جست‌وجوی استاد و پژوهشگر

Sajad Daei Omshiمشاهده پروفایل

پژوهشگر

• Integrated Sensing and Communications
• Wireless Communications
• Signal Processing
• +۳ مورد دیگر

Sajad Daei Omshi is a Postdoctoral researcher at KTH Royal Institute of Technology, working in the Division of Information Science and Engineering under Professors Mickael Skoglund and Gabor Fodor. His research focuses on Integrated Sensing and Communications (ISAC), wireless signal processing, and radar-communication system design. Previously, he held a postdoc position at EURECOM under Professor Marios Kountouris, focusing on semantic and goal-oriented communications. Education: PhD in Electrical and Electronics Engineering from Iran University of Science and Technology (2015–2019). Research areas include mathematical optimization, compressed sensing, super-resolution techniques, MIMO communications, and channel estimation. His work addresses challenges in 6G networks, millimeter-wave systems, and radar-communication integration. Key research contributions span ISAC frameworks, blind signal recovery, and distributed computing. Notable achievements include the 2020 IEEE Iran Section Outstanding PhD Thesis Award. He collaborates actively with institutions like Farzad Parvaresh's Lab at KTH and has published over 50 articles in top conferences/journals. Awards: Outstanding PhD thesis award of IEEE Iran Section (2020) Advising/Grants: No specific advising information available, though his postdoc roles imply mentorship in collaborative projects. His research is supported by grants focusing on ISAC and 6G technologies. Labs/Teams: Member of Farzad Parvaresh's Lab at KTH, contributing to signal processing and communication systems research.

Ioana-Oriana Berceaمشاهده پروفایل

استادیار

• Theoretical Computer Science
• Data Structures
• Randomized Algorithms
• +۶ مورد دیگر

Ioana-Oriana Bercea is an Assistant Professor at the Division of Theoretical Computer Science (EECS), KTH Royal Institute of Technology, and a member of the Digital Futures Faculty. She holds a PhD in Computer Science from the University of Maryland, with prior postdoctoral research at the IT University of Copenhagen and Tel Aviv University. Her research focuses on Theoretical Computer Science, including Data Structures (e.g., Bloom filters), Randomized Algorithms (e.g., hashing), and Computational Geometry (e.g., TSP). Education : PhD in Computer Science, University of Maryland (advisor: Samir Khuller) Master's in Computer Science, University of Maryland (advisor: Aravind Srinivasan) Bachelor of Science in Mathematics (Honors) and Computer Science, University of Chicago Research Interests : She explores scalable data management (e.g., Bloom filters), algorithm design for clustering and hashing, and geometric optimization problems. Her work emphasizes theoretical foundations with practical applications. Key Achievements : VR Starting Grant (2024) for the project "DataTech" Best Artifact Award at ACM SIGMOD 2023 for the InfiniFilter paper Advising & Grants : Advises PhD student Jonas Østergaard Klausen (joint with Mikkel Thorup and Jacob Holm) Lead researcher on grants exploring data storage and algorithmic efficiency Labs & Teams : Active in KTH's Theoretical Computer Science group and collaborates with the Digital Futures initiative to advance cross-disciplinary digital technologies.

Henrik Kaatariمشاهده پروفایل

مدرس ارشد

• Corpus Linguistics
• Language Learning
• Grammatical Variation
• +۳ مورد دیگر

Henrik Kaatari is a Senior Lecturer in the Department of English at the University of Gävle . His research focuses on corpus linguistics , language learning , and formality in academic writing , with particular interests in grammatical variation , syntactic complexity , and the impact of extramural English (EE) activities on L2 writing development. Current Project : Principal Investigator of the ComplEExity Project (RJ P23-0437), funded by the Bank of Sweden Tercentenary Foundation, investigating EE's impact on Swedish secondary students' L2 writing. Research Areas : Lexical complexity, register variation, phraseology, and self-initiated language learning. His recent publications analyze the relationship between extramural exposure (e.g., gaming, YouTube) and improvements in lexical diversity and grammatical complexity. Using the Swedish Learner English Corpus , Kaatari employs cross-sectional designs and complexity measures to assess writing development across lexis, phraseology, and grammar. His work has practical implications for English pedagogy in Swedish schools.

• Cryptography
• Steganography
• Machine Learning
• +۵ مورد دیگر

Eric Järpe is a Senior Lecturer at the School of Information Technology, Halmstad University, Sweden, specializing in the convergence of cryptography, steganography, and machine learning for real-world applications. His research focuses on: Advanced steganography techniques across unconventional domains (music, vehicles, smart homes) Machine learning applications for healthcare monitoring and smart sensing Statistical modeling for anomaly detection and sensor data analysis Synthetic data generation to enhance real-world dataset limitations Järpe's work bridges theoretical statistics with practical security and health informatics, particularly addressing challenges in elderly care systems and vehicular networks through innovative data-driven approaches. Publication trends reveal a clear evolution from foundational statistical methods (Ising models, change-point detection) toward applied cryptographic solutions and machine learning for smart environments, with recent emphasis on synthetic data generation for dementia care and activity monitoring systems.

Yushan Liمشاهده پروفایل

پژوهشگر ارشد

• Control Systems
• Networked Dynamical Systems
• Multi-Robot Systems
• +۳ مورد دیگر

Yushan Li is currently a Postdoc Researcher in the Division of Decision and Control Systems at KTH Royal Institute of Technology, Sweden. He received his Ph.D. in Control Science and Engineering from Shanghai Jiao Tong University (SJTU) in 2024 and a B.E. in Automation from Huazhong University of Science and Technology (HUST) in 2018. His research focuses on cooperation and inference in networked systems, with applications to robotic networks and control security. Education: B.E. in Automation (2018) from HUST Ph.D. in Control Science and Engineering (2024) from SJTU His research interests include networked dynamical systems, multi-robot cooperation, topology inference, and cybersecurity in control systems. He has contributed to adversarial strategies against formation control, secure collaboration algorithms, and topology preservation under attacks. Recent publications highlight his work on network topology inference, secure control mechanisms, and adversarial strategies. His research has been accepted in prestigious journals such as IEEE Transactions on Automatic Control and IEEE Transactions on Robotics , with presentations at international conferences like CDC and IFAC World Congress. Scientific Awards: 2025 SJTU Outstanding Doctoral Dissertation Award 2023 SJTU Academic Star National Scholarships (2023, 2022, 2019) 2023 Best Oral Presentation Award at ZJU Swarm Intelligence Forum Li has also served as a teaching assistant for undergraduate courses on intelligent optimization of network systems and as a reviewer for leading journals including IEEE Transactions on Automatic Control and Automatica . He co-founded the Distributed Control, Optimization, and Security Zhizhen Forum and contributed to organizing major international conferences.

• Industrial Internet of Things
• Wireless Sensor Networks
• Network Security
• +۵ مورد دیگر

Patrik Österberg serves as Associate Professor and Head of Department at Mid Sweden University's Department of Computer and Electrical Engineering (DET) in Sundsvall. He leads the STC Research Centre and actively contributes to multiple research projects including DRIVEN, InSIKT, KITT, and M2M Communication initiatives. His office is located in room L407 with direct contact via phone (+46 (0)10-1428614) and email. His research spans Industrial Internet of Things, wireless sensor networks, and network security with particular focus on mission-critical communication systems. Österberg investigates protocol enhancements for LoRaWAN, 6TiSCH networks, and Non-Orthogonal Multiple Access techniques to optimize reliability, latency, and security in industrial environments. His work addresses fundamental challenges in energy efficiency, congestion control, and traffic differentiation for heterogeneous IoT deployments. Recent publications (2021-2025) demonstrate concentrated effort on balancing mission-critical and enhanced mobile broadband services in cellular IoT, security frameworks for blockchain-based access control, and synchronization techniques for large-scale LoRa networks. His research increasingly integrates artificial intelligence for congestion management and explores hardware security solutions for fog computing end-devices. Österberg leads multiple significant research projects including DRIVEN (Expert Competence for Data-Driven Industrial Transformation), InSIKT (Secure ICT for indoor environments), and KITT (Context-Information Sharing for IoT Applications). These initiatives receive substantial funding and involve collaboration with industrial partners to address real-world challenges in industrial digitalization and secure communications. He actively contributes to the STC Research Centre where his team develops advanced communication protocols for industrial applications. Current work focuses on reliable emergency-aware communication schemes, priority-aware wireless fieldbus protocols, and energy-efficient synchronization mechanisms for large-scale IoT deployments.

• Person-Centered Integrated Care
• Care Transitions
• Health Services Research
• +۷ مورد دیگر

Sebastian Lindblom is a Postdoctoral Fellow and SFO-V Fellow at the Department of Neurobiology, Health Sciences and Society, Karolinska Institutet (2021-2025). He holds a doctoral degree in Medical Science (2021) and clinical affiliations as a registered physiotherapist at Karolinska University Hospital since 2011. Doctorate in Medical Science (2021) Master's in Clinical Medical Science (2015) Bachelor's in Physiotherapy (2011) His research focuses on person-centered integrated care, emphasizing how meaning-making, continuous learning, and interdisciplinary collaboration enhance healthcare design for stroke survivors and hypertension patients. Key interests include care transitions, implementation science, and fostering global networks for junior researchers. Recent publications span care transitions for stroke patients ( Int J Integr Care 2025), hypertension management in primary care ( J Clin Hypertens 2025), machine learning for hypertension prediction ( Prev Med Rep 2024), and qualitative analyses of stakeholder experiences in integrated care ( BMC Neurol 2024). Scientific Awards: SFO-V Fellowship Grants: Swedish Research Council for Health Working Life and Welfare (2021-2024), funding care transition research for older stroke patients Network Involvement: Chairs the global Emerging Researchers and Professionals in Integrated Care (ERPIC) network, promoting international collaboration and career development in integrated care research.

• Numerical Analysis
• Stochastic Partial Differential Equations
• Random Fields
• +۳ مورد دیگر

Annika Lang is a Professor in the Department of Applied Mathematics and Statistics at Chalmers University of Technology's School of Mathematical Sciences. She serves as head of her department/unit and is responsible for all PhD students, postdocs, researchers, and guest teachers. Her research focuses on numerical analysis of stochastic partial differential equations and the regularity and simulation of random fields . Her work bridges theoretical mathematics with practical applications in areas such as traffic modeling, quantum computing applications, and ice sheet modeling. Lang has made significant contributions to the development of numerical methods for stochastic PDEs on manifolds, particularly on spherical domains. Lang's recent publications (2022-2025) demonstrate a consistent focus on advancing computational methods for stochastic processes. Her work spans theoretical developments in regularity analysis of random fields, numerical approximation techniques like finite element methods and Galerkin-Chebyshev approximations, and practical applications in traffic management and environmental modeling. A notable trend is her increasing interdisciplinary work connecting stochastic mathematics with transportation engineering and physics-aware machine learning. Principal investigator for the European Commission-funded project 'Time-Evolving Stochastic Manifolds (StochMan)' (2023-2028) Co-investigator on the Swedish Research Council project 'Efficient approximation methods for random fields on manifolds' (2021-2024) Collaborator on multiple projects including 'Quantum computing for future mobility solutions' and 'STOchastic Traffic NEtworks (STONE)' Lang leads a research group that bridges pure mathematical theory with computational applications, supervising PhD students and postdoctoral researchers in developing novel numerical methods for stochastic processes. Her work has received funding from major sources including the European Commission, Swedish Research Council, and Chalmers University.

Torsten Olbersمشاهده پروفایل

استاد

• Bariatric Surgery
• Metabolic Disease
• Obesity Treatment
• +۳ مورد دیگر

Torsten Olbers is a Professor of Surgery at Linköping University and a researcher at the Wallenberg Centre for Molecular Medicine (WCMM). He leads the Swedish Nationwide BEST project and the AMOS research program for adolescent bariatric surgery. His clinical expertise includes over 2,000 laparoscopic bariatric procedures, refining the double-loop gastric bypass technique widely used in Scandinavia. Olbers holds leadership roles at Sahlgrenska University Hospital and Carlanderska Hospital, overseeing bariatric surgery and research groups. He has authored key studies on obesity surgery outcomes, including long-term cardiovascular effects and gut microbiome changes post-surgery. Education: MD from Lund University (1991), PhD from Sahlgrenska Academy (2004), postdoc at Harvard Medical School (2006-2007). He completed pedagogical courses for teaching skills at Sahlgrenska (2005, 2009, 2012). Research Focus: Bariatric surgery innovation, metabolic disease, and adolescent obesity treatment. He investigates surgical techniques, comorbidity resolution, and long-term patient outcomes. His work includes the SOS study, a landmark investigation into obesity surgery’s effects. Awards: Swedish Surgical Society award (2008), Best Resident (1998), and teaching recognition (2006). He serves on editorial boards, including Scandinavian Journal of Surgery , and chairs the Swedish Bariatric Surgery Association. Administration: Directorships in Minimal Invasive Surgery and Obesity Centers, Medical Director of Bariatric Surgery at Carlanderska Hospital, and leadership roles in national and international obesity surgery registries.

Peter Bangمشاهده پروفایل

استاد

• Pediatric Endocrinology
• Growth Disorders
• Insulin-like Growth Factor (IGF-I) Research
• +۴ مورد دیگر

Peter Bang is a Professor of Pediatrics and Head of Division at the Division of Children's and Women's Health (BKH) within the Department of Biomedical and Clinical Sciences (BKV) at Linköping University. His academic career includes a PhD from the Karolinska Institute, postdoctoral training at Stanford University, and clinical expertise in pediatric endocrinology. Education: Graduated from the Engineering School, Technical University of Copenhagen; Medical School, University of Copenhagen; PhD under Prof. Kerstin Hall at Karolinska Institute. Completed pediatric endocrine training at Karolinska University Hospital. Research focuses on GH-IGF axis regulation, growth disorders, diabetes, and neonatal health, with 50+ peer-reviewed publications. Key projects include the Global Increlex Registry analyzing rhIGF-1 therapy and the EU-IGFD registry for SPIGFD patients. Labs/Teams: Leads the Division of Children's and Women's Health (BKH), collaborating on multidisciplinary pediatric and妇幼 health research. Active in clinical trials and registry-based studies for rare endocrine disorders.

August Ernstssonمشاهده پروفایل

مدرس

• Parallel Programming
• Heterogeneous Computing Systems
• High-Performance Computing
• +۳ مورد دیگر

August Ernstsson is a Lecturer at Linköping University’s Department of Computer and Information Science (IDA). He is affiliated with the Graduate School in Computer Science (CUGS) and research groups Programming Environments (PELAB) and Software and Systems (SAS). His research focuses on parallel programming models, heterogeneous computing systems, and optimizing software for FPGA and GPU architectures. Notable contributions include frameworks for high development productivity (EXA2PRO) and deterministic parallel algorithms. Ernstsson’s work emphasizes performance portability, compiler design, and abstraction layers for heterogeneous systems. He collaborates with international teams on projects like pattern-based programming abstractions and FPGA-accelerated systems.

• Immunology
• Respiratory Medicine
• Allergy
• +۳ مورد دیگر

Lars-Olaf Cardell is a Professor and Senior Physician at Karolinska Institutet's Department of Clinical Science, Intervention and Technology. His work bridges immunology, respiratory medicine, and otorhinolaryngology, with a focus on allergy mechanisms, cancer immunology, and translational clinical research. He leads studies on immune responses in chronic rhinosinusitis, nasal polyps, and head/neck cancers, emphasizing tumor-draining lymph node biology and immunotherapy efficacy. Cardell’s research integrates clinical trials (e.g., comparing immunotherapy modalities) with mechanistic studies (e.g., neutrophil and regulatory B cell behavior). He collaborates internationally, contributing to EUFOREA guidelines for allergic rhinitis classification and treatment algorithms. His work addresses both basic science (e.g., ILC2 memory) and public health aspects (costs and sustainability of immunotherapy). Notable contributions include defining phenotypic differences in tumor-associated neutrophils and linking PD-L1 expression to poor oral cancer prognosis. His studies often involve multidisciplinary teams and translational approaches, aiming to improve patient outcomes through biomarker discovery and therapy optimization.

Zhanzhang Caiمشاهده پروفایل

پژوهشگر ارشد

• Remote Sensing
• Vegetation Dynamics
• Climate Change Impacts
• +۴ مورد دیگر

Zhanzhang Cai is a Research Fellow and Postdoctoral Fellow at Lund University's Department of Physical Geography and Ecosystem Science, with a secondary affiliation as a Visiting Research Fellow in the Division of Water Resources Engineering. His research utilizes satellite remote sensing to study vegetation dynamics, climate impacts, and ecosystem processes. Dr. Cai's work centers on environmental remote sensing with applications in: Vegetation phenology and productivity monitoring Drought and climate change impacts on ecosystems Machine learning applications for agricultural yield prediction Wildfire effects on carbon cycling in boreal forests His publications frequently employ Sentinel-2 and MODIS data for time-series analysis across diverse biomes. He contributes to major projects including: BioClima (Horizon Europe, 2025-2028): Integrating climate and biodiversity monitoring HR-VPP2: Copernicus vegetation phenology and productivity mapping Twin-Waters (FORMAS, 2024-2026): Sustainable water resource management tools He has supervised graduate research on agricultural albedo impacts using Sentinel-2 data.

Magnus Löfstrandمشاهده پروفایل

استاد

• Mechanical Engineering
• Product Development
• Production Development
• +۷ مورد دیگر

Magnus Löfstrand is a Professor of Mechanical Engineering at Örebro University, Sweden. He holds a PhD in Computer-Aided Design (2007) from Luleå University of Technology and a Docent (2015) in Product and Production Development from Chalmers University of Technology. His academic career spans multiple institutions, including Uppsala University and Umeå University prior to his current role. Research focuses on industrial system availability, digital twin technology, and data-driven approaches for optimizing production systems. Key areas include simulation-driven design, predictive maintenance, and integrating mechanical engineering with information technology. His work emphasizes sustainability through resource-efficient production processes and competitive industrial advantages. Teaching responsibilities include courses in the Industrial Engineering and Management program at Örebro University, covering topics like Process Development, Reliability Engineering, and Academic Writing. He supervises bachelor's and master's theses across engineering disciplines. Collaborations with institutions like the University of Nottingham and Umeå University's Logic and Applications group highlight his interdisciplinary approach. He is a member of the American Society of Mechanical Engineers (ASME) and actively participates in international conferences and research projects, including the AVANS MAXI program and digital twin initiatives in mining innovation.

Martin Rosvallمشاهده پروفایل

استاد

• Complex Systems
• Network Science
• Information Theory
• +۲ مورد دیگر

Martin Rosvall is a Professor at the Department of Physics (IceLab section) at Umeå University, with joint affiliation to Molecular Infection Medicine Sweden (MIMS). He leads research on information flows through social and biological systems, developing methods to simplify complex network interactions into interpretable maps. His work addresses critical questions about disease spread, plant stress responses, and biodiversity distribution with applications to sustainability challenges. Research focuses on: Network mapping techniques for complex systems Biogeographical patterns and climate regions Evolutionary transitions in fossil records Higher-order network modeling Recent publications demonstrate strong emphasis on ecological and evolutionary applications of network science, with themes spanning from paleontological analyses to contemporary climate impacts on species distribution. Teaching includes coordination of the Design-Build-Test project course and Information Theory, Networks and Markets.