جستجوی استاد راهنمای دانشگاهی

Saleh Javadi is a Senior Lecturer at the Department of Mathematics and Natural Sciences at Blekinge Institute of Technology (BTH) in Karlskrona, Sweden. He is actively engaged in research and teaching within the field of systems engineering. His educational background includes: B.Sc. in Electrical-Control Engineering from Amirkabir University of Technology (2009) M.Sc. in Electrical, Electronic and Systems Engineering from The National University of Malaysia (2013) Ph.D. in Systems Engineering from Blekinge Institute of Technology (BTH) (2021) Saleh Javadi's research focuses on signal processing, machine learning, and computer vision , with applications spanning remote sensing, intelligent transportation systems, and AI-driven industrial optimization. His work bridges theoretical advancements with practical implementations, particularly in SAR imagery analysis, drone-based agricultural monitoring, and traffic surveillance systems. His recent publications demonstrate a strong focus on remote sensing technologies, particularly Synthetic Aperture Radar (SAR) image processing and analysis. There's a clear trend toward applying machine learning techniques to solve complex problems in aerial and satellite imagery, traffic monitoring, and agricultural applications. His research shows interdisciplinary connections between computer vision, signal processing, and practical engineering applications. Saleh Javadi has received significant recognition for his innovative work: Innovator of the Year award (SKAPA – Innovation Prize in Memory of Alfred Nobel) in Blekinge for innovative efforts in optimizing and reducing energy consumption in industries by using artificial intelligence ÅForsk Entrepreneur's prize at the Swedish Innovation Council Day – Swedish Incubators & Science Park's annual conference in May 2019 Dr. Javadi is involved in practical applications of his research through projects such as "Artificiell intelligens AI kan reducera ogräsfrön i utsäde" (ongoing) and "Bekämpa Renkavle med hjälp av drönare och Artificiell Intelligens (AI)" (completed). His work demonstrates a strong commitment to translating academic research into real-world solutions that address industrial and environmental challenges. His research appears to be conducted within a collaborative framework, working with colleagues on drone technology, SAR image analysis, and AI applications across multiple domains including agriculture, maritime monitoring, and transportation systems.

• Systems engineering
• Signal processing
• Machine learning
• +۱ مورد دیگر

Erchan Aptoula is a Professor of Computer Science at Sabanci University's Faculty of Engineering and Natural Sciences in Istanbul, Türkiye. He is affiliated with the Computer Vision and Pattern Analysis Laboratory (VPALab) and actively conducts research in digital image analysis, computer vision, and deep learning with a focus on remote sensing and (bio)medical data. University: Sabanci University School: Faculty of Engineering and Natural Sciences Academic Rank: Professor Email: erchan.aptoula@sabanciuniv.edu His research interests span domain generalization for remote sensing, explainable AI, medical image analysis, and precision agriculture applications. Recent work includes advancements in open-set domain generalization for hyperspectral classification, pollen classification with novel datasets, and domain adaptation techniques for SAR flood segmentation. Scientific contributions include 15+ recent publications addressing domain generalization, semantic segmentation, and uncertainty quantification in remote sensing and medical imaging. Awards include 2nd place at IEEE SIU'25 student paper awards. Projects involve international collaborations with institutions in Tunisia, Finland, and the UK, focusing on medical image understanding, crowd counting, and Ottoman document analysis.

• Digital Image Analysis
• Computer Vision
• Remote Sensing
• +۳ مورد دیگر

Markus H. Flierl is an Associate Professor at the School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology in Stockholm. He holds a PhD in Engineering from Friedrich Alexander University (2003). His career includes senior research roles at École Polytechnique Fédérale de Lausanne (2003-2005), leadership of the Max Planck Center for Visual Computing and Communication (2005-2008), and a Visiting Assistant Professorship at Stanford University (2000-2002). He has served as Program Director of the EIT Digital Master School’s 'Visual Computing and Communication' program and as Associate Editor for the IEEE Transactions on Circuits and Systems for Video Technology. Education: PhD in Engineering, Friedrich Alexander University, 2003 Studies at Friedrich Alexander University (1999-2002), EPF Lausanne (2003-2005), and Stanford University (2005-2008) Research Interests: Focused on visual computing, machine learning, and information theory. Key areas include distributed coding of dynamic scenes, multiview video coding, motion-compensated transforms, and applications in video compression and multimedia systems. His work explores efficient signal processing techniques for video and 3D visual search, with recent contributions in drone-based environmental monitoring and adversarial training methods. Awards: SPIE VCIP Young Investigator Award (2007) Teaching & Grants: Teaches courses on image/video processing, information theory, and multimedia systems. His research is supported by Ericsson, the Swedish Research Council, the European Commission, and KTH’s Digitalization Platform. He advises PhD and master’s students in visual computing and communication. Labs & Teams: Leads the Visual Computing and Communication research group at KTH, collaborating with industry partners like Ericsson and Qamcom. Former members include researchers now at Tobii AB and the University of Iceland.

• Visual Computing and Communication
• Machine Learning
• Information Theory
• +۳ مورد دیگر

Mats Olvmo is a Lecturer at the Department of Geosciences, University of Gothenburg. His academic career spans over three decades, with a focus on geomorphology, glacial geology, and planetary landform studies. He holds a bachelor's degree (1983) and a doctoral degree (1989) from the University of Gothenburg, mentored by Professor Sten Rudberg. His teaching primarily revolves around geomorphology within the Geography program, integrating physical and human geography perspectives. Research interests include glaciofluvial canyons, preglacial weathered soils, and structural morphology. Since 2016, he has investigated palsa mires in northern Sweden and their response to climate change. Collaborations with institutions like Stockholm University and international planetary scientists highlight his work on Martian landform analogs and Svalbard’s periglacial environments. Key contributions span geomorphic mapping, glacial erosion quantification, and interdisciplinary studies linking geology with climate and human systems. His fieldwork emphasizes detailed terrestrial and extraterrestrial landscape analysis, with over 40 peer-reviewed publications since 1989. Education: Bachelor in Physical Geography, University of Gothenburg (1983) Doctoral Thesis: Glaciofluvial Canyons in Sweden (1989) Key Research Themes: Palsa mire degradation and climate change Martian landform analogs (Nereidum Montes) Structural morphology of Swedish bedrock Long-term landscape evolution models Collaborations: Stockholm University (Karna Lidmar-Bergström) German Aerospace Center (Mars landform studies) Swedish Permafrost Research Network Fieldwork and remote sensing techniques form the core of his methodology, with recent work emphasizing UAV lidar and multispectral imaging for palsa monitoring. His research bridges terrestrial and planetary sciences, contributing to both Earth system and Mars exploration studies.

• Geomorphology
• Glacial Geology
• Permafrost Studies
• +۳ مورد دیگر

Maria Ewerlöf is a Senior Research Coordinator at Linköping University, affiliated with the Department of Health, Medicine and Caring Sciences (HMV) and the LiU Strategic Research Area of Circulation and Metabolism (CircM). She holds a PhD in Biomedical Engineering from Linköping University (2022). Her primary roles include supporting researchers through strategic initiatives, fostering collaborations, and organizing events such as the annual CircM retreat and Scientific Forum. She also serves on union-related committees, including Saco-S and Sveriges ingenjörer. Her research focuses on biomedical optics, particularly the development of multispectral imaging techniques to evaluate skin microcirculation and wound healing. This work involves applying artificial neural networks for real-time imaging of hemoglobin oxygen saturation. She has contributed to advancements in clinical diagnostics and biomedical engineering through her publications in journals such as Journal of Biomedical Optics . Her professional activities span administrative support, research coordination, and union representation within the academic community.

• Biomedical Optics
• Medical Imaging
• Skin Microcirculation
• +۳ مورد دیگر

Felicia Akinyemi is an Associate Professor in Geomatics Research at Karlstad University, Sweden. A certified Geographic Information Systems Professional (GISP), she leads projects integrating GeoAI and remote sensing to assess land degradation and model crop types in smallholder farming systems. Her work bridges geoinformatics, environmental sustainability, and policy interfaces. University : Karlstad University, Sweden Research Focus : Land system change, Land Degradation Neutrality (SDG 15.3.1), climate change impacts on land use, and stakeholder-driven land management. Education : Habilitation (venia docendi) in Remote Sensing and Integrative Geography, University of Bern, Switzerland (2025) Research Interests : Felicia investigates land system dynamics in coupled human-natural systems, emphasizing sustainability challenges like biodiversity decline and climate change. Her work includes developing frameworks for land degradation assessment and stakeholder engagement in EU and African contexts. Scientific Awards : Marie Sklodowska-Curie Individual Fellowship (Horizon 2020) Certified GISP (Geographic Information Systems Professional) Collaborations : She collaborates with institutions in Switzerland, Germany, Sweden, South Africa, Nigeria, Benin, Burkina Faso, Rwanda, and Botswana. Key affiliations include the UNCCD Science Policy Interface, IPBES Model Intercomparison WG, and EGU Biodiversity Task Force.

• Geomatics
• Remote Sensing
• Environmental Change
• +۷ مورد دیگر

Mohit Daga is a Researcher at KTH Royal Institute of Technology, Sweden, specializing in theoretical computer science, distributed computing, and algorithmic research. He holds an MS in Computer Science from IIT Madras (2018). His current role involves research engineering and supervising master thesis projects across Machine Learning, AI, and GPU Programming. Education: MS in Computer Science, Indian Institute of Technology Madras (2018) Research Interests: His work focuses on distributed algorithms, approximation methods, and dynamic systems. He has explored applications in network analysis, optimization, and medical imaging. Recent projects include developing consensus protocols for DAG-based systems and analyzing multi-shot broadcast stability in distributed networks. Awards: Google Summer of Code Scholarship (2020) Advising & Grants: Supervised 9 master’s theses since 2020. Research internships include Cystar Labs (IIT Madras), IMDEA Networks Lab, and Xerox Research. His work on resource allocation at Xerox led to a patented solution. Labs/Teams: Contributed to projects at KTH’s Department of Computer Science and collaborated with IMDEA Networks and Cystar Labs. Part of the team developing the AciSpace CubeSat payload integration system.

• Theoretical Computer Science
• Distributed Computing
• Approximation Algorithms
• +۴ مورد دیگر

Nina Reistad is a Senior Lecturer in Atomic Physics at Lund University with significant cross-disciplinary affiliations. She holds positions at the Centre for Environmental and Climate Science (CEC), serves as a profile area member in Engineering Health and Photon Science and Technology at LTH (Faculty of Engineering), and Light and Materials at Lund University. As a Principal Investigator at the Lund University Cancer Centre (LUCC), she leads cutting-edge biomedical optics research with applications in cancer diagnostics and treatment. Her research expertise spans multiple domains: Atomic Physics and Photon Science Optical Tomography and Spectroscopy Photoacoustic Imaging for Medical Diagnostics Photodynamic Therapy for Cancer Treatment Development of Tissue-Mimicking Materials Dr. Reistad's recent publications demonstrate a strong focus on applying optical techniques to cancer diagnostics and therapy monitoring. Her work bridges physics, engineering, and clinical medicine, developing innovative non-invasive imaging methods for cancer treatment assessment and surgical monitoring. Her notable scientific awards include: Lunds universitets pedagogiska pris för framstående insatser i utbildningen (2012) LTHs bästa lärare 2007 (2007) Teknologernas pris för utmärkta lärarinsatser inom undervisningen (1992) Dr. Reistad actively leads multiple research projects including photoacoustic imaging for breast cancer diagnosis, non-surgical diagnostic tools for giant cell arteritis, and monitoring techniques for reconstructive surgery. Her work contributes significantly to UN Sustainable Development Goals related to good health and well-being, with direct clinical applications in improving cancer diagnostics and treatment monitoring.

• Atomic Physics
• Photon Science and Technology
• Optical Tomography
• +۴ مورد دیگر

Yifang Ban is a Professor and Head of the Division of Geoinformatics at KTH Royal Institute of Technology's Department of Urban Planning and Environment. She is also an Associate Director for Dissemination & Impact at Digital Futures in Stockholm. Her research focuses on Earth observation big data analytics, machine learning/deep learning applications in environmental monitoring (e.g., urbanization, wildfires, flooding), and sustainable development. She has led impactful projects such as EO-AI4GlobalChange and HARMONIA, and is ranked among the top 2% of scientists in Geological and Geomatics Engineering (2020-2023). Education: PhD from the University of Waterloo (1996), with additional leadership training (2023, University of Cambridge). Research Interests: Environmental change monitoring, satellite data fusion, AI-driven geospatial analysis, and global urban observation. Awards: Top 2% scientist recognition (Stanford/Elsevier), UN Habitat Technical Committee member, and expert in EU grant evaluations. Advising: Supervised projects on wildfire monitoring (Zeinab Shirvani, Puzhao Zhang), population predictions (Stefanos Georganos), and urbanization impacts. Grants: EO-AI4GlobalChange (Digital Futures), HARMONIA (EU H2020), SAR4Wildfire (FORMAS/ESA), and Climate Change Induced Disaster Management in Africa (EU Erasmus+). Labs/Teams: Leads the EO-AI4GlobalChange initiative and collaborates with Digital Futures, a cross-disciplinary center addressing societal challenges through digital tech.

• Earth Observation
• Machine Learning
• Remote Sensing
• +۴ مورد دیگر

Amanda Berg is an Adjunct Associate Professor at the Department of Electrical Engineering, Linköping University, affiliated with the Computer Vision Laboratory (CVL). Her research focuses on thermal imaging, computer vision, and machine learning applications in environmental monitoring and security systems. Key research areas include: Thermal-Visible Spectrum Correlation 3D Reconstruction from Satellite Data Anomaly Detection in Wild Environments Multispectral Video Analysis Wildlife Management via UAV Imagery Her work spans computer vision, anomaly detection, and thermal imaging, with recent publications on neural radiance fields, wildfire detection benchmarks, and multispectral tracking algorithms. The 15 most recent articles demonstrate a strong focus on thermal infrared applications and AI-driven image analysis.

• Computer Vision
• Thermal Imaging
• Machine Learning
• +۵ مورد دیگر

Tomas Strömberg is a Professor at the Department of Medical Technology (IMT), Linköping University, Sweden. His research and teaching focus on the intersection of engineering and medicine, particularly biomedical optics and microcirculation. He collaborates with healthcare providers and industry partners like Perimed AB to translate optical technologies into clinical and industrial applications. His research group develops optical methods for tissue characterization, including Laser Doppler techniques for blood flow measurement and multispectral imaging for oxygen saturation analysis. Key areas include Monte Carlo modeling of light transport in tissue, quantitative assessment of skin physiology, and applications of machine learning in real-time perfusion imaging. Recent publication trends highlight the use of advanced computational models, artificial intelligence, and multimodal optical systems to study microcirculatory dynamics in diseases like diabetes, lupus, and cardiovascular conditions. His work bridges theoretical modeling with clinical validation, emphasizing non-invasive diagnostic tools. As an educator, Strömberg teaches lung physiology, signal theory, and statistical methods in research, contributing to both undergraduate and graduate programs. He is part of the Biomedical Imaging and Spectroscopy; Clinical Instrument Translation (BISCIT) group, driving innovation in clinical detection and monitoring of skin diseases.

• Biomedical Optics
• Microcirculation
• Medical Imaging
• +۳ مورد دیگر

Marcus Larsson is Assistant Professor and Head of the Department of Medical Technology at Linköping University, Sweden, where he also serves as Deputy Dean. His research develops optical methods—laser speckle contrast imaging, multispectral imaging and Monte-Carlo modelling—to quantify skin capillary perfusion and oxygenation, work that has continuous funding from national and EU sources and direct translation to cardiovascular risk assessment. Education: MSc in Applied Physics and Electrical Engineering, Linköping University, 1999 PhD in Biomedical Instrumentation, Linköping University, 2006 Marcus leads the Biomedical Optics group that designs real-time, non-invasive systems combining hardware advances with machine-learning algorithms. By merging spectroscopic and laser-Doppler data his team achieves comprehensive microcirculatory maps applicable to diabetes, sepsis and population-based cohorts such as SCAPIS. He is Director of Studies for the Biomedical Engineering programme, teaching five core courses from first-year design to specialised optics and modelling, and acts as assistant supervisor for doctoral student Andisheh Etminan. Collaborative projects involve senior colleagues Göran Salerud, Tomas Strömberg and Ingemar Fredriksson and are conducted within the Department of Medical Technology, a national centre for medical technology research and education founded in 1972.

• Biomedical optics
• Microcirculation imaging
• Laser speckle contrast imaging
• +۵ مورد دیگر

Daniel Nyström is an Associate Professor at Linköping University, affiliated with the Department of Science and Technology (ITN) and the Media and Information Technology (MIT) research group. He holds a Ph.D. in Media Technology from Linköping University (2009). His teaching focuses on Digital Media, Image Reproduction, Image Quality, and Graphic Technology within the Media Technology and Engineering master’s programme. Research interests include multispectral imaging, spectral reproduction, paper optics (modeling ink-light-paper interactions), color prediction models, and appearance reproduction. His work bridges theoretical advancements and applied solutions in color science and imaging technologies. Recent publications (2021-2024) emphasize material appearance modeling, spectral reproduction techniques, and innovative printing methods using RGBW reflective inks. Key contributions include empirical BRDF modeling for goniochromatic materials and angular-dependent reflectance analysis of pigments. No scientific awards explicitly mentioned. Advising no listed students. Active in research groups exploring visualization, interaction design, and media technology applications.

• Multispectral Imaging
• Spectral Reproduction
• Paper Optics
• +۳ مورد دیگر

Alexander Bleasdale is a Postdoctoral Researcher at the Swedish University of Agricultural Sciences (SLU), focusing on integrating remote sensing, AI, and camera trapping to monitor vegetation and wildlife interactions. His work bridges environmental science with technological innovation, emphasizing low-cost, accessible methods for ecological research. Current Position: Postdoctoral Researcher, Department of Wildlife, Fish and Environmental Studies, SLU (2025–present) Previous Roles: Research Associate at Lancaster University (2024–2025), PhD in Environmental Science (2019–2024) Education: MSc Environmental Management (2017–2018), BEng Mechanical Engineering (2013–2017) His research interests include applying AI to vegetation phenology, camera trap networks for habitat monitoring, and early disease detection in agriculture. He advocates for ethical AI use and accessible environmental monitoring tools. His publications explore multispectral imaging for apple scab detection, with a focus on neural networks and sensor technology. Current projects under the Big Picture initiative aim to link camera trap and satellite data for ecosystem analysis. While no formal awards are listed, his work contributes significantly to biodiversity and agricultural research. He collaborates across institutions and integrates citizen science data in his frameworks.

• Remote Sensing
• Artificial Intelligence
• Vegetation Monitoring
• +۳ مورد دیگر

Martin Hultman is an Assistant Professor at the Department of Biomedical Engineering (IMT), Division of Biomedical Engineering (MT), Linköping University. His work centers on biomedical optics and microcirculation, with a strong emphasis on developing high-speed, real-time imaging algorithms using FPGA and GPU platforms. Department: Division of Biomedical Engineering (MT) University: Linköping University Academic Rank: Assistant Professor Email: martin.o.hultman@liu.se His research focuses on non-invasive optical techniques for assessing microvascular blood flow, particularly through laser speckle contrast imaging. These methods are applied in clinical contexts such as burn wound assessment and critical limb ischemia. He actively contributes to advancing real-time perfusion imaging with hardware-accelerated processing. The recent publications highlight a consistent trend in developing robust, speed-resolved, and depth-sensitive imaging techniques using multi-exposure laser speckle contrast imaging, wavelet analysis, and machine learning. These studies span applications in skin perfusion, coagulation monitoring, and longitudinal variability in microcirculation, reflecting a strong interdisciplinary focus at the intersection of biomedical engineering, signal processing, and clinical physiology. Scientific recognition includes: Best Research Presentation Award at Medicinteknikdagarna, awarded by the International Federation for Medical and Biological Engineering (IFMBE) and Svensk förening för medicinsk teknik och fysik (MTF) Martin Hultman collaborates closely with senior researchers such as Professor Tomas Strömberg, Senior Associate Professor Marcus Larsson, and Adjunct Associate Professor Ingemar Fredriksson. He is involved in the Biomedical Optics research group, contributing to innovations in optical imaging for clinical diagnostics. While no formal grants are mentioned, his work implies involvement in funded research projects related to real-time imaging and microcirculatory assessment. There is no indication of student advising at this time. He is part of the Biomedical Optics research team within the Division of Biomedical Engineering, which develops technologies for clinical and research applications using light-tissue interactions. The group is actively involved in translating optical methods into practical tools for healthcare, including real-time imaging systems and diagnostic algorithms.

• Biomedical Optics
• Microcirculation
• Biomedical Engineering
• +۷ مورد دیگر