جستجوی استاد راهنمای دانشگاهی

• Informatics
• Digitalization
• Quality Management
• +۴ مورد دیگر

Thomas Persson is a Senior Lecturer at Mid Sweden University's Department of Communication, Quality Technology and Information Systems (KKI). His research spans digitalization, quality management, rural entrepreneurship, and gender perspectives in informatics education. Academic Rank: Senior Lecturer University: Mid Sweden University Department: Department of Communication, Quality Technology and Information Systems (KKI) Research interests focus on co-working environments in rural contexts, digital transformation in social care, boundary objects in data hubs, and action research methodologies. He actively contributes to police science in hybrid investigation settings and explores social interaction in e-learning. Recent publications (2015–2025) address digital innovation in energy systems, gender integration challenges in informatics, and configuration management benefits. Collaborative projects involve stakeholders across Scandinavia. Thomas participates in the Forum for Digitalization (FODI) and has editorial roles in academic publications. His work combines technical systems analysis with socio-cultural dimensions of digital adoption.

• Political Science
• Electoral Systems
• Voter Behavior
• +۴ مورد دیگر

Stefan Dahlberg is a Professor in the Department of Humanities and Social Sciences at Mid Sweden University, specializing in political science with focus on electoral behavior, democracy perception, and indigenous politics. His research spans comparative electoral systems, voter psychology, and Sámi political participation across Nordic contexts. His primary research interests include electoral system impacts , radical right party dynamics , Sámi political representation , and computational analysis of democracy concepts . Dahlberg employs advanced methodologies including distributional semantic modeling, experimental designs, and cross-national survey analysis to examine voter behavior, media discourse, and institutional trust. His work frequently addresses how contextual factors like electoral systems and social stigma shape political engagement. Dahlberg's publication trends reveal increasing focus on computational political science since 2020, with significant work on semantic modeling of democratic concepts across 93 countries. His research bridges traditional political science with digital humanities approaches, particularly through development of linguistic tools for societal analysis. Recent outputs emphasize radical right voting stigma, indigenous electoral participation, and media representations of minority groups. Scientific awards: 2020 GESIS Klingemann Prize for Best CSES Scholarship (shared with Harteveld, Kokkonen, van der Brug) Dahlberg leads multiple research projects examining political discrimination against Sámi communities and democratic innovations at municipal levels. His ongoing work includes election surveys for Sami Parliament elections (2021 and beyond), analyzing continuity and change in indigenous political representation. He contributes significantly to the Quality of Government datasets and collaborates extensively on international projects involving European electoral behavior and media effects. His laboratory work centers on computational analysis of political discourse, utilizing distributional semantic models to map conceptualizations of democracy across languages. Current team projects involve 16-country comparative experiments on populist communication effects and longitudinal studies of voter behavior in Nordic contexts.

Christine Beckerمشاهده پروفایل

مدرس ارشد

• Language Education
• Cultural Memory Studies
• Digital Media in Language Instruction
• +۳ مورد دیگر

Christine Becker is a Senior Lecturer and Associate Professor at the Department of Slavic and Baltic Languages, Finnish, Dutch and German at Stockholm University. She specializes in cultural learning, historical memory, and digital media applications in language education. Her work integrates intercultural competence with technological innovation, focusing on asynchronous communication and blended learning models. Degree in literary translation and German as a foreign language from Heinrich-Heine-Universität Düsseldorf PhD in 2017 on cultural learning in computer-mediated communication Director of Studies for doctoral program (2020-2023) Deputy Head of Department (2024-2025) Research explores memory culture in language teaching, postcolonial perspectives, and digital learning tools. She co-founded the international network HolDaF/Z for Holocaust education in German as a foreign language contexts and leads the Swedish network for empirical research in German language education. Recent publications examine digital competencies in language teaching, discourse analysis of historical memory, and pedagogical frameworks for blended learning. Supervises doctoral research on AI-assisted writing and community representations in textbooks, utilizing both synchronous and asynchronous online platforms for collaborative learning.

Robert Johanssonمشاهده پروفایل

دانشیار

• Artificial General Intelligence
• Clinical Psychology
• Emotion-focused Psychotherapy
• +۴ مورد دیگر

Robert Johansson is an Associate Professor and University Lecturer in the Department of Psychology at Stockholm University, where he maintains an active research program spanning both artificial intelligence and clinical psychology. His work bridges two seemingly disparate fields, exploring how principles of human cognition can inform artificial general intelligence development while simultaneously applying psychological insights to improve mental health treatments. Dr. Johansson's research focuses on two primary areas: Artificial General Intelligence (specifically examining Arbitrarily Applicable Relational Responding as a framework for understanding intelligence) and clinical psychology (with emphasis on emotion-focused psychotherapy and internet-delivered treatments). His work demonstrates how insights from behavioral psychology can inform both therapeutic approaches and AI development. He has been instrumental in the ERiCA project, which developed and tested internet-mediated psychodynamic therapy for adolescents with depression, showing promising results compared to established cognitive behavioral approaches. His publication record reveals a distinctive dual trajectory in scholarship. On one hand, he has made significant contributions to understanding and developing internet-based psychological treatments for depression, anxiety, and somatic symptom disorders. On the other hand, he has pioneered research connecting relational frame theory with artificial intelligence, particularly through the Non-Axiomatic Reasoning System (NARS). This unique interdisciplinary approach positions him at the intersection of clinical practice and AI theory. Dr. Johansson's work demonstrates consistent methodological rigor, with numerous randomized controlled trials, systematic reviews, and meta-analyses in clinical psychology, alongside theoretically sophisticated computational modeling in AI. His research shows particular strength in translating theoretical concepts into practical applications, whether developing new therapeutic protocols or computational frameworks for artificial intelligence.

Martin Henkelمشاهده پروفایل

دانشیار

• Enterprise Modelling
• Business Process Management
• Conceptual Modelling
• +۵ مورد دیگر

Martin Henkel is an Associate Professor at Stockholm University's Department of Computer and Systems Sciences (DSV), where he conducts research and teaches in enterprise modeling, business process management, and service-oriented computing. His work bridges theoretical frameworks with practical applications in healthcare, transportation, and public sector digitalization. Dr. Henkel earned his PhD in 2008 in service-oriented information systems. His research focuses on enterprise capability design, business value modeling, and developing methodologies for organizational change. He leads the PRECIS research group which addresses theories, methods and tools for analysis and design of organizational and IT solutions in congruence across three key topics: Enterprise Modelling, Business Process Management, and Conceptual Modelling. His publication record demonstrates consistent contributions to enterprise modeling, particularly in capability modeling and inter-organizational processes. Recent work shows a growing emphasis on healthcare applications, with several projects addressing digital solutions for elderly care and healthcare collaboration. His research combines theoretical modeling with practical implementation across multiple sectors. Ongoing Projects: DISAL (Data-driven solutions in complex care processes), DISRA (Digital innovation in collaboration between city, region and academy) Completed Projects: KYKLOS method for capability change, Online rehabilitation system for COVID-19 patients, Virtual Case System, Enterprise Modelling of Organisational Rules Dr. Henkel teaches courses on cross-organizational ERP systems, software architecture, enterprise modeling, and service design. His research has been applied in domains including transport, healthcare, and IT systems for energy efficiency through various projects such as CaaS, REMS Healthcare, Serviam, and EnRiMa.

Joanna Tyrchaمشاهده پروفایل

استاد

• Statistical Inference
• Econometrics
• Neuroscience
• +۶ مورد دیگر

Joanna Tyrcha is a Professor in Mathematical Statistics at the Department of Mathematics, Stockholm University, and currently serves as the Head of the Department. Her academic career spans institutions in Poland, Canada, and Sweden, with roles including Lecturer, Director of Undergraduate Studies, and Head of the Division of Mathematical Statistics. M.S., Mathematical Statistics, Warsaw School of Economics, 1980 Ph.D., Mathematics, Jagiellonian University, 1989 Associate Professor, Mathematical Statistics, Stockholm University, 2003 Professor, Mathematical Statistics, Stockholm University, 2011 Her research integrates statistical inference , econometrics , and neuroscience , focusing on cell cycle models , neural connectivity , biological information processing , causality , and ion channel modeling . Recent publications highlight applications of Ising models to neural data, nonstationary dynamics , and transfer entropy in non-Gaussian distributions. Key collaborations include work with J. Hertz and Y. Roudi on network inference, and with C. Nellåker on mixture models for genomic data. Joanna has taught courses such as Probability Theory and Econometrics . She leads the Mathematical Statistics research group at Stockholm University, which focuses on biostochastics , biostatistics , discrete random structures , and finance/insurance applications.

• Signal Processing
• Machine Learning
• Statistical Signal Processing
• +۱۱ مورد دیگر

Saikat Chatterjee is a Professor in the Department of Information Science and Engineering at the School of Electrical Engineering and Computer Science, Royal Institute of Technology (KTH). He is also a Fellow of Digital Futures and maintains visiting researcher positions at Karolinska Institute, Karolinska Hospital (specializing in 'AI for Health Care'), and Oslo University Hospital in Norway. His primary research interests span Signal Processing and Machine Learning, with specific focus on signal modeling (sparsity, compressive sensing, dynamical systems), statistical signal processing, statistical machine learning, deep learning, speech/audio/image processing, medical data analytics, life science data analysis, perception for autonomous systems, distributed machine learning, and explainable AI (XAI). He particularly emphasizes explainable machine learning, having a strong background in signal processing and statistical machine learning, with growing passion for medical data analysis due to its societal importance. SSF - Swedish Foundation for Strategic Research Region Stockholm European Union Digital Futures Vinnova WASP Companies: Ericsson, Scania, Saab Professor Chatterjee is actively involved in teaching, serving as examiner and course responsible for various degree projects and courses including Machine Learning and Data Science, Pattern Recognition and Machine Learning, and Speech and Audio Processing. His research group has produced significant work across multiple domains, with notable publications in Bioinformatics and smart city applications, demonstrating the breadth of his research impact from healthcare to urban systems.

• Network Security
• Machine Learning
• Data-Driven Systems
• +۳ مورد دیگر

Xiaoxuan Wang is a researcher at the Network and Systems Engineering department of the Royal Institute of Technology (KTH). Their work focuses on optimizing machine learning processes in networked systems, particularly through feature selection and statistical methods for cybersecurity applications. Research Trends: Analysis of the four articles (2020-2024) reveals expertise in Developing online feature selection techniques for networked systems Applying statistical learning to intrusion detection Designing low-overhead machine learning architectures Network security evaluation through testbed measurements

• MAC layer wireless
• Machine learning
• Optimization theory
• +۳ مورد دیگر

Xiaojing Yan is a Researcher at the Division of Network and Systems Engineering, School of Electrical Engineering and Computer Science , KTH Royal Institute of Technology . She is supervised by Carlo Fischione and Gabor Fodor in her doctoral studies. Her research focuses on integrating MAC layer wireless , machine learning , and channel coding with an emphasis on over-the-air computation using the superposition property of electromagnetic waves. She holds a bachelor's and master's degree in Electrical Engineering from the Beijing University of Posts and Telecommunications. Xiaojing Yan's publications address advanced topics in wireless systems, including modulation design , power adaptation , multiple access computing , and stochastic game theory applied to network coexistence and resource allocation. Her work spans both theoretical and applied aspects of digital signal processing and network optimization in modern communication systems.

• Atomistic modeling
• Materials Science
• Fracture Mechanics
• +۵ مورد دیگر

Pär Olsson is a Senior Lecturer at the Department of Mechanics, Materials and Component Design within Lund University's Faculty of Engineering. His research focuses on atomistic-scale modeling of materials phenomena using both classical and quantum mechanical approaches. Research Areas: Intergranular fracture in tungsten alloys, adhesion between metal-oxides and polymers, phase stability of ultra-thin iron-oxide films, transgranular fracture in titanium and zirconium hydrides Subject Classification: Applied Mechanics, Condensed Matter Physics, Nanotechnology Recent publications highlight his work in: Dynamic instability in sigma phase transition metal alloys Grain boundary interaction potentials Phase-field crystal modeling for elastic deformation Polarization in polyvinyl fluoride systems Neutron scattering laws for zirconium hydrides He leads the research project Atomistic investigation of intergranular fracture in tungsten (2017-2023) with collaborators from Lund University.

Hui Chenمشاهده پروفایل

پژوهشگر

• Integrated Sensing and Communication (ISAC)
• 5G/6G localization
• wireless sensing
• +۵ مورد دیگر

Hui Chen is a Research Specialist in the Communication Systems group at the Department of Electrical Engineering, Chalmers University of Technology, Sweden. He leads research in 5G/6G localization and sensing, distributed ISAC, and machine learning, contributing to major EU and Swedish projects including 6G-DISAC, RISE-6G, HEXA-X, and 5GPOS/B5GPOS. His educational background includes a Ph.D. in Electrical and Computer Engineering from King Abdullah University of Science and Technology (KAUST) in August 2021, where he worked in the Information System Lab under Professor Tareq Al-Naffouri. Chen's research focuses on advancing wireless localization through integrated sensing and communication (ISAC) techniques, with emphasis on distributed systems and machine learning applications. His work spans channel modeling, algorithm design, and optimization for mmWave/THz communications, addressing challenges in privacy preservation, mutual coupling effects, and cooperative positioning in complex environments. He actively develops solutions for next-generation 6G networks including terrestrial and non-terrestrial integration. Recent publications demonstrate strong trends toward RIS-assisted localization, privacy-aware beamforming, and multi-vehicle control frameworks, reflecting a multidisciplinary approach bridging communications, aerospace systems, and signal processing. His work shows increasing focus on non-terrestrial networks and cooperative positioning architectures. Key scientific recognitions include: European Union Marie Skłodowska-Curie Postdoctoral Fellowship (MSCA-PF) Swedish Vinnova International Mobility Grant Chalmers Area-of-Advance Transport Seed Funding Ericsson Research Grant China National Scholarship (awarded three times) Chen has secured substantial research funding through competitive grants and leads technical contributions in multiple high-impact projects. As an Editor for IEEE Communications Letters since March 2025, he actively shapes scholarly discourse in wireless communications while mentoring junior researchers within the CROSSNET team. He is a core member of the CROSSNET research team at Chalmers, led by Professor Henk Wymeersch, which focuses on communication systems for future networks. The team maintains active GitHub repositories for radio localization algorithms and collaborates internationally on 6G standardization efforts, with recent work accepted at IEEE ICC 2025 and major IEEE transactions.

• Wireless Communications
• 6G Technology
• Radio Localization
• +۳ مورد دیگر

Sharief Saleh is a Postdoctoral Researcher at the Communication Systems department within Chalmers University of Technology . His work focuses on advanced wireless communication and localization technologies for next-generation networks. Research Affiliation: Chalmers University of Technology School: College of Engineering Department: Communication Systems Contact: sharief@chalmers.se | +46 31 772 20 27 Research interests center on: 6G Network Localization - Integrating terrestrial and non-terrestrial networks Sub-THz Communication Systems - Addressing propagation and interference challenges Radio Wave Positioning - Enhancing accuracy through signal processing Vehicle Tracking Algorithms - Optimizing Kalman filter covariance parameters Recent publications analyze: Ground-air-space network localization techniques Sub-THz communication standards RIS-aided satellite localization Multipath reflection utilization in 5G Active projects include: 6G LUNAR (2025-2029): European Commission-funded lunar communication network research Hexa-X-II : EU-COST project on 6G cross-layer design

• Aerodynamics
• Propulsion Systems
• Computational Fluid Dynamics (CFD)
• +۴ مورد دیگر

Olivier Petit is a researcher at the Department of Thermo and Fluid Dynamics at Chalmers University of Technology, Sweden. His work focuses on aerodynamics , propulsion systems , and computational fluid dynamics (CFD) , with emphasis on turbofan engines, open rotor designs, and boundary layer ingestion technologies.

• Energy Technology
• Biomass Gasification
• Waste Valorization
• +۵ مورد دیگر

Martin Seemann is a Professor at Chalmers University of Technology in the Department of Energy Technology. His research focuses on thermochemical conversion processes, particularly gasification and steam cracking, for renewable energy and waste valorization. He specializes in fluidized bed reactor technologies and catalytic processes for sustainable chemical production. Key research themes include biomass gasification, plastic waste recycling, and chemical looping systems. Recent publications address the optimization of dual fluidized bed reactors, tar reforming, and the use of industrial byproducts as catalysts. His work spans from laboratory-scale experiments to industrial-scale applications, emphasizing practical solutions for carbon-neutral processes and circular economy strategies in energy systems.

• Learning Analytics
• Artificial Intelligence in Education
• Human-Computer Interaction
• +۷ مورد دیگر

Robert Ramberg is a Professor at the Department of Computer and Systems Sciences (DSV) at Stockholm University, Sweden, and serves as research director at the Swedish Defence Research Agency (FOI). His academic journey began with a PhD in cognitive psychology from Stockholm University's psychology department, establishing a strong foundation for his interdisciplinary research spanning cognitive science, educational technology, and human-computer interaction. Ramberg's research interests focus on learning analytics, AI for education, and the application of emerging technologies like IoT, VR, and MR in educational contexts. He leads the Learning Analytics and AI for Education Group and the ReVisE Research Group, which explores how technologies can enhance educational practice through innovative visualizations and real-world applications. His work bridges theoretical frameworks of socio-cultural learning with practical implementations in both educational and military training environments. His recent publications reveal a strong focus on teachers' design processes, simulation training (particularly Live-Virtual-Constructive integration for flight training), and the application of learning analytics in educational settings. His research demonstrates a consistent pattern of investigating how digital tools mediate human action, collaboration, and learning across diverse contexts from primary schools to military aviation. Ramberg teaches courses including 'Cognitive Psychology in HMI' for the bachelor program in interaction design and 'Design for complex and dynamic contexts' for the master's program in design for creative and immersive technology. His current research projects include 'Use of IoT to visualize teachers' patterns of movement in the classroom' and 'L(ive), V(irtual) & C(onstructive) for efficient flight training,' reflecting his dual focus on educational technology and military simulation training. His research methodology frequently employs participatory design approaches, collaborating with teachers, students, and military personnel to develop and evaluate technology-enhanced learning environments. Ramberg maintains active collaborations with schools, industry partners across Sweden, and international research institutions, contributing to the broader field of Technology Enhanced Learning (TEL) through both theoretical contributions and practical implementations.