جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence in Healthcare
• Precision Medicine
• Machine Learning Applications in Healthcare
• +۵ مورد دیگر

Magnus Boman is a Professor of AI and Health at the Department of Medicine, Solna, Karolinska Institutet (KI), where he leads the AI@KI initiative to support researchers in AI integration. He is affiliated with the Chronic Inflammatory Disease Epidemiology research group under Johan Askling. His research focuses on AI applications in precision medicine, multimodal prediction, ethical norms in AI systems, energy-efficient computing, and quantum sensor data interpretation. Research Interests: Artificial Intelligence in healthcare and precision medicine Multimodal data analysis for disease prediction and treatment Machine learning for clinical decision support systems Ethical and societal implications of AI Grants: Swedish Research Council: Improving breast cancer histology image classification (2024-2026) Scalable Federated Learning (2022-2025) Ai in sustainable cities (VINNOVA, 2019) Advising & Students: Supervised over 50 PhD and Master's students across KI, KTH, and Stockholm University, focusing on AI applications in healthcare, machine learning, and computational epidemiology. Notable projects include predictive modeling for mental health outcomes and variant filtering in genetic data. Labs & Teams: Leads AI@KI, fostering AI adoption in medical research. Collaborates with the Johan Askling group on epidemiology and chronic disease studies.

Elisabet Langmannمشاهده پروفایل

دانشیار

• Educational Philosophy
• Didactics
• Ethics in Education
• +۵ مورد دیگر

Elisabet Langmann serves as Associate Professor and Department Head at Södertörn University, Sweden, specializing in Teacher Training with research bridging educational philosophy and classroom practice. Her work critically examines ethical dimensions of schooling and democratic values implementation. Langmann holds a PhD in Educational Philosophy from Örebro University (2013), where her dissertation explored pedagogical approaches to teaching tolerance while avoiding student marginalization. Her academic journey reflects deep engagement with continental philosophy and didactic theory. Her research centers on ambiguities in democratic values (tolerance, justice, responsibility) and their classroom implications, investigating how value conflicts manifest and how supportive teaching climates emerge. Methodologically, she integrates empirical classroom observations with philosophical analysis, drawing from phenomenology and critical theory to examine sensory, affective, and ethical dimensions of learning environments. Analysis of her 2021-2025 publications reveals three evolving trajectories: sustainability education exploring climate change pedagogy; sensory-phenomenological approaches to classroom climate; and continued refinement of tolerance education frameworks. These strands converge in examining how affective dissonance and bodily experiences shape ethical learning. Langmann actively secures research funding including two Swedish Research Council projects (2020-2023): as project leader for "Forms of Upbringing" investigating bodily dimensions in value conflict resolution, and as co-investigator in "How can schools reduce unequal educational opportunities?" examining school culture in disadvantaged areas. She mentors junior researchers through international networks rather than formal student supervision. She contributes significantly to academic infrastructure as board member of the Nordic Society of Philosophy of Education, co-convenor for NERA/EERA educational philosophy networks, and peer reviewer for 12+ journals including Studies in Philosophy and Education. Her leadership extends to international research collectives like PEDST and SCAPE, focusing on democratic sustainability transitions and cultural conflicts in education.

Malin Brobergمشاهده پروفایل

استاد

• Developmental Psychology
• Disability Studies
• Family Welfare Systems
• +۶ مورد دیگر

Malin Broberg is a Professor in Psychology and the current Vice-Chancellor (since 2023) and President of the University of Gothenburg. She was previously Dean of the Faculty of Social Sciences at the same institution. Educated at Umeå University, she is a licensed psychologist with a clinical background in child and youth habilitation. Her research focuses on: Welfare systems for families with disabled children Stress coping mechanisms Neurodevelopmental impacts of brain damage in children Augmentative and Alternative Communication (AAC) Parental well-being and resilience Recent publications (2024-2023) highlight her work in neuropsychology, health-promoting learning environments, and AAC interventions for children with profound disabilities. She has collaborated with researchers in Sweden and the USA, and her work appears in journals like Child Neuropsychology and Disability and Rehabilitation-Assistive Technology . Malin Broberg has supervised doctoral and Master’s theses in developmental psychology and disability research. She has also served as General Secretary of the International Association for the Scientific Study of Intellectual and Developmental Disabilities (IASSIDD).

Gustav Eje Henterمشاهده پروفایل

استادیار

• Speech Synthesis
• Machine Learning
• Artificial Intelligence
• +۶ مورد دیگر

Gustav Eje Henter is an Assistant Professor at KTH Royal Institute of Technology, holding roles as the Head of Research at Motorica AB and a Core Team Member of the Wallenberg Research Arena (WARA) for Media and Language. He is the Secretary of the ISCA SynSIG (Special Interest Group on Speech Synthesis) and a Co-Organiser of the GENEA Workshops on Embodied Agents' Non-Verbal Behavior. His research focuses on speech synthesis, gesture generation, and multimodal interaction, with contributions to TTS systems, neural networks, and embodied AI. He leads Digital Futures, a cross-disciplinary research center addressing societal challenges through digital technologies. This center is a collaboration between KTH, Stockholm University, and RISE. His work spans foundational research to industrial applications, emphasizing ethical AI, privacy in voice conversion, and human-robot interaction. Key research themes include causal reasoning in LLMs, adversarial privacy techniques, and benchmarking frameworks like the GENEA Leaderboard. He has organized international workshops (GENEA 2021-2024) and contributed to standards in TTS evaluation methodologies. His technical innovations include HiFi-Glot for formant synthesis and Matcha-TTS for fast waveform generation. His research integrates audio, gesture, and motion synthesis with deep learning, addressing challenges in spontaneous speech synthesis, multimodal coherence, and listener perception. He advocates for rigorous evaluation practices and open challenges to advance the field's reproducibility and real-world applicability.

• Control Technology
• Distributed Optimization
• Machine Learning
• +۴ مورد دیگر

Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +۴ مورد دیگر

Zenun Kastrati is an Associate Professor at the Department of Informatics, Linnaeus University. His research focuses on Artificial Intelligence, Natural Language Processing, Machine Learning, Semantic Web, Sentiment Analysis, and Learning Technologies. He contributes to the Data-driven Business Innovation (DBI) and Interaction Design Research Groups, leading projects like Forest 4.0, RAPID, and IGNITE. His recent work involves Explainable AI, medical imaging, and multilingual NLP. Ph.D. in Computer Science (NTNU, 2018) Master's in Computer Science (EU TEMPUS Programme) Previous Lecturer/Researcher at University of Prishtina His research spans AI applications in medical diagnostics , NLP , sentiment analysis , and semantic technologies . Key projects include Forest 4.0 (environment monitoring) and RAPID (online education in Pakistan). Publications highlight his expertise in deep learning , transformer models , and context-aware systems . Recent publications demonstrate trends in Explainable AI (XAI) for healthcare, medical imaging techniques, and multilingual NLP frameworks. Other work explores social media analytics , student feedback analysis , and pedagogical document classification . Zenun's teaching includes Fundamentals of Programming , Object-Oriented Programming , Web Applications , Data Analytics , and Adaptive Web courses at BSc and MSc levels.

Susan Sayehliمشاهده پروفایل

دانشیار

• Psycholinguistics
• Second Language Acquisition
• Neurocognitive Linguistics
• +۳ مورد دیگر

Susan Sayehli is an Associate Professor at the Department of Swedish Language and Multilingualism , Stockholm University. She specializes in psycholinguistics and second language acquisition, with a focus on crosslinguistic influence and morphosyntactic processing. Research Interests: Neurocognitive aspects of language learning Focus intonation development in Swedish children Policy impact on SFL (Spanish/French/German) education ERP and eye-tracking methodologies for language processing Urban-rural educational disparities in language programs Current Projects: TAL – Alignment study on oral proficiency in Swedish schools Att lära sig fokusera – Intonation perception in Stockholm/Skåne children Prior Projects: SWOP2 – Swedish word order processing in L2 learners PSUII – Precursors of sign use in intersubjectivity

• Pedagogical Anthropology
• Tacit Knowledge
• Corporeality in Education
• +۷ مورد دیگر

Anja Kraus is a Professor in Arts and Culture Education at Stockholm University, Department of Teaching and Learning. She has held academic positions at the University of Education Ludwigsburg (2003-2013), Linnaeus University Växjö (2013-2019), and joined Stockholm University in 2018. Her academic journey began with studies in Philosophy and Educational Sciences at Free University Berlin and Arts Education at the University of the Arts Berlin, Germany. Her research focuses on Pedagogical Anthropology, with special emphasis on tacit knowledge, corporeality, aesthetic education, and multimodal learning. She has developed systematic approaches to understanding tacit knowing in educational contexts, particularly examining how corporeality, aesthetic learning, and inclusivity function in schools. Her work bridges phenomenological, ethnographical, and body-phenomenological approaches with practical educational applications. She has made significant contributions to understanding how materiality, performativity, and imaginaries shape educational practices. Her recent publications reveal strong trends in embodiment studies, with particular attention to kinesthetic learning, spatial pedagogy, and the relationship between aesthetics and sustainability. Her work increasingly explores educational practices within the Anthropocene context, examining how arts education can address environmental concerns through embodied approaches. The recurring theme across her publications is the exploration of how tacit knowledge manifests in educational settings and how this understanding can transform teaching practices. As head convenor of the international scientific network 'Tacit Dimensions of Pedagogy,' she has organized numerous workshops and conferences addressing pedagogical terminologies across languages. Her collaborative projects span Scandinavia, Europe, Asia, and North and South America, demonstrating her commitment to transcultural approaches in educational research. Her teaching spans multiple languages (German, English, Swedish, Spanish) and covers diverse areas including Classroom Education, Cultural and Media Education, Sciences of Bildung, Elementary Education, and Vocational Training. Her pedagogical approach emphasizes practice-oriented competence, inclusive school development, and aesthetic learning environments with a comparative perspective.

• Robotics
• Human-Robot Interaction
• Machine Learning
• +۷ مورد دیگر

Christian Smith is an Associate Professor and Lecturer at the Department of Robotics, Perception and Learning at Kungliga Tekniska Högskolan (KTH Royal Institute of Technology). His research focuses on robotics and applications in human-centered environments like home environments, small workshops, and healthcare facilities, including the development of new robotic systems for research. Teaching Roles: Course Coordinator/Teacher/Examiner for courses such as Introduction to Robotics (DD2410), Research Project in Robotics (DD2411), and Java Programming for Python Programmers (DD1380) Research Themes: Human-Robot Interaction, Behavior Trees, Exoskeletons, Intent Recognition, and Multimodal Perception Awards: No specific scientific awards mentioned in the provided text His KTH profile highlights work on adaptive robotics systems and formalized control strategies. The research portfolio spans from theoretical studies on behavior tree programming to applied work in assistive technologies and teleoperation systems.

• Lifelong Learning
• Digitalization in Education
• Teacher Shortage
• +۶ مورد دیگر

Marcia Håkansson Lindqvist is a researcher at Mid Sweden University's Department of Education (UTV), with expertise in digitalization in education, teacher shortage, and school leadership. She contributes to projects like European Education Policy Network and HIMUV (Sustainability in Mid Sweden University Everyday Life) , focusing on organizational development and lifelong learning. Her research spans Technology-enhanced learning environments Professional development frameworks Artificial intelligence applications in education Comparative studies on teacher shortages in Nordic countries She has published extensively in journals like Journal of Educational Administration and British Journal of Educational Technology . Recent work explores AI integration in school leadership, hybrid work-integrated learning models, and cross-sector collaboration for special needs education. She collaborates with researchers across Scandinavia and contributes to edited volumes on leadership identity and digital competence.

Morteza Haghir Chehreghaniمشاهده پروفایل

استاد

• Machine Learning
• Decision Making
• Reinforcement Learning
• +۱۷ مورد دیگر

Morteza Haghir Chehreghani is a Professor of Artificial Intelligence and Machine Learning at the Data Science and AI Division of Chalmers University of Technology , Sweden. He leads the Machine Learning and Decision Making Lab and is affiliated with WASP , CHAIR , and ELLIS . Education : PhD in Computer Science (2014) from ETH Zurich under Prof. Dr. Joachim M. Buhmann Prior Roles : Staff Research Scientist at Naver Labs Europe (2014-2018) Research spans Interactive Machine Learning , Sequential Decision Making , Federated Learning , Efficient Deep Learning , and Graph-Based Learning . Key application areas include Transport , Autonomous Systems , Energy , Drug Discovery , and Computational Biology . Selected Publications (2020-2025) demonstrate expertise in Reinforcement Learning for drug design, Minimax Distance Measures for clustering, and Graph Neural Networks for trajectory analysis. Current work focuses on Combinatorial Bandits and Human-in-the-loop AI . Teaching includes graduate courses like Advanced Topics in Machine Learning (DAT441/DIT41), Algorithms for Machine Learning (TDA233/DIT382), and PhD-level Advanced Reinforcement Learning . He has also taught Statistical Methods for Data Science and Theoretical Foundations of ML . Patents include systems for Autonomous Vehicle Motion Control , K-NN Search via Minimax Distances , and Trip Prediction Algorithms . Collaborative projects involve Nature Communications (2022) and multiple ICML / CVPR publications.

• Software Metrics
• Model Driven Software Development
• Empirical Software Engineering
• +۵ مورد دیگر

Miroslaw Staron is a Professor of Interaction Design and Software Engineering at Chalmers University of Technology. He maintains a unique 50/50 work arrangement, spending half his time on field research at Ericsson while holding his academic position. His research bridges academic theory with industrial practice through collaborations with major companies including Volvo Car Corporation and Volvo Information Technology. His research spans several key areas in software engineering: Software metrics and measurement systems in industry Model driven software development and empirical studies Defect prediction in software projects Requirements engineering in model-based development Applications of AI and machine learning in software engineering Automotive software development and security Staron's recent work demonstrates a strategic shift toward integrating AI technologies into software engineering processes, with particular focus on automotive applications. His publications from 2024-2025 reveal expertise in generative AI applications for code review automation, testing methodologies, and requirements engineering, showing how these technologies can transform traditional software development practices while addressing domain-specific challenges in automotive systems. Current research projects include: Kvantdatorer för framtidens mobilitetslösningar (2025-2027) Automatiserad och designoptimerad programvarukonstruktion/kodgenerering (2025-2029) Förvandla fordonsarkitektur med hjälp från AI (2021-2023) Arkitektonisk design och verifiering/validering av system med maskininlärning komponenter (2020-2024) With 78 publications documented in Chalmers' research database, Staron has established himself as a significant contributor to evidence-based software engineering research with strong industrial relevance.

• Memory
• Cognitive Control
• Neuroscience
• +۵ مورد دیگر

Mikael Johansson is a Professor in the Department of Psychology at Lund University, where he leads research on the cognitive and neural bases of memory and cognitive control. His academic appointments include membership in eSSENCE: The e-Science Collaboration, LAMiNATE (Language Acquisition, Multilingualism, and Teaching), LU Profile Area: Proactive Ageing, and LU Profile Area: Natural and Artificial Cognition. With 159 research outputs and leadership in 18 projects (8 active), he maintains a prominent position in cognitive neuroscience research. His research focuses on the neural mechanisms of memory using behavioral, electrophysiological (EEG/ERP), and functional magnetic resonance imaging (fMRI) methods. Key interests include interactions between memory systems, formation and retrieval of episodic memories, emotion regulation and emotional memory, mechanisms underlying incidental and intentional forgetting, and the relationship between eye-movements, mental imagery and memory. His work has significant implications for understanding memory functions in psychiatric conditions such as depression and post-traumatic stress disorder. Analyzing his extensive publication record spanning from 2012-2025 reveals a consistent focus on memory mechanisms with increasing integration of eye-tracking methodologies and clinical applications. His research demonstrates an evolving trajectory from basic memory processes toward understanding memory in real-world contexts and clinical populations, with recent work emphasizing the role of eye movements in memory construction and the neural dynamics of memory integration. Mikael Johansson serves as a member of The Swedish National Committee for Psychological Sciences at the Royal Swedish Academy of Sciences since 2011 and has received significant research funding including from The Bank of Sweden Tercentenary Foundation, Swedish Research Council, and Stiftelsen Marcus och Amalia Wallenbergs Minnesfond. His current major projects include TEAM: Transdisciplinary Approaches to Learning, Acquisition, Multilingualism (2024-2029), Tracking cognitive change as a function of normal ageing and different types of degenerative disease, and How the brain constructs the present and reconstructs the past via sequences of eye movements. He leads the Lund Memory Lab where his team investigates how the brain constructs and maintains coherent episodic memories through eye movements. His research group actively collaborates with international partners across multiple disciplines, bridging cognitive psychology, neuroscience, and clinical applications. The lab's work has gained significant attention, with several publications being highlighted in news outlets and academic discussions.

• Contemporary German-Language Literature
• GDR Literature
• Cultural Studies Didactics
• +۷ مورد دیگر

Dr. Frank Thomas Grub is Professor of German and Head of the Department of Modern Languages at Uppsala University. Educated at Universität des Saarlandes (Dr. phil. 2003) and promoted to Associate Professor at Gothenburg University (2012) before joining Uppsala as Professor (2018), he has been recognized as Excellent Teacher (2021). As founder of the Landeskunde Nord network since 2012 and editor of the Peter Lang book series since 2013, his career bridges academic research, educational innovation, and international collaboration. His research focuses on contemporary German-language literature , GDR cultural studies , and transcultural didactics . Key projects explore autobiographical writing, post-Wall literary representations, and the intersection of travel literature with cultural memory. Recent publications (2024-2025) examine media narratives of reunification and cultural stereotypes in language pedagogy. Prof. Grub contributes to German as a foreign language curriculum development Intercultural competence frameworks Editorial leadership in Northern European Germanistics His 2023-2025 works analyze graphic novels in education, migration discourse in literature, and media transitions during the Cold War.

Tommy Löfstedtمشاهده پروفایل

دانشیار

• Machine Learning
• Computer Vision
• Medical Image Analysis
• +۴ مورد دیگر

Tommy Löfstedt is an Associate Professor at Umeå University , affiliated with the Department of Computing Science and the Department of Mathematics and Mathematical Statistics. His research focuses on machine learning , computer vision , and medical image analysis , with applications in life sciences, radiation therapy, and biomedical imaging. He leads multiple research projects, including AI-driven delineation in radiation therapy, quantitative MRI for radiotherapy, and machine learning for plant nutrient uptake. Current research emphasizes structured regularization methods to improve model interpretability and robustness. Key applications include medical image segmentation , Alzheimer's classification , and uncertainty estimation in MRI . Recent publications highlight his work on morphological regularization , adversarial attack mitigation , and multi-task learning in medical imaging contexts. His projects span 2022–2026 with funding for pediatric oncology automation and gynecological cancer staging. Affiliated with both computing and mathematical departments, he bridges algorithm development with applied mathematical frameworks in medical and life science domains.