جست‌وجوی استاد و پژوهشگر

Martina Maggioمشاهده پروفایل

استاد

• Computer Systems
• Control Theory
• Cyber-Physical Systems
• +۷ مورد دیگر

Martina Maggio is a Full Professor at both Saarland University's Department of Computer Science and Lund University's Department of Automatic Control. She is actively involved in ELLIIT (the Linköping-Lund initiative on IT and mobile communication) and serves as Coordinator of the LTH Profile Area on AI and Digitalization and as a member of the LU Profile Area on Natural and Artificial Cognition. Her research lies at the intersection of computer science and control engineering, with a focus on self-adaptive software, cyber-physical systems, real-time systems, and cloud computing . She applies control-theoretical methods to enhance the reliability, efficiency, and resilience of computing systems. Her work contributes to UN Sustainable Development Goals related to sustainable computing and intelligent systems. The most recent publications highlight a strong trend in resilience and security of control systems , particularly under timing faults, deadline misses, and stealthy attacks. Her research combines theoretical modeling with practical implementation, often validated through industrial case studies and real-world systems. Scientific Awards: ACM SIGSOFT Distinguished Paper Award (2020) Best Paper Award - ECRTS 2021 Outstanding Reviewer Award (2020) Best Paper Award (2018) Advising and Grants: Martina has supervised Ph.D. students such as Chiara Mandrioli and has led major research projects including ADMORPH (EU Horizon 2020), Trustworthy Cyber-Physical Pipelines (Swedish Research Council), and DYNACON . Her funding sources include European and national agencies, reflecting the high impact and interdisciplinary nature of her work. Labs and Research Teams: She collaborates with leading institutions including MIT's CSAIL and Bosch Corporate Research. At Lund, she is part of the Department of Automatic Control and contributes to AI and digitalization initiatives. Her work is embedded in large research networks such as ELLIIT and involves cross-institutional teams focused on autonomous, adaptive, and resilient systems.

Maria Andreina Francisco Rodriguezمشاهده پروفایل

استادیار

• Artificial Intelligence
• Constraint Programming
• Discrete Optimization
• +۵ مورد دیگر

Maria Andreina Francisco Rodriguez is an Assistant Professor in Artificial Intelligence at Uppsala University's Department of Information Technology, affiliated with the Optimization Group and Pharmaceutical Bioinformatics Research Group. She holds additional roles as a teacher representative on the Master Programme in Computer Science board and Department of IT board. Her research focuses on constraint programming, AI-driven decision support systems, and optimization in biomedical applications. Notable projects include automated microplate layout design for drug discovery, data-driven models for the water-energy-food-ecosystem nexus, and reinforcement learning for scientific data management. Her work bridges theoretical computer science with practical applications in healthcare, sustainability, and education. Key achievements include a Best Student Paper Award (ICTAI 2017) and Best Poster Award (CP 2015). She actively promotes inclusivity in STEM through initiatives like the EURO WISDOM Forum white paper on gender equality. Her teaching spans Artificial Intelligence, Cryptology, and programming methodologies. Supervised projects highlight interdisciplinary applications like AI in railway maintenance planning and machine learning for glioma treatment personalization. Current collaborations involve pharmaceutical bioinformatics groups and transportation optimization projects. She also leads grant initiatives in hybrid-AI methods for precision medicine and computing education research.

• Railway Energy
• Sustainability
• Traction and Braking Systems
• +۸ مورد دیگر

William Liu is a Researcher at KTH Royal Institute of Technology's Department of Vehicle Engineering and Technical Acoustics since 2020, focusing on railway energy and sustainability. He has extensive experience in railway systems development, having contributed to high-speed rail projects (up to 421 km/h) and over 20 research projects, yielding 60 publications. His work emphasizes energy efficiency, safety, and innovative systems like maglev and hyperloop. Education: He holds a Doctor of Philosophy (2017), Licentiate (2015), and Master's (2009) in Mechanical Engineering from KTH and Tianjin University. He is also a Docent in Rail Vehicle Technology (expected 2025). Research interests include traction systems, electric power supply optimization, pantograph-catenary dynamics, climate adaptation, and circular economy applications in rail transport. He teaches multiple courses, including Rail Vehicle Technology and Energy Technologies for Sustainable Transport at the bachelor and master levels, and advises doctoral students in areas like braking systems and vehicle dynamics under adverse conditions. Recent research trends in his articles focus on smart controllers for decarbonization, pantograph-catenary interaction dynamics, and hyperloop technology. He co-supervises PhD projects and mentors over 20 thesis students, addressing topics such as energy optimization for commuter trains and circular economy quantification. He is a member of the Swedish Electrical Standardization Committee and leads the KTH Delsbo Electric Team, actively shaping industry standards and next-gen rail innovation.

• Computational Science
• Scientific Computing
• Technology Research
• +۳ مورد دیگر

Dimitrios Korakovounis is a Researcher and doctoral student at KTH Royal Institute of Technology, affiliated with the Division of Computational Science and Technology. He is based at Lindstedtsvägen 5 in Stockholm, Sweden, and can be reached at dimkor@kth.se . His role involves contributing to research activities within computational methodologies and technological innovation. While specific research interests are not detailed in the provided text, his affiliation with the Division of Computational Science and Technology suggests a focus on computational methods, algorithm design, and interdisciplinary applications of technology. His doctoral studies likely align with these areas, though no explicit description of his thesis topic or ongoing projects is available. No academic awards, grants, or published articles are listed in the current information. His professional narrative emphasizes his current engagement in academic research and training at KTH.

Oskar Kvimanمشاهده پروفایل

پژوهشگر

• Bayesian phylogenetics
• Probabilistic machine learning
• Variational inference
• +۱۵ مورد دیگر

Oskar Kviman is a doctoral student at KTH Royal Institute of Technology working in the Lagergren Lab within the Division of Computational Science and Technology. His research bridges machine learning, statistics, and computational biology with a focus on developing and applying advanced probabilistic methods. His primary research interests include: Bayesian phylogenetics and probabilistic machine learning Variational inference, variational auto-encoders, and sequential Monte Carlo methods Generative AI techniques including flow matching, Schrödinger bridges, and diffusion models Computational cancer research focusing on differential expression testing and spatial transcriptomics Kviman's publication record demonstrates significant contributions to variational inference methodology, particularly in phylogenetics and generative modeling. His work spans top machine learning conferences including ICML, NeurIPS, and AISTATS, showing consistent development of techniques that improve efficiency and accuracy in probabilistic modeling. Recent publications focus on multi-marginal flow matching, variational resampling, and mixture learning in black-box variational inference. He has been recognized for his peer review contributions as a Top reviewer (10%) for AISTATS 2023. Kviman has supervised master's theses for Xindi Liu and Ricky Molén at KTH and serves as a lecturer for 'Statistical Methods in Applied Computer Science' since 2021, while previously working as a teaching assistant for 'Machine Learning, Advanced Course' and 'Deep Learning, Advanced Course'.

• Optical Engineering
• Photonics
• Materials Science
• +۳ مورد دیگر

Michael Fokine is a Professor at the Department of Physics, KTH Royal Institute of Technology. His research focuses on advanced optical materials and fabrication techniques, including semiconductor-core optical fibers, laser-based additive manufacturing of glass, and nonlinear photonics. He leads projects in femtosecond laser micromachining, 3D printing of optical components, and the development of quantum light sources using novel fiber designs. His work bridges fundamental materials science with applied photonics, addressing challenges in high-precision fabrication and optical device integration. Teaching roles include course responsibilities for Optical Measurement Technology and supervision in Engineering Physics and Applied Physics degree projects. His research has produced breakthroughs in glass 3D printing, silicon-core fiber fabrication, and fiber Bragg grating technologies. Current efforts emphasize scalable production of silica micro-optics and optofluidic systems for biosensing and high-resolution imaging. Key innovations include low-loss silicon-core fibers, laser-annealed semiconductor fibers, and CO laser systems for fiber preform manufacturing. His interdisciplinary approach combines experimental methods with computational modeling to optimize material properties and device performance. Collaborations span academia and industry, targeting applications in telecommunications, quantum optics, and biomedical engineering.

• X-ray Imaging
• Nanoparticle Bioengineering
• Biomedical Imaging
• +۳ مورد دیگر

Hans Hertz is a Senior Professor at the Royal Institute of Technology (KTH), specializing in Bio-Opto-Nano Physics. He leads research in advanced X-ray imaging technologies, with a focus on nanoparticle design and biomedical applications. His work integrates phase-contrast imaging, X-ray fluorescence tomography, and cryo-microscopy to develop non-invasive diagnostic tools for cellular and tissue analysis. Key research interests include nanoparticle bioengineering, contrast agent development for XFCT (X-ray Fluorescence Computed Tomography), and the application of phase-contrast techniques for virtual histology and tumor margin assessment. He has pioneered liquid-jet X-ray sources and high-resolution tomography systems for preclinical imaging. His recent publications highlight advancements in nanoparticle biodistribution studies, cryo-soft X-ray microscopy for cellular imaging, and hybrid XFCT-MRI contrast agents. He also contributes to industrial quality inspections using phase-contrast X-ray imaging for non-destructive material analysis. Hans Hertz has been instrumental in developing imaging solutions for tumor resection guidance and has explored applications in ancient mummy studies, demonstrating the versatility of his techniques across biomedical and archaeological domains.

Guocai Chaiمشاهده پروفایل

استاد مدعو

• Mechanical Properties of Structural Materials
• Fatigue and Fracture
• Deformation Mechanisms
• +۴ مورد دیگر

Guocai Chai is an Adjunct Professor in Engineering Materials at Linköping University, affiliated with the Department of Management and Engineering (IEI) and the Division of Engineering Materials (KMAT). He has held this position since 2011 and continues to contribute to research in mechanical properties of structural materials. His research focuses on mechanical properties of metallic materials , particularly fatigue behavior, deformation mechanisms, and microstructural analysis. He investigates how materials respond under extreme conditions such as very high cycle fatigue, cryogenic environments, and pre-straining, with applications in aerospace and oil and gas sectors. The recent publications (2024–2025) reveal a strong trend in combining experimental mechanics with advanced computational techniques , including deep learning for fatigue life prediction and multi-scale simulations of strain hardening. His work frequently involves nickel-based superalloys and high-strength aluminum alloys, targeting industrial durability and safety challenges. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: While no information is available about students or grants in the provided content, his active publication record suggests ongoing research supervision and likely involvement in funded projects within materials engineering at Linköping University. Labs and Research Teams: Guocai Chai is part of the Engineering Materials (KMAT) division, which conducts interdisciplinary research on metallic materials, ceramics, composites, and polymers. The group emphasizes experimental testing coupled with microstructural investigations to understand material performance in engineering applications.

Balaje Kalyanaramanمشاهده پروفایل

پژوهشگر ارشد

• Numerical Methods
• Partial Differential Equations
• Finite Element Methods
• +۴ مورد دیگر

Balaje Kalyanaraman is a postdoctoral fellow in the Computational Mathematics Group at Umeå University, Sweden. He received his PhD from the University of Newcastle, Australia in August 2022, with prior degrees in Mathematics and Mechanical Engineering from BITS Pilani - Goa Campus. His research spans computational mathematics with a focus on numerical methods for partial differential equations. Key areas include finite element methods, virtual element methods, hydroelasticity, and ice-shelf vibrations. His work bridges theoretical numerical analysis with practical applications in environmental science and engineering. Dr. Kalyanaraman has made significant contributions to gradient recovery techniques for virtual element methods and has developed software tools including iceFEM for hydro-elasticity problems and contributions to Gridap.jl for finite element analysis. His publications cover advanced topics in numerical methods with applications to real-world problems. His recent publications show a trend toward increasingly sophisticated numerical techniques with broader applications across scientific domains, particularly in multiscale methods and mixed formulations for complex PDEs. Dr. Kalyanaraman has received recognition through opportunities like Google Summer of Code 2021 with Gridap.jl and NumFOCUS, demonstrating the value of his technical skills to the scientific computing community. He actively shares his knowledge through detailed blog posts explaining complex numerical methods and making them accessible to other researchers. His approach combines deep theoretical understanding with practical implementation skills, making his work valuable to both theoreticians and practitioners in computational science.

• Vascular Surgery
• Abdominal Aortic Aneurysm
• Aortic Dissection
• +۳ مورد دیگر

Rebecka Hultgren is an active Adjunct Professor and Head of Department at Karolinska Institutet, affiliated with the Department of Molecular Medicine and Surgery (K1 MMK) and Ulf Hedin's research group in Vascular Surgery. Her work spans clinical and translational vascular research with a focus on abdominal aortic aneurysms (AAA) and aortic dissection, utilizing population-based registries, randomized trials, and biomechanical modeling to address critical gaps in disease management. Her research interests center on vascular disease pathophysiology, particularly AAA growth prediction, sex-specific rupture risks, and psychological comorbidities. She investigates biomechanical factors like sealing zone failure and peak wall rupture index, explores molecular mechanisms including microRNA biomarkers and vascular calcification, and pioneers eHealth interventions for anxiety management. Her work emphasizes cardiovascular risk optimization, hereditary screening, and the impact of comorbidities such as kidney disease and cancer on aortic conditions. Recent publications (2024-2025) reveal three dominant trends: advanced biomechanical modeling for rupture prediction, gender-specific outcome disparities in aneurysm repair, and psychological/cardiovascular risk management integration. Key journals include Journal of Vascular Surgery and European Journal of Vascular and Endovascular Surgery, with studies frequently involving Swedish national registries and international collaborations like the PHAST trial. While her profile indicates a Grants section, no specific funding details or student advisees were extracted from the provided text. Her leadership role and extensive publication record suggest active grant acquisition, particularly for clinical trials such as the TRAIN Health Awareness study and DAAAD screening project. She operates within Ulf Hedin's research group at Karolinska Institutet, which focuses on molecular mechanisms of vascular diseases. The group utilizes advanced imaging (PET/CT), biomechanical analysis, and population health data to investigate aneurysm progression and treatment efficacy.

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.

• Behavioral Sciences
• Neurosciences
• Psychiatry
• +۹ مورد دیگر

Predrag Petrovic is a Senior Lecturer and Senior Physician at the Karolinska Institutet 's Department of Clinical Neuroscience. His career spans clinical practice and academic research, focusing on the interplay between cognitive processes, psychiatric conditions, and neurobiological mechanisms. As Docent and leader of the Cognitive Neuropsychiatry research group, he bridges clinical observations with cutting-edge neuroimaging and behavioral studies. Employment: Senior Lecturer/Senior Physician (2017-), Karolinska Institutet Academic Credentials: PhD in Clinical Neuroscience (2002), MD (1996), Docent title (2013) Research Themes: Delusion-proneness and belief formation Sleep deprivation effects on cognition ADHD and executive function Neurodegenerative disease (Alzheimer's, frontotemporal dementia) Neural mechanisms of empathy and pain Psychoactive substances and cognition Publication Trends reveal interdisciplinary work combining fMRI , psychopharmacology , and population studies . Recent 2025 work explores machine learning applications in dementia detection and soccer player cognition , while 2024 studies examine psychedelics , chronotypes , and vaccine hesitancy through cognitive neuroscience lenses. Research Group: The Cognitive Neuropsychiatry group includes Christoph Abé (PhD), Kasim Acar (PhD Student), Orestis Floros (Clinical Assistant), and others, conducting studies on topics from soccer intelligence to resignation syndrome .

• 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.

Jonas Mindemarkمشاهده پروفایل

مدرس ارشد

• Polymer Electrolytes
• Solid-State Batteries
• Lithium-Ion Batteries
• +۱۲ مورد دیگر

Jonas Mindemark is a Senior Lecturer and Associate Professor in the Department of Chemistry at Uppsala University, affiliated with the Ångström Laboratory and specializing in Structural Chemistry. His research focuses on the development and characterization of polymer electrolytes for next-generation solid-state batteries. Institution: Uppsala University Department: Department of Chemistry - Structural Chemistry Research Lab: Ångström Laboratory His primary research interests include solid-state batteries, polymer electrolytes, ion transport mechanisms, fluorine-free electrolytes, and interfacial chemistry in energy storage systems. His work bridges experimental and computational approaches to understand and improve electrolyte performance in lithium, sodium, and multivalent batteries. The recent publications highlight a strong trend in advancing polymer-based electrolytes for high-performance, safe, and sustainable batteries. Research focuses on understanding ion coordination, improving transference numbers, developing composite materials with ceramic fillers, and designing electrolytes for high-temperature and high-voltage operation. A significant portion of the work involves innovative characterization techniques such as electrophoretic NMR and molecular dynamics simulations to probe ion transport at a fundamental level. Jonas Mindemark actively collaborates with leading researchers including Daniel Brandell, Reza Younesi, and Guiomar Hernández. His group works on both fundamental material design and practical battery integration, contributing to the development of safer, higher-energy-density energy storage solutions. The research spans from molecular synthesis to full cell testing, with a strong emphasis on sustainability through fluorine-free formulations.

• Biomaterials
• Biomedical Engineering
• Bone Regeneration
• +۹ مورد دیگر

Caroline Öhman Mägi is a Senior Lecturer at the Department of Materials Science; Applied Materials Science, Uppsala University, based at The Ångström Laboratory. Her research centers on the development and characterization of advanced biomaterials, particularly calcium phosphate cements and titanium-based alloys, for use in bone and dental implants. Her research interests lie at the intersection of materials science and biomedical engineering, with a strong focus on biomaterials for bone regeneration , mechanical properties of bone cements , degradation behavior of implants , and antibacterial material design . She investigates how material composition and microstructure influence biological response and mechanical performance, aiming to create safer and more effective medical devices. The analysis of her recent publications reveals a consistent trend toward translational research in orthopedics and dentistry. Her work spans from fundamental material characterization (e.g., fatigue, modulus, degradation) to preclinical and clinical evaluation of implants, with a particular emphasis on cranial and spinal applications. Keywords across her work include biomaterials, bone regeneration, calcium phosphate, titanium alloys, and biomechanics. She has actively contributed to the scientific community through numerous peer-reviewed publications in high-impact journals such as Materials & Design , ACS Applied Materials & Interfaces , and Acta Biomaterialia . Her research often involves interdisciplinary collaboration with engineers, biologists, and clinicians. Dr. Öhman Mägi advises and collaborates with a network of researchers and students, contributing to the training of the next generation of biomaterials scientists. While specific grant details are not provided in the text, her sustained publication output suggests successful funding acquisition. She is involved in multiple research projects related to bone cements, cranial implants, and additive manufacturing of medical devices. She is part of a research team at Uppsala University that develops and tests novel biomaterials, including low-modulus bone cements and composite implants, using advanced techniques such as micro-computed tomography (µCT), mechanical testing, and in vivo models.