جست‌وجوی استاد و پژوهشگر

• Image Analysis
• Artificial Intelligence
• Deep Learning
• +۵ مورد دیگر

Joakim Lindblad is a Professor at the Department of Information Technology, Uppsala University , and holds affiliated roles as Senior Research Associate at the Mathematical Institute of the Serbian Academy of Sciences and Arts, and Head of Research at Topgolf Sweden AB. With over two decades of expertise in image analysis and machine learning , his work bridges computational methods with biomedical applications. Key affiliations: Uppsala University, Serbian Academy of Sciences, Topgolf Sweden Specializations: Deep Learning, Multimodal Image Registration, Quantitative Microscopy His research focuses on reliable image processing frameworks that integrate intensity and spatial information , particularly for biomedical applications . Recent publications highlight innovations in autofluorescence-based cancer detection , self-supervised one-class learning for sparse instance identification, and rotation-equivariant CNNs for robust analysis of cytology images. Recent article trends demonstrate expertise in multimodal image analysis (2024: 3 papers), oral cancer detection (2025: 2 papers), and multiscale biomedical imaging . His 2025 work on the Uppsala Storytelling Dataset introduces novel frameworks for multimodal dataset creation in AI research. While no scientific awards are explicitly mentioned, his extensive publication record (2000-2025) across top venues like Pattern Recognition , PLOS ONE , and IEEE Transactions indicates significant academic impact. His methodological contributions span stochastic distance transforms , fuzzy set defuzzification , and multimodal image registration techniques. Collaborative work with researchers like Nataša Sladoje and interdisciplinary teams has produced innovations in automated cytology analysis , TEM image enhancement , and AI-driven medical diagnostics . His 2021-2022 projects introduced contrastive learning approaches for multimodal image registration and explainable AI frameworks for infant engagement analysis.

• Nanophotonics
• Optical Tweezers
• Active Matter
• +۴ مورد دیگر

Giovanni Volpe is a Professor at the Department of Physics, University of Gothenburg. His research focuses on nanophotonics, optical tweezers, active matter, and machine learning applications in microscopy and neurodegenerative diseases. He leads the Soft Matter Lab (http://softmatterlab.org/) and collaborates internationally in interdisciplinary projects. His work bridges physics, biology, and AI, addressing challenges in nanoparticle manipulation, biomedical imaging, and neurodegenerative disease modeling. Key research areas include optical trapping of nanoparticles, self-assembly of colloidal systems, and leveraging deep learning for microscopy and sensor technologies. Recent publications span neurodegenerative disease pathways, advanced optical microscopy techniques, and plasmonic sensor development. Volpe's team has pioneered methods in computational neuroscience and nanotechnology. His lab's innovations include novel optical tweezers control algorithms and neural network models for analyzing complex biological systems. Collaborations span materials science, biophysics, and cognitive neuroscience, with applications in healthcare and environmental monitoring.

• artificial intelligence
• image analysis
• deep learning
• +۸ مورد دیگر

Natasa Sladoje is a Professor in Computerized Image Analysis at the Department of Information Technology, Uppsala University. She is affiliated with the Vi3 and Image Analysis research group and leads the MIDA research group. Her work spans artificial intelligence, biomedical image analysis, deep learning, and algorithm development, with applications in medical imaging and life sciences. Her research focuses on developing advanced image analysis methods, particularly using machine and deep learning, to enable automated analysis of image data in science and everyday life. Key areas include medical image analysis, image registration, segmentation, pattern recognition, and discrete geometry. She applies these techniques to critical domains such as oral cancer detection, cytology, and multimodal imaging. The recent publications highlight a strong trend in AI-driven medical diagnostics, particularly in cancer detection using whole slide images, self-supervised learning for sparse instance detection, and contrastive learning for multimodal image registration. Her work also emphasizes reproducibility and benchmarking in bioimage analysis through frameworks like BIAFLOWS and public datasets like HISTOBREAST. She has no listed scientific awards in the provided text. Natasa Sladoje supervises research within the MIDA group and collaborates extensively on projects involving bioimage analysis, deep learning, and medical applications. While specific grant details are not mentioned, her leadership in collaborative frameworks and publication output suggests active involvement in funded research initiatives. She leads the MIDA (Medical Image Analysis) research group, which focuses on developing and applying novel image analysis tools for biomedical applications, particularly in cancer diagnostics and multimodal imaging.

Daniel Daleyمشاهده پروفایل

استاد

• Biochemistry
• Protein Folding
• Bacterial Cell Biology
• +۳ مورد دیگر

Daniel Daley is a Professor at the Department of Biochemistry and Biophysics, Stockholm University . His research group focuses on protein trafficking, folding, and assembly in bacterial cell factories , providing molecular insights into fundamental processes like protein secretion and cell division, with applications in engineering more efficient bacterial systems. His educational background includes a B.Sc. Hons and PhD in Biochemistry from the University of Western Australia . He is also a co-founder of biotech startups CloneOpt and Mycropt . Nationality: Australian (implied by education) Contact: daniel.daley@dbb.su.se Workplace: Room A433, Svante Arrhenius väg 16, Stockholm University Dr. Daley’s research integrates biochemistry, molecular biology, and advanced imaging techniques to study Gram-negative bacteria. His work on the divisome revealed its concentric ring structure via super-resolution microscopy, while his studies on chaperones like YfgM uncovered their roles in protein trafficking and substrate identification. His team also pioneered methods for optimizing protein production through translation initiation region engineering and codon substitution strategies. Key themes in his publications include: Cell division mechanics (divisome dynamics, FtsZ/FtsN separation) Protein folding and trafficking (YfgM substrates, SecYEG translocon) Biotechnological tools (TARSyn, CRISPRi validation) Membrane protein production (codon optimization, translation initiation)

• Bioinformatics and Computational Biology
• Computer Graphics and Computer Vision
• Medical Imaging

Kimmo Kartasalo is a Senior Research Specialist and Assistant Professor at the Department of Medical Epidemiology and Biostatistics , Karolinska Institutet , Sweden. His research focuses on the intersection of Artificial Intelligence , Bioinformatics , and Medical Imaging , particularly in cancer diagnostics. Current roles: Senior Research Specialist (2024-), Assistant Professor (2024-2030) Supervision: Sol Erika Boman (2023), Kelvin Szolnoky (2022) His work emphasizes deep learning for histopathology analysis, including prostate cancer grading, breast cancer spatial gene expression prediction, and multi-stain whole-slide imaging. He leads projects in 3D tissue reconstruction , virtual reality histology visualization , and AI-assisted diagnostic uncertainty estimation . Collaborations span international institutions and include algorithm benchmarking challenges like PANDA and ACROBAT. Key methodological contributions include physical color calibration for digital pathology scanners, conformal prediction frameworks for diagnostic reliability, and open-source tools like OpenPhi for whole-slide image processing. His publications appear in top journals including Nature Medicine , Cancer Research , and European Urology .

Jaakko Patrakkaمشاهده پروفایل

استاد مدعو

• Glomerular Diseases
• Kidney Disease
• Molecular Biology
• +۳ مورد دیگر

Jaakko Patrakka serves as an Adjunct Professor of Pathology and Docent at Karolinska Institutet, leading the Renal Glomerulus Biology and Diseases research group within the Department of Laboratory Medicine. His primary focus is deciphering molecular pathways in glomerular diseases—the predominant cause of end-stage renal disease—using transgenic models and single-cell technologies to advance diagnostics and therapeutics. Dr. Patrakka's research program centers on glomerular biology and disease mechanisms , with emphasis on podocyte function, glomerular injury pathways, and kidney cell heterogeneity. His group pioneers single-cell RNA sequencing applications to identify novel cell types and molecular targets, bridging basic science with clinical translation for chronic kidney disease. Analysis of his 15 most recent publications reveals a strategic shift toward multi-omics integration and computational pathology , particularly in leveraging deep learning for morphological analysis. Collaborations with AstraZeneca highlight his commitment to drug discovery , while single-cell studies consistently uncover species-specific and disease-stage-specific molecular signatures. No individual scientific awards, fellowships, or medals are explicitly listed in Dr. Patrakka's public profile. Dr. Patrakka directs a multidisciplinary team comprising research specialists and postdoctoral fellows, fostering innovation in kidney research. His group's industry partnership with AstraZeneca accelerates therapeutic development, and his work has attracted significant funding, including a 2025 Swedish Kidney Foundation award of SEK 3.4 million for Karolinska Institutet's kidney research initiatives. The Renal Glomerulus Biology and Diseases laboratory employs cutting-edge methodologies including CRISPR/Cas9 in zebrafish, transgenic mouse modeling, spatial transcriptomics, and super-resolution imaging. Current projects focus on NPR3 receptor signaling in glomerular disease, Klotho-mediated cytoprotection, and dendrin's role in IgA nephropathy, positioning the group at the forefront of nephrology research.

Ilaria Testaمشاهده پروفایل

استاد

• Biophysics
• Neuroscience
• Chemistry
• +۳ مورد دیگر

Ilaria Testa is a Professor in Applied Physics at KTH Royal Institute of Technology, affiliated with the Unit of Biophysics and located at the Science for Life Laboratory (SciLifeLab) . Her research focuses on developing advanced optical bioimaging techniques, such as super-resolution microscopy, to study protein interactions and dynamics in biological systems. She leads the TestaLab , which builds cutting-edge microscopes to visualize nanoscale structures and cellular processes in real-time. Research Interests: Super-resolution microscopy (RESOLFT, STED) Protein dynamics in neurons and synaptic transmission Development of novel imaging technologies (e.g., event-triggered microscopy, STARSS) Her work bridges physics, chemistry, and neuroscience, aiming to uncover fundamental biological mechanisms relevant to health and disease. The lab collaborates on projects involving rotational dynamics of cellular complexes and imaging in live brain tissues. Teaching/Courses: Examiner for Degree Project in Applied Physics (Second Cycle) Teacher for Experimental Physics and Physics of Biomedical Microscopy Labs/Teams: TestaLab at SciLifeLab, part of KTH’s Department of Applied Physics.

Carla Brunnerمشاهده پروفایل

پژوهشگر

• Quantum Optics
• Ultrafast Spectroscopy
• Plasmonics
• +۷ مورد دیگر

Carla Brunner is a doctoral student in the Ultrafast Nanoscience group at the Department of Physics, Umeå University. Her research focuses on the interaction of orbital angular momentum of light and magnetic materials using ultrafast spectroscopy, with applications in quantum optics and plasmonics. Education: B.Sc. in Physics (Mass Photometry for protein mass measurement), M.Sc. in Physics (entangled photon triplet states in tapered nanofibers). Current research involves developing an ultrafast pump-probe setup to study magnetism-plasmon interactions with temporal resolution. Research interests span quantum states of light, biochemistry applications like super-resolution microscopy, and nanoparticle dynamics in glycocalyx systems. Member of the Ultrafast Nanoscience group led by Prof. Nicoló Maccaferri at Umeå.

• Biochemistry
• Neuroscience
• Physical Chemistry
• +۷ مورد دیگر

Vladana Vukojevic is an Associate Professor of Biochemistry and Principal Researcher at Karolinska Institutet's Department of Clinical Neuroscience, where she leads the Experimental Alcohol- and Drug Dependence Research group. She holds a PhD in Physical Chemistry from the University of Belgrade (2000) and earned her Docent title from Karolinska Institutet in 2011. Her research focuses on cellular mechanisms underlying alcohol use disorder, amyloid diseases, and neuropeptide signaling. Her primary research investigates molecular mechanisms of addiction through quantitative fluorescence microscopy techniques. Key areas include: Opioid receptor dynamics in alcohol dependence Amyloid-β aggregation in Alzheimer's disease Hypothalamic-pituitary-adrenal (HPA) axis modeling Development of advanced fluorescence correlation spectroscopy Vukojevic's publications demonstrate consistent focus on neuropharmacology and biophysical methods. Recent work emphasizes: Nanoscale receptor organization in addiction Amyloid plaque detection methods Transcription factor dynamics Computational modeling of stress responses She teaches advanced analytical methods through doctoral courses including Functional Fluorescence Microscopy Imaging in Biomedical Research and contributes to pedagogical development at Karolinska Institutet and Hokkaido University.

Vinay Swaminathanمشاهده پروفایل

مدرس ارشد

• Cell Mechanobiology
• Cancer Microenvironment
• Quantitative Microscopy
• +۵ مورد دیگر

Vinay Swaminathan is a Senior Lecturer and Principal Investigator at Lund University, affiliated with the Wallenberg Centre for Molecular Medicine , Lund University Cancer Centre (LUCC) , and NanoLund . His research focuses on cell mechanobiology , particularly how mechanical environments regulate cellular functions in cancer progression and tissue homeostasis. Research Themes: Mechanotransduction 3D Cancer Models Integrin-Actin Dynamics Multimolecular Adhesion Structures Quantitative Microscopy Key contributions include ECM-stiffness sensing , septin regulation in focal adhesions , and pol-diSPIM microscopy . He supervises PhD students in projects related to HER2-targeted immunotherapy and lipid-mediated siRNA delivery , funded by Mrs. Berta Kamprad's Cancer Foundation . His work aligns with UN Sustainable Development Goals for health and environmental innovation .

Staffan Strömbladمشاهده پروفایل

استاد

• Cancer Cell Biology
• Cell-Matrix Interactions
• Mechanotransduction
• +۴ مورد دیگر

Staffan Strömblad is a Professor at Karolinska Institutet in the Department of Medicine, Huddinge, where he leads the Cell Biology of Cancer research group. He also serves as Scientific Director of the Live Cell Imaging Core Facility and is a Member of the Nobel Assembly. His research focuses on how extracellular matrix (ECM) interactions influence cancer progression, cellular migration, and mechanotransduction signaling pathways. Research Interests: Strömblad investigates ECM stiffness-induced oncogenic transformation, Rho GTPase-regulated cell migration dynamics, PAK4 kinase in senescence bypass, and breast cancer metastasis. His work integrates live-cell imaging, molecular biology, and biomechanical analyses to uncover mechanisms driving tumor aggressiveness. Publication Trends: Recent articles emphasize ECM biomechanics, PAK4 signaling in cancer, high-content migration imaging, and transcriptional reprogramming during tumor progression. Key themes include mechanotransduction, senescence escape, and metastasis. Advising & Funding: He mentors PhD students (e.g., Christos Vogiatzakis, Feifei Yan) and secures grants from the Swedish Research Council, Swedish Cancer Society, and Worldwide Cancer Research. His lab uses advanced microscopy to study real-time cell dynamics. Infrastructure: As director of the Live Cell Imaging Facility, he oversees cutting-edge microscopy resources for BSL1/BSL2 cellular and tissue imaging, supporting quantitative analyses of cell behavior.

• Cell Division
• Embryonic Development
• Nuclear Organization
• +۴ مورد دیگر

Jan Ellenberg is a Professor at the Department of Medical Biochemistry and Biophysics, Karolinska Institutet, leading a research group focused on uncovering the molecular and physical principles governing early embryonic division and nuclear organization. His work utilizes advanced fluorescence-based imaging technologies to study these processes in a non-invasive and quantitative manner. Previously, his group at EMBL Heidelberg conducted large-scale RNAi screening to identify cell division genes, developed high-throughput live-cell imaging methods, and created a protein atlas of the human dividing cell. They also employed super-resolution microscopy to resolve nuclear pore complex structures and analyze chromatin dynamics. The group is now based at Karolinska Institutet and SciLifeLab, where they aim to deepen understanding of mitotic division in mammalian embryos and nuclear organization through cutting-edge imaging and computational approaches. Research spans developmental biology, biophysics, and bioimaging technologies.

• Biophysics
• Cellular Biology
• Ion Pump Mechanisms
• +۳ مورد دیگر

Hjalmar Brismar is a Professor of Experimental Biological Physics at the Department of Applied Physics, KTH Royal Institute of Technology. He also serves as Director of the Cellular and Molecular Imaging Platform at the Science for Life Laboratory and coordinates the National Microscopy Infrastructure (NMI). His research focuses on understanding cellular dynamics through the study of Na,K-ATPase ion pumps and advanced microscopy techniques. He holds a CivIng (1991) and PhD (1996) in Engineering Physics from KTH, followed by postdoctoral training at Harvard University. Research interests include Na,K-ATPase signaling, calcium oscillations, and the development of super-resolution microscopy. Key projects involve the pump's role in cellular stress response and apoptosis, as well as innovations in microscopy for biomedical applications. His team collaborates across KTH and Karolinska Institutet, integrating light microscopy with cell and molecular biology. Recent articles highlight advancements in imaging techniques, ion pump regulation, and pathological mechanisms in kidney and neurological diseases. Awards include membership in the Royal Swedish Academy of Engineering Sciences (2010) and leadership roles in national and international microscopy initiatives. Brismar has supervised 15 PhD students, 8 Licentiate candidates, and 48 M.Sc. theses, reflecting his extensive mentorship in biophysical research. Labs/Teams: Leader of the national super-resolution microscopy infrastructure at SciLifeLab, Swedish node in EurobioImaging, and core member of the Brismar Lab focusing on cellular biophysics and imaging innovation.

• Biophotonics
• Nanophotonics
• Fluorescence Spectroscopy
• +۴ مورد دیگر

Jerker Widengren is a Professor at the Royal Institute of Technology (KTH) within the Department of Physics, School of Engineering Sciences (SCI). His research focuses on advanced optical techniques in biophysics, nanophotonics, and biomedical imaging. He specializes in fluorescence spectroscopy, single-molecule imaging, and the development of novel upconversion nanoparticles for applications in deep-tissue imaging and cancer diagnostics. Widengren teaches courses such as Nanophotonics and Bionanophotonics , Fluorescence Spectroscopy for Biomedical Studies , and Experimental Biophysics , emphasizing practical skills and cutting-edge methodologies. His work bridges fundamental physics with biomedical applications, particularly in improving imaging resolution and minimizing phototoxicity in live-cell studies. Recent research highlights include advancements in MINFLUX microscopy, STED nanoscopy, and the design of low-cost NIR imaging sensors. Widengren’s contributions have implications for cancer biomarker detection, energy transduction in biological systems, and the optimization of fluorescent probes for clinical use.

• AI in Biology
• Bioimaging Analysis
• Data-Driven Science
• +۳ مورد دیگر

Wei Ouyang is an Assistant Professor in the Department of Applied Physics at KTH Royal Institute of Technology. He leads the AICell Lab , funded by the Data-Driven Life Science Fellow program, focusing on developing AI systems for data-driven cell and molecular biology. The lab's work emphasizes integrating advanced computational tools with biological imaging to advance understanding of cellular processes. His research interests include bioimaging analysis , deep learning applications , and cloud-optimized data formats . Notable contributions include open-source platforms like ImJoy and Pycro-Manager , which enhance accessibility and reproducibility in microscopy and bioinformatics. Recent publications highlight innovations in AI-driven microscopy tools , automated imaging frameworks , and data-sharing platforms . Key projects include the ESPressoscope for portable microscopy and the BioImage.IO Chatbot for community-driven bioimaging support. Dr. Ouyang teaches the Data-driven Life Sciences course at KTH and oversees the Degree Project in Applied Physics . His work bridges computational methods with biological discovery, fostering collaborative advancements in life sciences.