جست‌وجوی استاد و پژوهشگر

Stefan Skareمشاهده پروفایل

استاد مدعو

• Radiology
• Medical Imaging
• MRI Physics
• +۵ مورد دیگر

Stefan Skare is an Adjunct Professor at the Department of Clinical Neuroscience, Karolinska Institutet (2022–2026), with a primary role as MR Physicist at Karolinska University Hospital. His research focuses on developing ultrafast MRI techniques and real-time motion correction systems to enable anesthesia-free MRI for pediatric patients . He leads a research group collaborating with GE Healthcare and Karolinska University Hospital engineers, creating globally adopted tools like NeuroMix and KS Foundation for simplified MRI programming. Doctor of Philosophy, Karolinska Institutet (2002) Recipient of Swedish Childhood Cancer Fund grant (SEK 3.9M over 3 years) for motion-robust MRI in pediatric oncology His work addresses critical challenges in neuroradiology , including reducing scan times from 20–30 minutes to under 3 minutes via proprietary software while maintaining diagnostic quality. Key innovations include: Tracoline : Real-time optical motion tracking for head movement compensation WRAD : Wireless RF sensor for 3ms latency motion correction Snapshot SWI-EPI : Motion-boosted susceptibility imaging NeuroMix : Single-scan, multi-contrast brain exams Scientific contributions span diffusion-tensor imaging , fat/water separation algorithms , and 3D volumetric analysis , with over 20 publications since 2020. His methods have been implemented in clinical settings worldwide, reducing sedation risks and healthcare system burdens.

Hanna Erikssonمشاهده پروفایل

دانشیار

• Cancer and Oncology
• Melanoma Research
• Translational Medicine
• +۴ مورد دیگر

Hanna Eriksson is an Associate Professor at the Department of Oncology-Pathology, Karolinska Institutet , where she leads the Clinical and Translational Melanoma Research Group. Her work bridges clinical decision-making and translational research, leveraging large-scale register data, artificial intelligence, and multi-omics analyses within clinical trials. Her research focuses on: Immune-tumor microenvironment interactions Overcoming immunotherapy resistance Real-world melanoma treatment outcomes Gender differences in immunotherapy side effects Development of quality of life modules for advanced melanoma Key trends in her 2025–2021 publications include tumor heterogeneity in brain metastases, adjuvant immunotherapy optimization, plasma proteomics, and biomarkers for immune checkpoint inhibitors. Her group explores AI integration in diagnostics and precision medicine strategies. She supervises PhD students and postdocs, and has secured grants from: Swedish Research Council Swedish Cancer Society Horizon 2020 (GenderNet-Plus) Radiumhemmet Research Funds Stockholm Regional Council Karolinska Institutet Translational Seed Funding Her team collaborates on trials like G-DEFINER (gender-specific immunotherapy toxicities) and AIDMel (AI in melanoma diagnostics), emphasizing real-world data and multi-omics approaches.

• Cancer Research
• Precision Medicine
• Hematology
• +۳ مورد دیگر

Tom Erkers is an Assistant Professor at the Department of Oncology-Pathology, Karolinska Institutet, leading the Functional Systems Oncology team. His research focuses on functional precision medicine and molecular profiling in blood cancers, particularly acute myeloid leukemia (AML) and pediatric acute lymphoblastic leukemia (ALL). University: Karolinska Institutet Department: Department of Oncology-Pathology Academic Rank: Assistant Professor (2020-2024) Research Interests: His work explores cancer cell behavior, treatment resistance, and immune interactions in hematologic malignancies. Key areas include: Functional precision medicine (fPM) Multi-omics integration for therapeutic targets Drug synergy prediction models Radiotherapy and autophagy inhibition strategies Immune tolerance mechanisms in transplantation Publications Trends: Recent articles emphasize: Ex vivo sample handling impacts on precision medicine reliability Computational models for drug combinations in AML Targeting SAMHD1 and BCLxL in leukemia iNKT cell heterogeneity in autoimmune contexts Molecular hallmarks of hematologic cancers Team Members: Collaborators include PhD students Lucía Rico Pizarro and Nona Struyf, postdoctoral researcher Flora Mikaeloff, and multidisciplinary scientists across the Kallioniemi group.

• Functional Programming
• Domain-Specific Languages
• Climate Impact Research
• +۷ مورد دیگر

Patrik Jansson is a Professor of Computer Science at Chalmers University of Technology since 2011, with joint affiliation to Gothenburg University. His work bridges Functional Programming, Domain-Specific Languages (DSLs), and applications to Climate Impact Research, Fusion, and Physics.

Yi Wangمشاهده پروفایل

استاد

• Embedded Systems
• Real-Time Systems
• Real-Time Scheduling
• +۷ مورد دیگر

Yi Wang is a Professor of Embedded Systems at the Department of Information Technology, Uppsala University , Sweden. He leads research in real-time and embedded systems with a focus on modeling, analysis, and implementation of safety-critical applications. He is affiliated with the Embedded Systems Group and serves as a Principal Investigator (PI) in major research centers such as UPMARC and projects like CUSTOMER (ERC Advanced Grant), CoDeR-MP, and CERTAINTY. Research Interests: Yi Wang’s work centers on Embedded Systems Design, Real-Time Scheduling, Multicore Programming, and Model-Checking of Real-Time Systems . His research addresses fundamental challenges in timing predictability, schedulability analysis, and the verification of complex real-time systems. He has made significant contributions to the digraph real-time task model, mixed-criticality systems, and timing analysis of ROS 2 systems. His work bridges theory and practice, often resulting in deployable tools and formal methods for industrial applications. Recent Research Trends: His most recent publications (2023–2025) focus on optimizing real-time performance in ROS 2, managing parallel task graphs with resource contention, improving GPU-based inference on embedded platforms, and enhancing timing predictability in multithreaded executors. These works reflect a strong trend toward applying formal real-time theory to modern robotics, AI integration, and multicore embedded architectures. Scientific Tools and Leadership: He is a key contributor to foundational tools in real-time systems: UPPAAL – Model checking for timed automata TIMES – Schedulability analysis and code generation CATS – Compositional analysis of timed systems TIMES-Pro – Based on the digraph real-time task model Advising and Research Funding: Yi Wang has supervised numerous PhD students and postdocs. He has led or participated in multiple large-scale funded projects supported by the Swedish Research Council (VR), the Swedish Foundation for Strategic Research (SSF), and the European Commission (FP7, ERC). These include UPMARC (10-year Linnaeus center), CoDeR-MP (with ABB and SAAB), SAVE++ (with VOLVO), and CREDO. Laboratories and Research Groups: He is a core member of the Embedded Systems Group at Uppsala University and leads research within the UPMARC center, which focuses on programming models and analysis techniques for multicore architectures. His lab develops formal methods and tools to ensure correctness and timing guarantees in embedded and cyber-physical systems.

Anders Ynnermanمشاهده پروفایل

استاد

• Scientific Visualisation
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Anders Ynnerman is a Professor of Scientific Visualisation at Linköping University, specializing in leveraging visualization for data exploration, human-computer interaction, and bridging scientific communication between experts and the public. His research focuses on transforming massive datasets into interpretable visual representations, spanning scales from cellular molecules to cosmic structures, while advancing transparency in AI systems through visualization. Institution: Linköping University Award: Wallenberg Scholar Ynnerman leads efforts within the Wallenberg AI Autonomous Systems and Software Program (WASP) to integrate human-centric design into autonomous systems, emphasizing visual interfaces for bidirectional human-machine feedback. His work targets demystifying AI algorithms by visualizing training data and neural network structures, enabling better understanding and refinement of machine learning processes.

• Gender Studies
• Norm-Critical Design
• Sociology of Education
• +۳ مورد دیگر

Anna Isaksson serves as a Senior Lecturer at Halmstad University's School of Health and Welfare, where she has established herself as a leading researcher in gender studies, norm-critical design, and sociology of education. Her interdisciplinary work bridges healthcare, education, and public sector innovation, with particular focus on how gender norms operate in institutional settings. Her research interests center on gender equality implementation , norm-critical pedagogical approaches , and sociological interventions in healthcare and educational systems . Isaksson's work examines how gender norms manifest in professional environments, educational settings, and healthcare contexts, with special attention to power dynamics and institutional structures. She has developed innovative tools like the G-Core framework for gender mainstreaming in higher education and has conducted extensive research on gender in male-dominated professions such as the fire service. Analysis of her 15 most recent publications reveals consistent focus on gendered experiences in institutional contexts , with particular emphasis on visual methodologies, participatory design, and norm-critical approaches. Her work spans healthcare (particularly women's health and elder care), education systems, and public sector organizations, demonstrating how gender norms operate across different institutional settings through both material and discursive practices. Isaksson completed her doctoral thesis Challenging the limits of change: A study of transformative work, partnership and gender, exemplified by the Equal Programme in 2010, establishing her foundational work on gender mainstreaming in collaborative projects. Her research consistently bridges theoretical frameworks with practical applications, particularly in educational settings where she develops and tests norm-critical teaching tools and methodologies.

Eva Frühwald Hanssonمشاهده پروفایل

مدرس ارشد

• Timber Structures
• Biobased Materials
• Wood-Moisture Relations
• +۵ مورد دیگر

Eva Frühwald Hansson serves as Senior Lecturer and Head of Office in the Division of Structural Engineering at Lund University's Department of Building and Environmental Technology. She holds additional leadership roles as Deputy Head of Department and contributes to two LTH Profile Areas: Circular Building Sector and The Energy Transition. Lund University, Faculty of Engineering (LTH) Department of Building and Environmental Technology Division of Structural Engineering Her research centers on timber structures and biobased materials, with specialization in wood-moisture dynamics, durability prediction, and sustainable building envelopes. Key focus areas include probabilistic hygrothermal modeling, mold risk assessment, and circular construction methodologies. Her work directly supports UN Sustainable Development Goals through sustainable building technologies. Recent publications demonstrate strong trends in machine learning applications for mold prediction (with Random Forest algorithms), probabilistic service life modeling, and innovative use of hygroscopic materials for energy efficiency. Research spans building physics, structural engineering, and environmental sustainability with emphasis on practical implementation. Scientific recognition includes: Best Research into Practice Paper Prize (2019) She actively supervises doctoral students and leads significant research initiatives, including five major projects funded by Vinnova and industry partners. Her grant portfolio emphasizes biobased construction, industrialized building systems, and service life performance frameworks. Hansson co-manages two critical university infrastructures: the Civil Engineering Laboratory and the Structural Engineering Laboratory, supporting experimental research in timber structures and building materials.

• Industrial Engineering and Management
• Optimization Modeling
• Risk and Uncertainty Analysis
• +۵ مورد دیگر

Dr. Leif Olsson is an Associate Professor at Mid Sweden University's Department of Communication, Quality Management and Information Systems (KKI), where he has been employed since 2004. He serves as Director and Head of Internationalization for the Industrial Engineering and Management (IEM) program and is affiliated with the Risk and Crisis Research Centre (RCR) and Forum for Digitalization (FODI) research groups. Academic Title: Associate Professor University: Mid Sweden University Department: Department of Communication, Quality Management and Information Systems (KKI) His research focuses on integrating quantitative and qualitative risk analysis in optimization modeling, with applications spanning industrial engineering, forest management, healthcare, and critical infrastructure resilience. Key subfields include: Supply Chain Optimization Accessibility and Regional Development Forest Economics and Sustainability Emergency Response Logistics Military Supply Chains Carbon Sequestration Valuation His publications (2002–2024) examine optimization techniques in diverse domains: Forest resource allocation (15% of articles) Transportation and logistics (40% of articles) Healthcare systems (10% of articles) Infrastructure resilience (25% of articles) Information systems (10% of articles) Research projects include: SYRE: Regional Electric Aviation Network Design CCRAAAFFFTING: Simulation Games for Critical Infrastructure Resilience Perspectives on Accessibility: Infrastructure-Regional Development Links Educational background: BSc in Mathematics Master of Education in Mathematics and Economics PhD in Forest Economics

Magnus Isakssonمشاهده پروفایل

استاد

• Signal Processing
• Telecommunications
• Electrical Engineering
• +۳ مورد دیگر

Professor Magnus Isaksson is affiliated with the University of Gävle as Head of Faculty of Health and Occupational Studies and Deputy Vice-Chancellor for EUI – Green Universities. He holds a PhD in Telecommunications from the Royal Institute of Technology (2007) and is an Honorary Professor at Amity University (since 2020). His research focuses on signal processing algorithms for radio frequency measurements and modeling of nonlinear microwave systems. Research Interests: Magnus specializes in RF power amplifier behavioral modeling, digital predistortion techniques, and MIMO system analysis. His work extends to robotic exoskeletons for physical assistance, including lower-limb and upper-body designs, with applications in rehabilitation and occupational ergonomics. He explores nonlinear network analysis, model parameter reduction, and advanced control strategies for mechatronic systems. Publication Trends: Recent publications highlight his dual expertise in telecommunications (e.g., Volterra kernel extraction, I/Q imbalance mitigation) and robotics (e.g., exoskeleton actuator design, dynamic load compensation). Articles from 2017-2025 reflect interdisciplinary applications of signal processing to human-robot interaction and wireless system optimization.

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۳ مورد دیگر

Abdallah Alabdallah is a postdoctoral researcher at the School of Information Technology , Halmstad University. His research focuses on Artificial Intelligence , Machine Learning , and Survival Analysis , particularly in developing trustworthy and explainable predictive models. University: Halmstad University School: School of Information Technology Email: abdallah.alabdallah@hh.se His recent publications emphasize Survival Analysis and Predictive Maintenance , with innovations in loss function design , counterfactual explanations , and SHAP-based interpretability . Collaborative work explores heterogeneous federated learning and generative proxy models for industrial applications. Contact: abdallah.alabdallah@hh.se

Donal Caseyمشاهده پروفایل

مدرس ارشد

• Regulatory Governance
• Gambling Regulation
• Artificial Intelligence Ethics
• +۳ مورد دیگر

Donal Casey is a Senior Lecturer at the Department of Law, Uppsala University, with a focus on regulatory governance, gambling regulation, and food safety. He has contributed extensively to interdisciplinary research, particularly in AI ethics and transnational business governance. Research Interests: Regulatory governance in public and private spheres Legal frameworks for gambling and charity regulation in the EU Food safety and quality standards under transnational regimes (e.g., GLOBALGAP) Human-machine interaction and ethical AI design Notable Collaborations: Worked with scholars like Lina Eklund (2025), Virginia Dignum (2024), and Kate Bedford (2018) on regulatory and technological challenges.

Folke Sjöbergمشاهده پروفایل

استاد

• Burn Care
• Critical Care
• Wound Healing
• +۵ مورد دیگر

Folke Sjöberg is a Professor in Burn Surger/Critical Care at Linköping University and Medical Director of the burn department at Linköping University Hospital, which holds national responsibility for burn care. His dual roles bridge clinical practice and academic research, focusing on intensive care , burn recovery , and microcirculation studies . PhD supervisor to 37 students (20 completed) Editorial board member of 7 journals including Burns and Microcirculation Active in international burn organizations (ISBI, EBA) Research Interests span burn care innovation , stem cell applications , and artificial intelligence in wound assessment . Recent work explores glass substrates for keratinocyte propagation , epidemiology of burns , and sepsis management in burn trauma. His team investigates miRNA regulation in skin regeneration and novel dermatome technologies . Scientific Awards include: Linköping University's "Promising Young Scientist" (1987) Olof Norlanders Memorial Fund for "Promising Swedish Anesthesiologist" (1995) Radiometer Prize (1999) Östergötland County Teaching & Research Prize (2003) Teaching & Supervision encompasses clinical mentorship since 1985 , lecturing medical students and specialty trainees , and opponent roles in 8 PhD defenses . He has served on editorial boards for journals like Burns and Critical Care Medicine , and contributed to over 200 peer-reviewed publications. Labs & Collaborations include the Burn Center at Linköping University Hospital and partnerships with institutions such as the Swedish Intensive Care Registry . His work impacts European burn care guidelines through leadership in the European Burns Association and ISBI.

• Sustainable Structural Engineering
• Multi-Criteria Optimization
• Structural Product Development
• +۳ مورد دیگر

Hamid Movaffaghi is a Senior Lecturer and Associate Professor in Structural Engineering at the Department of Engineering, University of Borås, with expertise in numerical methods, finite element modeling (FEM), and optimization algorithms. He plays a key role in teaching, supervision, and research within the Academy of Textiles, Technology and Economics. Education: Master of Science in Civil Engineering (Computational Mechanics, 1990), PhD in Structural Mechanics (Chalmers University of Technology, 2007) His research focuses on sustainable structural design , including: Multi-criteria analysis algorithms for product development Automatic coupling of commercial software using FEM and optimization He collaborates with researchers at the University of Borås and Jönköping University of Technology, as well as industry partners in manufacturing and software sectors. His academic service includes jury membership for the Byggmästaren scholarship and quality coordination for research/education initiatives.

Moa Johanssonمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Automated Reasoning
• Neuro-Symbolic Methods
• +۴ مورد دیگر

Moa Johansson is an Associate Professor (Docent) at the Department of Computer Science and Engineering, Chalmers University, Sweden. She serves as Co-Director of Chalmers' Area of Advance in Information and Communication Technology, driving interdisciplinary AI research. PhD in Automated Theorem Proving (University of Edinburgh, 2009) Postdoc at University of Verona (2009-2011) Her research spans neuro-symbolic AI methods , combining neural networks with symbolic reasoning for applications in mathematics, sports science, and political science. Current projects include: NeSSy (2023-): Neuro-symbolic synthesis via reinforcement learning Neurodynamic Programming (2023-): Agent communication learning Countering Bias in AI (2023-): NLP applications in social sciences Bias in Political Analysis (2020-2025): WASP-HS funded Recent publications focus on theory exploration , neuro-symbolic methods , and AI applications across disciplines. Scientific achievements include a VINNMER Marie Curie Fellowship and Best Paper Award at CICM 2014. Led TRACKS project course on sports digitalization Developed HipSpec automated inductive prover