جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Machine Learning
• Systems Biology
• +۴ مورد دیگر

Ross King is a Professor in the Department of Systems Biology at Chalmers University of Technology. He specializes in leveraging artificial intelligence, machine learning, and automation to advance scientific research. His work focuses on developing autonomous laboratory systems and AI-driven methodologies to accelerate discoveries in drug development, systems biology, and metabolic modeling. Key projects include Genesis, a database for autonomous systems, and AutonoMS for metabolomic analysis. His research emphasizes reproducibility, hypothesis generation via large language models, and integrating robotics with computational tools. King's contributions span interdisciplinary fields, combining computational methods with experimental validation. He leads efforts to automate scientific workflows, exemplified by his Robot Scientists (Adam and Eve), which autonomously design and execute experiments. His recent work explores extrapolation challenges in machine learning, ethical AI in science, and personalized medicine through predictive modeling. He has published extensively in journals like PNAS , Nature Machine Intelligence , and Scientific Reports , with a focus on AI ethics, closed-loop discovery systems, and translational applications in healthcare. His research bridges theoretical computer science with practical biomedical and environmental challenges.

• Aeroacoustics
• Automotive Engineering
• Acoustic Engineering
• +۳ مورد دیگر

Mikael Karlsson is a Researcher at the Department of Automotive Engineering and Technical Acoustics at KTH Royal Institute of Technology, Sweden. His work focuses on aeroacoustics, automotive systems, and noise control, with applications in vehicle design and environmental engineering. He teaches courses such as Acoustic Measurements (SD2165) and Flow Acoustics (SD2155), emphasizing practical and theoretical aspects of sound propagation and flow dynamics. His research interests include the study of fan noise, tube bank acoustics, and the integration of machine learning in biomedical diagnostics. He has contributed to projects on automotive exhaust systems, heat recovery technologies, and particle filtration, addressing challenges in both industrial and academic settings. Recent articles highlight advancements in aeroacoustic modeling, such as analyzing installation effects on fans and optimizing filter elements for cleaner vehicle exhausts. His work bridges mechanical engineering with environmental sustainability, aiming to reduce noise pollution and improve energy efficiency.

Evelyn Otero Solaمشاهده پروفایل

دانشیار

• Sustainable Aviation
• Air Traffic Management
• Emissions Reduction
• +۵ مورد دیگر

Dr. Evelyn Otero Sola is an Associate Professor in Aeronautical Engineering at KTH Royal Institute of Technology, serving as Vice-Director of the Centre for Sustainable Aviation (CSA) and a member of the Executive Board of the Environmentally Compatible Air Transport System (ECATS) International Association. Her research focuses on sustainable aviation, particularly optimizing air traffic management (ATM) to reduce emissions (CO2 and non-CO2) and noise, with projects involving sustainable aviation fuels (SAF), hydrogen, AI, and drones. She leads the doctoral course FSD3831 Future Sustainable Aviation and the master’s course SD2830 Aircraft Performance and Air Traffic Management , emphasizing interdisciplinary approaches to sustainability. Key collaborations include the Swedish Aerospace Research Center (SARC) and initiatives like TREVOL, TRACE, CIDER, and KLIMAFLY. Her work bridges research, education, and industry to drive sustainable aviation solutions globally. Education details are not explicitly provided, but her academic contributions include over 15 publications since 2009, spanning CFD optimization, climate modeling, and aviation environmental impact. She advises 11 doctoral students in the first iteration of her course and plans to expand access internationally. Her initiatives aim to create a skilled workforce for sustainable aviation through holistic education and cross-sector networks.

• Lung Cancer
• Precision Radiotherapy
• Biomarker Discovery
• +۴ مورد دیگر

Kristina Viktorsson is a Senior Research Specialist at Karolinska Institutet's Department of Oncology-Pathology , leading a research team focused on precision cancer medicine and precision radiotherapy in lung cancer. Her work spans preclinical, translational, and clinical trials, particularly investigating stereotactic body radiotherapy (SBRT) for lung tumors and molecular mechanisms of resistance. Research Highlights: Exploring biomarkers in tumor/liquid biopsies for radiation/pharmaceutical response Developing fine-needle aspiration (FNA) molecular profiling for real-time diagnostics Studying Eph/Ephrin signaling in radiotherapy sensitivity and cancer progression Collaborations: Nordic SBRT Group Royal Institute of Technology (KTH) RISE Research Institute of Sweden Publications demonstrate expertise in extracellular vesicles , drug resistance , and combination therapies . Her work includes grants from Karolinska Institutet, Swedish Cancer Society, and Radiumhemmet.

• Applied Optimization
• Wireless Internet of Things
• Machine Learning
• +۶ مورد دیگر

Carlo Fischione is a Full Professor at KTH Royal Institute of Technology in the School of Electrical Engineering and Computer Science, Division of Network and Systems Engineering, Stockholm, Sweden. He is a Fellow of IEEE, KTH Digital Futures, and the Italian Academy DASP, and a Distinguished Lecturer of the IEEE Communications Society. He holds a PhD and Laurea (Summa cum Laude) in Engineering from the University of L’Aquila, Italy, and has held research positions at MIT, Harvard, and UC Berkeley. PhD in Electrical and Information Engineering, University of L’Aquila (2005) Laurea in Electronic Engineering, Summa cum Laude, University of L’Aquila (2001) His research focuses on applied optimization, wireless Internet of Things, and machine learning , with particular emphasis on federated learning, over-the-air computation, and spectrum sharing in 5G/6G networks. He leads a vibrant research group and has supervised numerous PhD and postdoctoral researchers, many of whom now hold faculty or senior research positions globally. His recent publications reflect a strong trend toward machine learning in distributed and resource-constrained networked environments , especially focusing on communication efficiency, privacy, and scalability. Key themes include federated learning over fading channels, over-the-air computation, and AI-aided wireless channel prediction. IEEE Fellow IEEE Distinguished Lecturer, Communications Society IEEE Communication Society S. O. Rice Award (2018) Best Paper Award, IEEE Transactions on Industrial Informatics (2007) Starting Grant, Swedish Research Council (2008) Prof. Fischione has advised numerous students who have gone on to prominent academic and industry roles. He has secured significant research funding from the Swedish Research Council, SSF, KAW Foundation, Vinnova, and EU Horizon programs, leading projects such as MALEN, SAICOM, TAIRCOMP, and WIDCOMP. He is also the founding General Chair of IEEE ICMLCN and a co-founder of ELK.Audio, demonstrating strong industry and innovation engagement. He leads multiple research initiatives and labs focused on networked machine learning, including groups working on federated learning, wireless AI, and edge intelligence. His team actively contributes to advancing the theoretical and practical foundations of machine learning over networks.

Emanuel Larssonمشاهده پروفایل

پژوهشگر

• X-ray Tomography
• Neutron Tomography
• Synchrotron Imaging
• +۵ مورد دیگر

Emanuel Larsson serves as a Researcher at Lund University's Department of Experimental Medical Science within the Faculty of Medicine. He holds dual institutional roles as Assistant Director at LINXS (Institute of Advanced Neutron and X-ray Science) and as a staff member at MAX IV Laboratory. His operational framework spans national infrastructure coordination including CIPA (Correlative Image Processing and Analysis), InfraVis (National Research Infrastructure for Data Visualization), and HALRIC (Hanseatic Life Science Research Infrastructure Consortium). His research centers on advanced tomographic imaging techniques , specializing in X-ray and neutron tomography for multiscale materials characterization. Key application areas include food science (starch foams), nanomaterials (photonic crystals, nanoporous gold), and biomedical engineering. His work integrates synchrotron radiation methods with machine learning approaches for 3D microstructure analysis, contributing to UN Sustainable Development Goals through materials innovation. Analysis of his 32 publications reveals dominant themes in materials microstructure visualization across food systems, nanocomposites, and reference standards development. His imaging methodologies bridge physics, engineering, and life sciences with emphasis on correlative techniques that combine multiple imaging modalities for comprehensive material analysis. Larsson actively leads infrastructure development through current projects including CIPA (2020-2027), Marine Centre Simrishamn, and MICROMORPH (2026-2028). His organizational roles include coordinating the 2024 SynchroMage hackathon focused on environmental/climate applications of tomography. He manages critical research infrastructure including Correlative Image Processing and Analysis and InfraVis national visualization systems. His laboratory ecosystem operates at the intersection of MAX IV Laboratory's synchrotron facilities, LINXS neutron science infrastructure, and Lund University's medical research environment. Current initiatives involve µCT machine learning integration for morphological diversity analysis and correlative X-ray tomography for membrane studies in food processing applications.

• Wave Energy Conversion
• Renewable Energy
• Hydrodynamic Modeling
• +۹ مورد دیگر

Jens Engström is a Senior Lecturer at the Department of Electrical Engineering, Uppsala University, where he is affiliated with the Division of Electricity. His research is centered on wave energy conversion systems, particularly point-absorbing wave energy converters, with a strong emphasis on hydrodynamic modeling, survivability under extreme conditions, and control strategies. His research interests include wave energy conversion, hydrodynamic modeling, control systems for wave energy converters, marine renewable energy, and the application of machine learning to optimize energy extraction and survivability. He also investigates the integration of wave energy with desalination systems for sustainable freshwater production, especially in off-grid and island contexts. Recent publications show a clear trend toward the application of artificial intelligence and deep learning in enhancing the performance and survivability of wave energy converters. His work combines experimental validation, numerical simulation (including CFD), and field measurements, particularly from the Lysekil Research Site. The research spans from fundamental hydrodynamics to system-level optimization of wave energy farms. He has contributed to numerous high-impact journals such as Renewable Energy , Ocean Engineering , and IEEE Journal of Oceanic Engineering , and has co-authored review articles on wave energy park optimization. His research is highly collaborative, often involving teams from Uppsala University and international partners. Engström completed his doctoral thesis in 2011 on hydrodynamic modeling of point-absorbing wave energy converters and has been actively publishing since 2007. He is involved in advising students and supervising research projects, though specific names are not listed. His work is supported by experimental and numerical infrastructure at Uppsala University, particularly related to the Lysekil wave energy research site.

Fredrik Sävjeمشاهده پروفایل

دانشیار

• Causal Inference
• Econometrics
• Experimental Design
• +۳ مورد دیگر

Dr. Fredrik Sävje is a Senior Lecturer and Associate Professor at the Department of Economics, Uppsala University , specializing in causal inference and econometrics. His research focuses on experimental design, variance estimation, and treatment effect analysis under complex interference structures. Academic Affiliation: Department of Economics, Uppsala University Email: fredrik.savje@nek.uu.se Dr. Sävje’s research interests span causal inference, econometrics, and statistical methodology. Key areas include: Design-based frameworks for causal inference Threshold blocking and covariate balancing Exposure-response models in bipartite experiments Robust variance estimation under interference His recent work emphasizes: Foundations of causal inference in randomized controlled trials Optimized covariate balancing via Gram–Schmidt Walk Design Relaxing assumptions in exposure mapping for treatment effects Generalizing inference methods to sparse and complex experimental graphs Dr. Sävje has co-authored software packages including GSWDesign.jl for covariate balancing and quickmatch for generalized full matching in R. His publications appear in top journals like Biometrika , Journal of the American Statistical Association , and Electronic Journal of Statistics .

Astrid von Mentzerمشاهده پروفایل

مدرس ارشد

• Microbial Genomics
• Escherichia coli Pathogenesis
• Antibiotic Resistance
• +۳ مورد دیگر

Astrid von Mentzer is an Associate Senior Lecturer at the University of Gothenburg , affiliated with the Department of Microbiology and Immunology . Her research focuses on pathogenic Escherichia coli (ETEC), combining genomic approaches with machine learning to understand bacterial adaptation, spread, and disease mechanisms. Specializes in microbial genomics and antibiotic resistance research Investigates host-pathogen interactions through adhesin proteins Develops data-driven models for predicting pathogen transmission Studies hybrid E. coli strains with enhanced virulence potential Her recent work examines ETEC clones in aquatic environments (2025) and their molecular epidemiology in sub-Saharan Africa. She has created genomic resources like the ETECFinder database and contributed to understanding CS23-expressing isolates . Her lab ( vonmentzerlab.com ) applies computational methods to map transmission dynamics between humans, animals, and environmental reservoirs. Key methodologies include whole-genome sequencing , machine learning classification , and host specificity analysis . Research outcomes inform public health strategies for diagnostics and vaccine development against resistant strains.

• Artificial Intelligence in Healthcare
• Health Informatics
• Implementation Science
• +۳ مورد دیگر

Monika Nair is a post-doctoral researcher at Halmstad University's School of Health and Welfare, specializing in artificial intelligence implementation within healthcare systems. Her work bridges technical AI development and practical clinical deployment, with significant contributions to reducing heart failure readmissions and creating practitioner-focused implementation frameworks. Her research spans critical areas at the AI-healthcare intersection: Implementation science for clinical AI systems Predictive modeling of patient readmissions Human-centered design of decision support tools Barrier analysis for healthcare technology adoption Mixed-methods evaluation of AI interventions Stakeholder-driven framework development Analysis of her publication trends (2022-2025) reveals consistent focus on practical AI integration challenges, combining technical modeling with organizational and human factors. Her work emphasizes co-creation with healthcare providers and addresses domain-specific applications in heart failure management and mental health services through scoping reviews, framework development, and empirical implementation studies. Scientific awards: No specific awards documented in available sources Monika actively supervises Master's and PhD students while teaching health innovation courses, guiding research on AI implementation topics. Her project involvement in the "Heart Failure Readmission Prediction" initiative and AI framework development indicates active grant-funded research, though specific funding details aren't publicly enumerated. She collaborates within interdisciplinary teams focused on the "Heart Failure Readmission Prediction within 30-days" project and AI implementation framework development, working across computer science, clinical practice, and implementation science domains to translate research into actionable healthcare solutions.

Camilla Graneمشاهده پروفایل

مدرس ارشد

• Human-Machine Interaction
• Engineering Psychology
• Usability
• +۷ مورد دیگر

Camilla Grane serves as a Senior Lecturer in Psychology at Luleå University of Technology, where she is affiliated with the Department of Health, Education and Technology and specifically works within the Division of Health, Medicine and Rehabilitation. In addition to her teaching responsibilities, she holds the position of deputy head of education for the Department of Health, Medicine, and Rehabilitation (HMR). Dr. Grane holds a Master of Science degree in Ergonomic Design and Production and earned her PhD in Engineering Psychology. Her educational background has prepared her for interdisciplinary work at the intersection of psychology, engineering, and human factors, focusing on the practical application of psychological principles to real-world technological challenges. Her research centers on human-machine interaction and psychosocial factors, with notable expertise in attention and distraction when using multimodal interfaces in vehicles. She has expanded her research scope to include workers' digital tools and wearable sensors in mining and process industries, examining critical aspects such as usability, efficiency, safety, acceptance, and privacy. Dr. Grane is particularly interested in how ongoing digital development creates new relationships between humans and technology, with emerging interests in generative AI and human-robot interaction as research areas. Her publication record demonstrates a strong focus on automotive human factors, with numerous studies on gear shifter usability, human-automation interaction, and safety in industrial contexts. Her work spans multiple disciplines including psychology, engineering, ergonomics, and industrial safety, reflecting her interdisciplinary approach to understanding human-technology interactions across different environments. Dr. Grane teaches across multiple academic programs including the Psychology Bachelor's program and the Master of Science program in Industrial Design Engineering. Her extensive teaching portfolio covers Introduction to Psychology, Engineering Psychology, Social Psychology: Psychological Perspectives, Work and Motivation Psychology, Human-Machine Interaction, Usability, and Ergonomics and Cognition, among other specialized courses. She has led and participated in several significant research projects including 'Working environment of control room operators' (Swedish Transport Administration), 'SIMS' (attitudes towards positioning technology in mining environments), 'Quicktag' (mobile applications for inspections at Boliden), 'The Future Operator' (digital tools for future operators at LKAB and Boliden), 'MODAS' (measuring trust in highly automated vehicles), and 'Life on Board' (usability of future gear selectors in vehicles).

Markus Bohlinمشاهده پروفایل

استاد

• Applied Artificial Intelligence
• Railway Systems
• Transportation Engineering
• +۵ مورد دیگر

Markus Bohlin serves as Professor (on leave) at Mälardalen University within the School of Innovation, Design and Engineering's Division of Product Realisation. He concurrently holds leadership roles as Dean of the School of Business Society and Engineering, Division Manager for Product Realization, and School Director for the INDTECH Industrial Graduate School. His academic credentials include: Doctoral thesis defended at Mälardalen University (2009) Associate professorship (docent) granted at Mälardalen University (2013) Adjunct professorship in rail traffic systems analysis at KTH Royal Institute of Technology (2014) Full professorship in Computer Science with Applied AI focus at Mälardalen University (2019) Bohlin's research centers on Applied Artificial Intelligence across critical infrastructure domains. His primary focus areas include: Railway systems optimization and freight logistics Cyber-physical systems for construction automation Machine learning applications in manufacturing quality control Simulation-assisted decision support systems His work bridges theoretical AI with industrial implementation in transportation, production, and power systems. Recent publications demonstrate a clear trajectory toward integrating machine learning with simulation modeling for real-world problem solving, particularly in railway punctuality optimization, construction site autonomy, and manufacturing defect detection. This interdisciplinary approach consistently targets high-impact industrial applications. Bohlin has held significant leadership positions including: President of the Swedish Operations Research Association (2012-2016) Member of Trafikverket Board on Capacity in Railways Program chair for ICROMA 2019 and multiple national conferences His academic supervision includes 4 completed PhDs, 9 licentiate degrees, and 5 ongoing doctoral candidates. With 20+ years of experience managing organizations up to 60 employees and 40+ projects (including H2020 initiatives), he brings substantial operational expertise to research commercialization. Current leadership roles encompass the Product Realisation division and INDTECH Industrial Graduate School, driving industry-academia collaboration in innovation and engineering.

• Digital Learning
• Educational Technology
• Computational Thinking
• +۲ مورد دیگر

Eva Brooks is a Visiting Professor at the School of Education, Humanities and Social Sciences at Halmstad University. She leads the research program LeaDS - Learning in a digitalised society , focusing on pedagogical innovations in technology-enhanced learning environments. Her academic profile demonstrates strong Nordic research collaborations. Her research explores: Digital transformation in Nordic higher education systems AI integration in educational contexts Computational thinking development through play-based learning Game design as pedagogical strategy Collaborative problem-solving in technology-rich environments Dr. Brooks maintains particular interest in how open-ended digital tools foster creativity and cognitive development in K-12 education. Publications analysis reveals consistent focus on: Nordic education policy and future skills development Design thinking methodologies in education Educational robotics implementation Teacher perspectives on game-based learning Gender-inclusive technology education Her work consistently bridges theoretical frameworks with classroom applications.

• Data driven Organisation
• Data democratisation
• Analytics
• +۳ مورد دیگر

Imad Banihani is a Senior Lecturer at the School of Information Technology at Halmstad University. He earned a PhD in Informatics from Lund University and specializes in data-driven organizations, data democratization, and analytics. His work bridges theoretical and applied research in modern technological challenges.

• Machine Learning
• Electronic Health Records (EHR)
• Precision Medicine
• +۲ مورد دیگر

Emmanuella Ama Wieba is a doctoral student at the Center for Applied Intelligent Systems Research (CAISR) within Halmstad University's School of Information Technology. She holds a Bachelor's and Master's degree in Computer Science from the University of Botswana. PhD in Intelligent Systems (ongoing) Computer Science (BSc/MSc) Research Focus: Specializes in synthetic Electronic Health Records (EHRs) and machine learning applications in healthcare. Key areas include: Precision medicine through AI-enhanced EHR analysis Temporal fidelity evaluation in synthetic time-series medical data Cervical cancer risk prediction algorithms Bantu language identification using probabilistic models Development of EHR evaluation frameworks Publication Trends: Her work demonstrates expertise at the intersection of healthcare data science and machine learning, with recent publications focusing on synthetic data validation, medical risk modeling, and NLP applications for African languages. Key themes include temporal pattern analysis in EHRs, cervical cancer prediction methods, and data imputation techniques.