جست‌وجوی استاد و پژوهشگر

Emma Söderbergمشاهده پروفایل

مدرس ارشد

• Software Engineering
• Human-Computer Interaction
• Programming Tools
• +۴ مورد دیگر

Emma Söderberg is a Senior Lecturer in the Department of Computer Science at Lund University's Faculty of Engineering with key roles as Project Manager for ELLIIT (Linköping-Lund IT initiative), Coordinator of the LTH AI and Digitalization Profile Area, and Researcher in the NEXTG2COM competence centre. She earned her academic credentials from Lund University: M.Sc. (2007), Licentiate (2011), and Ph.D. (2013) in Computer Science and Engineering, with doctoral research on semantic editors using reference attribute grammars. After a Google tenure (2013-2018) developing Chromium infrastructure, she returned to Lund to pioneer human-centered software engineering research. Her work focuses on the intersection of programming tools, software engineering, and human-computer interaction, specifically how tools can support human needs in development workflows. Recent investigations examine cognitive aspects of code review, AI augmentation (not replacement) of developer judgment, and gamification for tool feedback collection. Analysis of her 2025 publications reveals a cohesive research trajectory centered on developer behavior modeling—spanning cognitive code review frameworks, AI-supported quality assurance, educational program analysis applications, and gamified static analysis feedback systems—all emphasizing human-tool symbiosis over full automation. She actively supervises four PhD candidates: N. Korkakakis on continuous automotive software engineering (CASE-SDV) N. Hagatulah on safeguards for LLM-assisted refactoring (REFORGE) P. Palesetti on AI-driven DevOps for cyber-physical systems A. Bexell on semi-automatic code improvement (SACI) Her leadership extends to organizing NEXTG2COM workshops, delivering industry outreach talks (e.g., 'This thing called programming & AI and programming'), and contributing to UN Sustainable Development Goals through software engineering advancements. Current projects funded through 2030 address critical challenges in automotive software and AI-enhanced development environments.

Lisa Rydenمشاهده پروفایل

استاد

• Breast Cancer
• Oncology
• Metastasis Prediction
• +۴ مورد دیگر

Lisa Ryden is a Professor and Senior Consultant Surgeon at Lund University's Department of Surgery. She serves as Principal Investigator at the Lund University Cancer Centre (LUCC) and manages multiple breast cancer research projects including the Liquid Biopsy and Tumor Progression in Breast Cancer initiative and Breast Cancer Surgery projects. Dr. Ryden's research focuses on improving prediction models for regional and distant metastatic spread in breast cancer to enable personalized treatment selection. Her work integrates patient, clinical, and tumor-related data to achieve high accuracy in prediction. She characterizes archival tumor tissue from primary tumors and metastasis on protein and genomic levels, linking these characteristics to clinical outcomes. A key aspect of her research involves developing models to identify node-negative breast cancer patients who might avoid axillary surgery. Her multidisciplinary research group includes clinical PhD students, clinical researchers, biostatisticians, molecular biologists, and technical personnel. Her work contributes to UN Sustainable Development Goals related to health and well-being. Honorary Skou Professor (2019) Reutersköldska Priset i Kirurgi (Reutersköld award in Surgery) (2019) Nordiska Medicinpriset (2016) Dr. Ryden actively supervises research students and leads multiple significant projects including 'Optimizing and individualizing adjuvant radiotherapy in breast cancer' and 'The T-REX trial.' Her research has been supported by Cancerfonden, Familjen Erling-Perssons Stiftelse, Bröstcancerförbundet, and Sjöbergstiftelsen. She is actively involved in organizing conferences and workshops through LUCC, demonstrating strong leadership in the breast cancer research community with activities extending into 2025.

• Proteomics
• Mass Spectrometry
• Infectious Disease
• +۳ مورد دیگر

Aaron Scott is a Bioinformatician and Doctoral Student at Lund University's Faculty of Medicine, Department of Infection Medicine (BMC). He actively contributes to proteomics research in infectious diseases, leveraging advanced mass spectrometry and computational methods. Education: PhD candidate in Infection Medicine Scott specializes in clinical proteomics, focusing on blood plasma and tissue-specific dynamics. His work spans biomarker discovery, peptidomics, and computational approaches to infectious disease biology. Current projects integrate AI with clinical data for sepsis subphenotyping. Recent publications highlight his contributions to proteome mapping (Cell 2025), peptide clustering methodologies (Nature Communications 2024), and digital twin modeling in sepsis (medRxiv 2024). His research emphasizes precision diagnostics and understanding host-pathogen interactions. Scientific Award: Best Poster Award (2023 Nov 17) As a researcher in active projects, Scott collaborates on computational methods development and clinical applications in proteomics. His work bridges technical innovation in mass spectrometry with real-world infectious disease challenges.

Adam Linderمشاهده پروفایل

استاد

• Critical Care Medicine
• Infectious Diseases
• Proteomics
• +۳ مورد دیگر

Adam Linder is a Professor and Principal Investigator at the Department of Infection Medicine , part of Lund University's Faculty of Medicine . He serves as a Consultant Physician, Researcher, and Supervisor in translational sepsis research. Key roles: Project Manager for SEBRA (Sepsis and Bacterial Resistance Alliance), Coordinator for Heparin Binding Protein studies in cardiothoracic surgery Active in clinical trials and biomarker development for sepsis and severe infections Research Interests focus on: Sepsis pathophysiology and treatment optimization Proteomic profiling of plasma and tissue-specific biomarkers Machine learning integration for disease subphenotyping Postoperative complication prediction models Recent Research Output includes trials on septic shock fluid management ( Acta Anaesthesiologica Scandinavica ), proteomics atlases ( Cell ), and cross-sectional analyses of sepsis care quality across Europe. Supervision includes doctoral projects on: Kidney stone disease and acute care Biomarker-driven prediction of long-term infection complications

Lisa Dellmuthمشاهده پروفایل

استاد

• Public Opinion
• Legitimacy
• Global Governance
• +۷ مورد دیگر

Lisa Dellmuth is a Professor at the Department of Economic History and International Relations, Stockholm University. She co-directs the Stockholm Center for Global Cooperation (SCGG) and leads the PhD program in International Relations. Her work focuses on public opinion, legitimacy, and redistribution in global governance, employing experimental and quantitative methodologies. Education: PhD in Political Science (2011, University of Mannheim) Postdoctoral Fellowships: Stockholm Resilience Center (2015–2016), Stockholm University Political Science Department (2011–2014) Her research explores legitimacy politics, elite communication, and climate governance, with books such as Legitimacy Politics: Elite Communication and Public Opinion in Global Governance (Cambridge University Press, 2023) and Citizens, Elites, and the Legitimacy of Global Governance (Oxford University Press, 2022). She coordinates major projects funded by Formas, Mistra, EU, Riksbankens Jubileumsfond, and the Swedish Research Council. Recent publications address peer opinion, ideological divides, non-state actor participation, and climate adaptation. Awards include the Michael Endres Prize 2021 , Sage Award 2012 , and UACES Honorable Mention 2022 . Editorial Roles: European Journal of Political Research, Interest Groups & Advocacy Program Committees: Political Economy of International Organizations (PEIO) annual conferences

Laura Carrollمشاهده پروفایل

پژوهشگر ارشد

• Bioinformatics
• Computational Biology
• Genomics
• +۶ مورد دیگر

Laura Carroll is a DDLS Fellow at Umeå University , Sweden, specializing in computational microbiology and genomic epidemiology. Her lab develops bioinformatic methods to combat bacterial pathogens through advanced data analysis. Current research focuses on phylodynamic modeling of zoonotic pathogens Development of machine learning tools for genomic phenotype prediction Creation of multi-omics methods to assess pathogen virulence Her work bridges computational and experimental microbiology, emphasizing data accessibility and public health applications through teaching and outreach. Recent publications highlight expertise in antimicrobial resistance , taxonomic classification , and outbreak detection using genomic data. Scientific Awards: DDLS Fellowship Her research combines genomic epidemiology , machine learning , and multi-omics approaches to enhance pathogen surveillance and risk evaluation systems.

Erika Comascoمشاهده پروفایل

دانشیار

• Psychoneurobiology
• Women's mental health
• Hormonal effects on brain
• +۵ مورد دیگر

Erika Comasco is an Associate Professor at Uppsala University's Department of Neuroscience and a SciLifeLab Fellow. Her research focuses on the psychoneurobiology of women's mental health, particularly examining how gonadal hormones influence behavior and mental health through molecular, genetic, endocrine, pharmacological, neurophysiological and neuroimaging approaches. Her primary research interests include the molecular underpinnings of gonadal hormones' influence on women's behavior and mental health, with emphasis on characterizing biomarkers for sex-specific disorders like premenstrual dysphoric disorder. She also investigates the effects of early-life stress and alcohol exposure on brain and behavior, examining (epi)gene-environment interactions in both rodent models and human population-based samples, with special focus on adolescence as a critical period for vulnerability to alcohol use and misuse. Her publication record demonstrates consistent research activity from 2012 through 2025, with a clear focus on women's mental health across the reproductive spectrum. Her work spans neuroimaging studies, genetic analyses, pharmacological interventions, and systematic reviews, with particular emphasis on premenstrual dysphoric disorder, hormonal effects on brain function, and the biological aspects of mood disorders related to reproductive transitions. Dr. Comasco leads a research group that includes multiple postdoctoral researchers and PhD students. Her collaborative network is extensive, with frequent co-authorship with researchers from Uppsala University and international institutions, particularly in studies examining hormonal influences on brain and behavior.

• infinite-dimensional differential geometry
• geometric hydrodynamics
• shape analysis
• +۳ مورد دیگر

Klas Modin is an Assistant Professor at the Department of Applied Mathematics and Statistics within the Department of Mathematical Sciences at Chalmers University of Technology in Gothenburg, Sweden. His research spans multiple disciplines at the intersection of mathematics, physics, and computer science, with a particular focus on geometric approaches to complex systems. Dr. Modin's research interests encompass a broad spectrum of mathematical and computational fields. His primary focus lies in infinite-dimensional differential geometry , geometric hydrodynamics , and shape analysis , which he applies to problems in computational mathematics , deep learning , and medical image analysis . His work often bridges theoretical mathematics with practical computational applications, particularly in fluid dynamics and image processing. The geometric perspective he brings to these fields has yielded novel insights into the mathematical structures underlying complex physical and computational systems. His recent publications demonstrate a strong trend toward interdisciplinary research that combines geometric mechanics with modern computational techniques. Many of his papers focus on optimal transport theory , geometric integration methods , and computational anatomy , with applications ranging from fluid dynamics to medical imaging. His work often develops novel mathematical frameworks that preserve important geometric structures in numerical simulations. Dr. Modin has received several prestigious awards for his research: Ingvar Carlsson Award from SSF (2013) Marie Sklodovska-Curie Individual Fellowship from EU's Horizon 2020 (2015) Starting Project from the Swedish Research Council (2017) Wallenberg Academy Fellow (WAF) by the Royal Swedish Academy of Sciences (2019) His research is supported by multiple grants from major funding organizations, including the Swedish Research Council, the Wallenberg Academy, and the European Union. Dr. Modin leads several research projects, including "Infinite-dimensional Lie groups in hydrodynamics and beyond" (2024) and "Långtidsbeteende för tvådimensionella inkompressibla flöden via kvantisering" (2023-2026), which explore fundamental mathematical structures in fluid dynamics and computational methods. Dr. Modin is actively involved in the geometric mechanics and computational mathematics research communities, collaborating with researchers across Europe and beyond. His work has significant implications for both theoretical mathematics and practical applications in medical imaging and fluid dynamics simulation.

• Monolithic Microwave Integrated Circuits (MMIC)
• Millimeter-wave and Terahertz Electronics
• Packaging Technologies for High-Frequency Circuits
• +۲ مورد دیگر

Vessen Vassilev serves as an Associate Professor in the Department of Microtechnology and Nanoscience at Chalmers University of Technology, Sweden, where he has been affiliated since 1998. His academic journey began at Sofia Technical University before transitioning to Chalmers for advanced degrees and his current research leadership role. His educational qualifications include: M.Sc. in Radio Communications, Sofia Technical University, Bulgaria (1995) M.Sc. in Digital Communications, Chalmers University of Technology (1998) Ph.D., Department of Radio and Space Science, Chalmers University of Technology (2003) Professor Vassilev's research focuses on pioneering Monolithic Microwave Integrated Circuits (MMIC) for frequencies exceeding 100 GHz, with dual emphasis on circuit design and specialized packaging technologies. His work extends to millimeter-wavelength sensor development, most notably an automotive polarimetric radar system validated in real traffic conditions for road surface characterization—a breakthrough enabling differentiation between wet, icy, and dry pavement through advanced electromagnetic sensing. Analysis of his recent publications (2021-2025) reveals concentrated expertise in D-band/E-band communications, automotive radar applications, and innovative packaging solutions. Key thematic threads include road surface sensing using polarimetric techniques, high-speed wireless data transmission above 100 GHz, and gap waveguide antenna integration—demonstrating consistent contributions to next-generation millimeter-wave systems for both communication and safety-critical applications. He maintains active research within Chalmers' Microwave Electronics Laboratory, driving projects that bridge theoretical circuit design with practical implementation in radio astronomy heritage systems and emerging automotive technologies.

• Modeling (multivariate methods, reactor modeling, experimental design)
• Catalytic reactors (exhaust gas purification, automotive catalysis)
• Internal combustion engines
• +۶ مورد دیگر

Jonas Sjöblom is an Associate Professor at Chalmers University of Technology, affiliated with the Transport, Energy and Environment division. His research focuses on connecting modeling techniques, catalytic reactor design, internal combustion engines, and emission control to create environmentally friendly vehicles and improve air quality. Modeling: Multivariate methods, reactor modeling, experimental design Emissions: Engine, brake, and tire particulate matter Air Quality: Control instruments and policy implications Projects: Involved in 40 initiatives, including hydrogen propulsion, emission regulations, and virtual calibration systems His recent work includes computational modeling of catalytic systems, characterization of alternative fuel emissions, and applications of machine learning in trip prediction. Collaborations span Chalmers departments, Gothenburg University, and industry partners like AFA Försäkring and Energimyndigheten.

• High Voltage Engineering
• Dielectric Properties
• Electrical Insulation
• +۳ مورد دیگر

Olof Hjortstam serves as an Adjunct Professor in the Department of Electrical Power Engineering at Chalmers University of Technology. His research primarily focuses on high voltage engineering, dielectric properties, and the application of machine learning techniques to electrical insulation problems. His research interests span high voltage engineering, dielectric properties, electrical insulation systems, physics-informed machine learning applications, charge dynamics in various media, and partial discharge phenomena. Hjortstam's work demonstrates a strong interdisciplinary approach, combining traditional electrical engineering principles with modern computational techniques. His recent publications reveal a consistent focus on understanding electrical insulation behavior under various conditions, particularly examining how humidity affects charge formation and accumulation in air and at material interfaces. A notable trend in his work is the innovative application of physics-informed neural networks to extract meaningful physical parameters from high voltage experimental data, bridging the gap between theoretical models and empirical observations. Hjortstam actively collaborates with researchers across multiple institutions, as evidenced by his co-authorship on numerous conference proceedings in leading IEEE dielectrics conferences. His work contributes significantly to advancing our understanding of electrical insulation systems under DC stress, which has important implications for the development of next-generation high-voltage DC transmission systems.

Maria Magnussonمشاهده پروفایل

مدرس

• Computer Vision
• Image Processing
• Scene Flow Estimation
• +۳ مورد دیگر

Maria Magnusson is a Lecturer at the Computer Vision Group within the Department of Systems Engineering at Linköping University . Her work bridges artificial vision systems with practical applications in medical imaging and computational photography . Research Focus : Computer Vision, Scene Flow Estimation, CT Reconstruction, and Machine Learning. Teaching : Courses in Digital Image Processing, Signal and Image Processing, Medical Images, and Computational Photography.

Anna-Kaisa Kailaمشاهده پروفایل

پژوهشگر

• socio-political effects of technology on creative and cultural sectors
• ethics and aesthetics of creative-AI
• copyright applied to art
• +۱۰ مورد دیگر

Anna-Kaisa Kaila is a Doctoral student and Researcher at KTH Royal Institute of Technology working within the Division of Media Technology and Interaction Design. She holds dual expertise as a musicologist (MA) and economist (M. Sc. Econ.), specializing in arts, communications, and intellectual property. Her interdisciplinary PhD project, part of the Wallenberg AI, Autonomous Systems and Software Program – Humanities and Society, examines artificial intelligence's social, ethical, and legal implications on artist communities. Dr. Kaila's research spans several interconnected domains: Socio-political effects of technology on creative and cultural sectors Ethics and aesthetics of creative-AI systems Copyright frameworks applied to AI-generated art Shifting narratives of creativity in the AI era Music semiotics and psychology regarding listeners' visual imagery She has developed innovative methodological tools including the Ethically Aligned Stakeholder Elicitation (EASE) framework for ethical analysis in music AI applications. Her work engages directly with artists using AI in creative work and provides critical analyses from humanist, social science, and legal perspectives. Her recent publications reveal significant tensions around environmental sustainability, data colonialism, and evolving notions of artistic authorship. Dr. Kaila actively contributes to academic discourse through: Teaching courses including Degree Project in Media Technology, Human Perception for Information Technology, and Machine Learning for Media Technology Supervising Bachelor and Master's thesis projects on creative-AI, AI-music, arts and media, and AI ethics Organizing influential workshops such as 'Fictional Abstracts: Ethics, Sustainability, and Creative-AI Futures' at ICCC '23 Moderating panel discussions on AI and Music at venues like the Museum of Artificial Intelligence in Stockholm Contributing to media discussions, including features in Opus Magasin, a prominent classical music magazine

• Stochastic Processes
• Monte Carlo Simulation
• Mathematics of Data Science
• +۴ مورد دیگر

Henrik Hult is a Professor of Mathematical Statistics at KTH Royal Institute of Technology. He currently serves as director of Brummer and Partners MathDataLab at KTH. His academic appointments include Assistant Professor at Brown University (2006-2008) and Senior Lecturer at KTH (2008-2015) before becoming a full Professor in 2015. His research spans multiple domains with strong connections between theoretical probability and practical applications. Hult's work demonstrates significant contributions to stochastic processes , Monte Carlo simulation , mathematics of data science , mathematical finance , and insurance . His research methodology often bridges theoretical mathematics with computational techniques to solve complex real-world problems. The analysis of his recent publications reveals a strong interdisciplinary approach, with research spanning financial mathematics (algorithmic trading, risk management), probability theory (coalescent models, diffusion processes), computational statistics (rare event simulation, importance sampling), and medical applications (neuroimmunology, medical image analysis). His work demonstrates consistent focus on developing rigorous mathematical frameworks for practical applications across diverse fields. Hult teaches several advanced courses including Degree Project in Financial Mathematics, Foundations of Probability Theory, Modern Methods of Statistical Learning, Portfolio Theory and Risk Management, and Statistical Machine Learning, reflecting his broad expertise across theoretical and applied statistics. His collaborative research network is extensive, with frequent co-authorship with colleagues at KTH and international institutions. The diversity of his publication venues—from top probability journals like Electronic Journal of Probability to interdisciplinary journals like Proceedings of the National Academy of Sciences —demonstrates the wide applicability of his mathematical approaches.

Stefano Manzoniمشاهده پروفایل

استاد

• Soil Ecology
• Biogeochemistry
• Climate Change Impacts
• +۷ مورد دیگر

Stefano Manzoni is a Professor in the Department of Physical Geography at Stockholm University , where he investigates biogeochemical processes in terrestrial ecosystems. His research integrates microbial physiology with soil carbon dynamics, drought impacts on vegetation, and nutrient cycling across grasslands, forests, and boreal systems. Current projects include SMILE (soil microbial adaptation to climate change), NITROPRIME (plant-microbe nitrogen interactions in Arctic soils), and European Forest Soil Management synthesis. He develops theoretical frameworks linking microbial carbon-use efficiency (CUE) to global soil carbon storage, emphasizing its role in climate feedbacks. Key methodologies involve stoichiometric modeling, isotope tracing, and ecohydrological optimization approaches. Notable research trends from his publications include: microbial carbon-use efficiency as a driver of soil carbon persistence, trait spectra in ectomycorrhizal fungi for nitrogen acquisition, drought-induced shifts in grassland root-shoot biomass allocation, and phosphorus conservation mechanisms in long-term ecosystem development. He actively collaborates on international initiatives like the HoliSoils policy briefs and participates in sessions at conferences such as EGU General Assembly . His lab ( @manzonilab.bsky.social ) trains researchers in modeling plant-soil-microbe interactions and climate change resilience.