to wellness in education through initiatives like walking seminars, and he investigates digital interventions for mental health, such as online Cognitive Behavioral Therapy (CBT) courses. His recent publications highlight trends in AI-generated educational content , learning efficiency , digital pedagogy , and inclusive course design , with applications in computer science education, language instruction, and global development. His research often employs experimental and data-driven methods, including randomized controlled trials and learning analytics. Teacher of the Year at the Surveying program KTH's Pedagogical Prize Higher Education Hero STINT Excellence in Teaching Scholarship (2008 and 2013) Olof Bälter has supervised numerous courses in programming, computer science, media technology, and learning engineering. He has collaborated with institutions such as Stanford University, Williams College, Region Stockholm, Stockholm University, and organizations like Promobilia and Begripsam. His projects aim to scale effective learning methods globally and make education more accessible and efficient. He leads research on the effectiveness of Pure QBL for students with ADHD and is involved in developing digital tools for health literacy and professional development in Ethiopia and Rwanda. His work bridges theory and practice, aiming to transform educational delivery through innovation and evidence-based design.

• Urban Analytics
• Urban Informatics
• Smart Cities
• +۱۲ مورد دیگر

Jorge Gil is an Associate Professor in Urban Analytics and Informatics at Chalmers University of Technology's Department of Architecture and Civil Engineering. His research focuses on integrated urban models, Smart Cities, City Information Modelling (CIM), and Urban Digital Twins, with applications in sustainable mobility, social inclusion, energy transition, and circular economy. He develops GIS solutions and open science methodologies. Teaching includes GIS, sustainable mobility, and spatial data science courses. He supervises Bachelor, Master's, and PhD students. Current projects include LogiNets (logistics network flows analysis), ComCy (cycling safety), and FlowSense (traffic flow data). Key research outputs span agent-based modeling of waste sorting behavior, mobility equity analysis, and multimodal urban network frameworks. He co-authored over 50 publications and actively contributes to interdisciplinary urban planning initiatives.

Frida Rudolphiمشاهده پروفایل

استادیار

• Educational Inequality
• Social Stratification
• Economic Inequality
• +۶ مورد دیگر

Frida Rudolphi serves as a Researcher at the Swedish Institute for Social Research (SOFI) at Stockholm University and as an Assistant Professor (lektor) in the Department for Social Work at Umeå University. Her work focuses on understanding inequality in educational systems, particularly examining how social background, ethnic origin, gender, and family structure intersect with schooling outcomes across different educational stages. Her research employs a multidimensional approach to educational inequality, utilizing quantitative data and methods to examine both primary effects (differences in school performance) and secondary effects (differences in educational choices given performance). She investigates how these mechanisms operate across different educational transitions in Sweden and through comparative studies in England, Germany, the Netherlands, and Norway. Her work reveals important insights about immigrant optimism, gender differences in educational outcomes, and how choice-driven education systems affect different student populations. Rudolphi's publication record demonstrates consistent scholarly output spanning from the early 2000s to the present, with a particular focus on educational transitions, social stratification, and immigrant integration. Her research shows evolving patterns of inequality, with declining overall social class inequality in educational transitions since the mid-20th century, though primary effects remain substantial. Her comparative work across Western countries reveals that female educational advantage persists among second-generation immigrants despite varying gender norms in countries of origin. She actively participates in multiple research projects including IntegrateYouth (examining youth integration across five countries), Gender differences in education, Interlocking inequalities (a multidimensional perspective on inequality in Sweden), and YOUNGWORK (studying early labor market outcomes). Her work on computer gaming and educational outcomes represents a more recent expansion of her research interests into understanding contemporary influences on youth development.

Jonathan Polkمشاهده پروفایل

استاد

• Political Parties
• European Politics
• Comparative Politics
• +۵ مورد دیگر

Jonathan Polk is a Professor at the Department of Political Science , Lund University , Sweden. Previously, he served as an Associate Professor at the University of Copenhagen and University of Gothenburg , where he held a docent title since 2017. His academic journey began with a PhD from the University of Georgia (2012) , followed by a post-doctoral fellowship at the Centre for European Research, University of Gothenburg (2012-2014) . He has contributed as a principal investigator for the Chapel Hill Expert Survey and co-principal investigator for the Swedish Party Membership Survey . Education Bachelor of Philosophy, Saint John's College (2002) Master's in Political Science, University of Georgia (2007) PhD in Political Science, University of Georgia (2012) Polk’s research examines political parties’ roles in contemporary democracies , focusing on multidimensional policy spaces , voter-party congruence , and intra-party dynamics . His work highlights how ideological incongruence leads to political dissatisfaction , voter defection , and support for anti-establishment parties . Recent studies analyze EU policy positioning , Ukraine conflict responses , and trade policy cleavages . His 15 most recent publications (2024-2019) span multidimensional party positioning , public opinion responsiveness , and anti-establishment voting patterns . These studies appear in journals like Journal of European Public Policy , Comparative Political Studies , and European Journal of Political Research , with methodological emphases on expert surveys , mixed-method designs , and cross-national data analysis . He supervises bachelor, master, and doctoral research on Comparative Politics , Political Behavior , and European Union studies . His work aligns with UN Sustainable Development Goals for Democratic Institutions and Peaceful Societies , supported by grants from the Norwegian Research Council , Swedish Research Council (VR) , and Riksbankens Jubeliumsfond (RJ) .

Christina Grundströmمشاهده پروفایل

دانشیار

• Innovation Strategy
• Small and Medium-Sized Enterprises (SMEs)
• Brand Management
• +۳ مورد دیگر

Christina Grundström is an Associate Professor at Linköping University, affiliated with the Department of Management and Engineering (IEI) and the Industrial Management (INDEK) program. Her research focuses on innovation strategies, SME growth dynamics, and brand management. She holds a PhD from Linköping University and has contributed to numerous academic awards including the Outstanding Reviewer accolade at the Academy of Management (AOM) conferences. Her teaching spans brand management and industrial economics across undergraduate to PhD levels. Current research explores how SMEs achieve growth through strategic renewal and effective brand communication. She is part of the Centre for Business Model Innovation (CBMI), emphasizing business adaptation to societal changes. Key collaborations include studies on successful SMEs and stakeholder influence on brand strategies. Education: Master of Science in Applied Physics and Electronics (LiU, 1988), PhD (2004). Research interests emphasize innovation ecosystems, open innovation in manufacturing SMEs, and strategic brand management. Her work bridges theory and practice through industry collaboration, ensuring educational programs remain industry-relevant. Awards highlight her peer-reviewed contributions to STR, TIM, and BPS divisions at AOM. Advising and grants involve thesis supervision in Industrial Economics and Graphic Design. She contributes to curriculum development in cross-media design and international business models. The CBMI lab focuses on business model innovation and adaptive strategies for modern industries.

• Clinical Psychology
• Cognitive Behavioral Therapy
• Chronic Pain Management
• +۳ مورد دیگر

Monica Buhrman is a Senior Lecturer at the Department of Psychology , Uppsala University, Sweden, with a focus on clinical psychology and digital therapeutic interventions. Her work primarily addresses chronic pain management, psychological flexibility, and internet-based cognitive behavioral therapy (CBT) for conditions like fibromyalgia, provoked vestibulodynia, and stress-induced exhaustion. Research Interests: Clinical psychology, acceptance and commitment therapy (ACT), chronic pain management, psychological flexibility, and health psychology. Key Collaborations: Regular co-authorship with researchers such as Lance McCracken, Gerhard Andersson, and Maria Hedman-Lagerlöf. Methodologies: Utilizes randomized controlled trials, network analysis, and psychometric evaluations to assess therapeutic outcomes. Recent Trends: Investigates cost-effectiveness of digital therapies, stigma in chronic pain, and tailored interventions for comorbid conditions. Publications (2022-2025): Explore ACT for fibromyalgia, digital CBT for insomnia in multiple sclerosis, and validation of psychological flexibility inventories.

Carina Moodمشاهده پروفایل

استاد

• Social Stratification
• Economic Inequality
• Intergenerational Transmission of Advantage
• +۵ مورد دیگر

Carina Mood is a Professor at the Swedish Institute for Social Research (SOFI) , Stockholm University. Her research spans social stratification, economic inequality, intergenerational mobility, and immigrant integration, with a focus on child/youth well-being. VR-funded project: Intergenerational mobility: Shifting the focus Completed FORTE-funded MINQ and NORDFORSK-funded IntegrateYouth Affiliated with Institute for Futures Studies and CILS4EU project Research trends show a multidimensional approach to inequality, combining register data with longitudinal surveys. Key sub-fields include: Intergenerational transmission mechanisms Educational and income mobility Immigrant youth integration (attitudes, labor market outcomes) Poverty measurement debates (material deprivation vs income metrics) Peer dynamics in adolescent social networks Urban segregation’s impact on integration opportunities Notable methodological contributions include multiverse analysis for mobility trends and critiques of poverty measurement assumptions. She has explicitly opted out of pure methodological research on logistic regression since 2017, redirecting focus to applied social policy questions.

• Family dynamics
• Fertility behavior
• Fertility intentions
• +۷ مورد دیگر

Chiara Comolli is an affiliated researcher at the Department of Sociology , Stockholm University , specializing in demographic studies with a focus on family dynamics, fertility behavior, and economic uncertainty. She contributes to research on population dynamics through quantitative methods and longitudinal data analysis. Current affiliation: Stockholm University Demographic Division (SUDA) Research areas: Fertility responses to economic crises, well-being analysis, causal inference Specializes in life course studies and social inequality Her recent publications examine fertility trends in Europe during economic downturns, the impact of employment uncertainty on childbearing, and longitudinal effects of family-work trajectories on well-being. Her work integrates interdisciplinary approaches from demography, sociology, and economics. Comolli actively participates in SUDA's research initiatives, which include master's and doctoral programs in demography. Her methodological expertise in causal inference and quantitative analysis contributes to Stockholm University's leading demographic research profile.

Rosa Weberمشاهده پروفایل

مدرس پاره‌وقت

• Social Stratification
• Ethnic Inequalities
• International Migration
• +۵ مورد دیگر

Rosa Weber is a PartTime Lecturer at the Department of Sociology, Stockholm University, and a Principal Investigator for the Segregation Across Domains project funded by the Swedish Research Council for Health, Working Life and Welfare (4.8m SEK, 2023). She holds a PhD in Sociology from Stockholm University (2020) and has conducted postdoctoral research at the French Institute for Demographic Studies (3GEN project) and Sweden’s social sciences sector. Education: PhD in Sociology (2020) Stockholm University MSc in Sociology (2014) London School of Economics BA in Serbian/Croatian and Eastern European Studies (2013) University College London Her research examines social stratification, ethnic inequalities, and migration dynamics across Sweden, Finland, and France. Using administrative data and surveys like Trajectories and Origins 2 (TeO2) and CILS4EU, she analyzes: Workplace and neighborhood segregation impacts on refugee integration Gender-specific labor market barriers for migrants Education-occupation mismatch across migrant generations Circular migration patterns in Nordic free-mobility frameworks Deportation policy effects on migrant financial behavior Key findings include: Male migrants benefit more from social contacts than women in labor markets Refugee children show consistent integration patterns across life domains Increased deportations shift Mexican migrant financial strategies toward remittances Swedish 'Ghetto' policies worsen socio-demographic outcomes Education-occupation vertical mismatch declines across generations in France Her work appears in Demography , Research in Social Stratification and Mobility , and European Journal of Population . She actively participates in migration research networks and policy discussions, maintaining collaborations with institutions like Sciences Po and CREST.

• Geophysics
• Electromagnetic Methods
• Numerical Modeling
• +۷ مورد دیگر

Thomas Kalscheuer is a Senior Lecturer and Associate Professor in Applied Geophysics specializing in electromagnetic methods at Uppsala University's Department of Earth Sciences, Geophysics section. He has been with Uppsala University since 2013 and was awarded Docent (Associate Professor) status in 2017. His work focuses on developing advanced geophysical methods for subsurface imaging and characterization. His educational background includes: PhD in Geophysics from Uppsala University (2008) Diplom-Geophysiker from University of Cologne, Germany (2004) Postdoctoral Fellowship at Swiss Federal Institute of Technology, Zurich (2009-2013) Dr. Kalscheuer's research centers on the development of multidimensional numerical forward modeling and inversion schemes for geophysical electromagnetic and potential field methods. He specializes in joint interpretation of EM, seismic, potential field and borehole data, with applications spanning geotechnical engineering, hardrock geology, tectonics, hydrology, geothermal systems, and volcanology. His current work focuses on 3D inversion algorithms for natural and controlled-source EM methods, building on his earlier contributions to 1D and 2D inversion schemes, model error analysis, and resolution studies. Analysis of his recent publications (2018-2025) reveals a strong focus on advancing 3D electromagnetic inversion techniques, with particular emphasis on transfer function data processing, mesh refinement strategies, and integration of multiple geophysical datasets. His work increasingly addresses practical applications in groundwater surveying, fracture zone detection in hard rock environments, and geothermal system characterization, demonstrating the applied value of his methodological innovations. His notable recognition includes: Distinguished University Teacher award from Uppsala University (2024) Dr. Kalscheuer has supervised numerous research projects, particularly those involving collaboration between Uppsala University and international partners. His work often involves field studies in Sweden (including the Äspö Hard Rock Laboratory site), the Okavango Delta in Botswana, and various locations in Europe. He has secured research funding for projects related to electromagnetic method development and their application to geological and hydrological problems, though specific grant details are not provided in the available information. His research is conducted within the Geophysics section of Uppsala University's Department of Earth Sciences, where he collaborates closely with colleagues specializing in seismic methods, potential field methods, and geological interpretation. His work at the Äspö Hard Rock Laboratory demonstrates involvement with a major international research facility for studying deep geological processes and repository technology.

Johan Henrik Koskinenمشاهده پروفایل

مدرس ارشد

• Bayesian Inference
• Statistical Network Analysis
• Social Network Modeling
• +۷ مورد دیگر

Johan Henrik Koskinen is a Senior Lecturer in Statistics at Stockholm University . He previously held academic positions at the Universities of Melbourne, Oxford, Manchester, and Linkoping . Teaching: Courses in Multivariate Methods and Generalized Linear Models (GLM). Advising: Supervises master’s and PhD students in applied statistics, including Jonathan Januar (funded by ARO Grant W911NF-21-1-0335 for research on missing data in covert networks). Research Interests: Specializes in Bayesian inference and statistical modeling for social networks, focusing on: Partially observed network data and missing data mechanisms Longitudinal and dynamic network analysis Exponential Random Graph Models (ERGM) and stochastic actor-oriented models Computational methods for complex network data Grants: Co-investigator on ARO Grant W911NF-21-1-0335 for covert network analysis Named non-US partner on NSF Proposal No 2005661 for multidimensional networks in car purchases Software Contributions: Development of RSiena (R package for longitudinal network analysis) Maintains MPNet (graphical interface for ERGM)

• Optical Communication
• Fiber Optics
• Photonics
• +۴ مورد دیگر

Magnus Karlsson is a Professor of Photonics at Chalmers University of Technology and serves as Deputy Dean of the Department of Microtechnology and Nanoscience (MC2), responsible for research and graduate education. He co-leads the fiber optics research group with Prof. Peter Andrekson and co-founded the Chalmers Center for Optical Communication (FORCE) in 2010 alongside Prof. Erik Agrell. Karlsson teaches courses in Wireless and Photonics System Engineering and Photonics and Lasers, and holds editorial leadership as Editor-in-Chief of the IEEE/Optica Journal of Lightwave Technology. His research centers on optical fiber communication systems with expertise in light propagation, polarization dynamics, and nonlinear optical effects. Current investigations focus on capacity-enhancing techniques including Voronoi constellation geometric shaping, silicon nitride integrated photonics for microwave applications, and machine learning-driven polarization sensing. His work bridges theoretical modeling of phase-noise channels with experimental validation of novel receiver architectures for deep-space communication through atmospheric turbulence. Recent publications reveal strong trends in overcoming nonlinear transmission limits through multidimensional modulation and MIMO processing for coupled-core fibers. His group pioneers integrated photonic solutions for high-frequency signal generation while advancing real-time network monitoring capabilities in operational fiber infrastructure. Key themes include power-efficient signaling, distributed sensing, and computational methods for channel compensation. Karlsson's leadership in the fiber optics group and FORCE drives collaborative research in next-generation optical networks. His editorial role and ECOC program committee membership position him as a key influencer in shaping global optical communication standards and disseminating cutting-edge research advancements.

• Machine Learning
• Visual Analytics
• Explainable AI
• +۷ مورد دیگر

Juhee Bae is a Senior Lecturer in the Department of Information Technology at the University of Skövde, Sweden. She is affiliated with the AI research group, focusing on machine learning, visual analytics, and explainable AI. Her work bridges research and education, with courses in advanced data science and experience in teaching coordination. Ph.D. in Computer Science, North Carolina State University Merited Teaching Award (2023) Mobility Grant for Belgian University Collaboration (2020) Her research spans machine learning , visual analytics , and explainable AI , with applications in Steel industry process optimization Climate-adaptive water management Migration intention forecasting Smart production logistics Wearable biosensor analysis Recent publications highlight predictive models for weather-driven migration, causal discovery frameworks, and interactive data mining techniques. She contributes to editorial boards and conference organization. Juhee Bae serves as course coordinator for Explainable AI and has been active in international collaborations. Scientific awards include 2023 Merited Teaching Award 2020 Mobility Grant Her projects STRATUS (AI for climate adaptation), INSITE-X (steel industry AI), and Understanding Human Migration demonstrate practical AI applications. She works with interdisciplinary teams and has presented talks on predictive machine learning and explainable AI.

Berkant Savasمشاهده پروفایل

دانشیار

• Scientific computing
• Numerical linear and multilinear algebra
• Large-scale graph/network computations
• +۳ مورد دیگر

Berkant Savas is an Associate Professor at Linköping University's Department of Science and Technology (ITN) within the Physics, Electronics and Mathematics school. His research focuses on scientific computing, numerical linear/multilinear algebra, large-scale graph/network computations, and tensor analysis. He has developed influential algorithms like Clustered Matrix Approximation (CMAPP) and Grassmann manifold computational tools. His work bridges theoretical foundations with practical applications in data science and engineering. Key contributions include scalable methods for massive graphs, low-rank tensor approximations, and optimization on manifolds. Savas' MATLAB-based tools (e.g., Grassmann classes, tensor approximation packages) are widely used in academic and industrial research. He has published extensively in top journals and conferences such as SIAM Journal on Matrix Analysis and IEEE transactions. Current research explores applications in link prediction, recommendation systems, and high-dimensional data analysis. Savas collaborates internationally, with notable co-authors like Inderjit Dhillon and Lars Eldén. His work emphasizes computational efficiency and memory optimization for large-scale problems arising in networks and information retrieval. Though no explicit awards are mentioned, his impactful contributions highlight recognition within the computational mathematics community.