Model Driven Software Development Professors and Supervisors in Sweden

Reza Rezassonمشاهده پروفایل

مدرس

University of GävleSweden

Reza Rezasson is an Assistant University Lecturer at Gävle University, specializing in X-ray imaging and detector technology. His research focuses on applications in industrial quality control, environmental analysis, and material science. Notably, he has contributed to advancements in phase-contrast X-ray imaging for paperboard quality inspections and X-ray fluorescence spectrometry for toxic metal detection. Rezasson holds a PhD from Mid Sweden University (2016) and a Licentiate degree (2014), both in related fields. Education: PhD in Advanced X-ray Detectors for Industrial and Environmental Applications, Mid Sweden University, 2016 Licentiate in Phase-Contrast and Spectroscopic X-ray Imaging, Mid Sweden University, 2014 Research Interests: Rezasson's work bridges electrical engineering and applied physics, with a focus on developing high-resolution imaging systems and detectors. His research addresses challenges in non-destructive testing, nanoparticle characterization, and sensor optimization. Recent projects include collaborations with institutions like DESY on detector development and software design for the PERCIVAL detector system. Publications: His over 30 peer-reviewed articles span X-ray imaging techniques, detector technology, and educational policy. Recent trends emphasize interdisciplinary applications, such as environmental monitoring and pandemic-driven educational reforms. Grants & Labs: Rezasson collaborates on detector projects involving institutions like DESY and international teams. His lab work focuses on PERCIVAL detector systems and their applications in synchrotron radiation studies. Future research aims to expand into smart dosimetry and AI-driven imaging algorithms. Academic Advocacy: He actively contributes to academic discourse on university policies, mentorship, and student well-being through articles in SULF publications, advocating for intellectual diversity and supportive academic environments.

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Anita Lindmarkمشاهده پروفایل

دانشیار

Umea UniversitySweden

Anita Lindmark is an Associate Professor in the Statistics department at the Umeå School of Business, Economics and Statistics (USBE), Umeå University. Her work focuses on understanding socioeconomic disparities in healthcare outcomes, particularly in stroke research and mediation analysis. She holds a recognized qualification as a university teacher. Education: Recognised as a university teacher (formal qualification). Research interests include the application of advanced statistical methods to analyze socioeconomic determinants of health outcomes, stroke severity, and survival rates. Her work emphasizes mediation analysis to identify pathways through which socioeconomic status influences health, and she develops novel statistical techniques to address unobserved confounding in observational studies. Her publications (2014–2025) consistently explore socioeconomic disparities in stroke care and outcomes, integrating sensitivity analysis and causal inference frameworks. This work bridges epidemiology, biostatistics, and public health, with a focus on improving healthcare equity. Awards: USBE Scientific Awards 2020. Research projects include 'Uncovering the mechanisms behind socioeconomic inequalities in stroke care and outcome through innovative statistical methods for mediation analysis' (2019–2022). She contributes to the Stat4Reg research group, emphasizing statistical methods in register-based studies. No formal advisees/students are listed, though her work involves collaborations with clinicians and epidemiologists. Lindmark’s team focuses on interdisciplinary approaches to healthcare data analysis, leveraging national registries like Riks-Stroke to address healthcare inequities.

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Maria Fahlgrenمشاهده پروفایل

دانشیار

Karlstad UniversitySweden

Maria Fahlgren is an Associate Professor in Mathematics Education at Karlstad University, specializing in the integration of digital technologies into mathematics teaching and learning. She focuses on task design, particularly at the upper secondary and tertiary levels, using dynamic software such as GeoGebra and Desmos. Her work emphasizes student exploration, experimentation, and reasoning through technology-enhanced environments. Collaborations include the National Centre for Mathematics Education (NCM) for professional development modules and the Nordplus Higher Education network (METT) for teacher training exchanges. Her research spans design-based research methodologies, formative feedback systems in engineering education, and cross-European projects under Erasmus+. Key themes include real-time classroom monitoring, hybrid assessment systems combining dynamic software with computer-aided tools, and fostering mathematical reasoning through technology. Publications highlight innovations in task design, adaptive assessment systems, and the role of programming as a mathematical instrument. Her work bridges pedagogical theory with practical classroom applications, aiming to enhance both student learning and teacher capacity through technology integration. Current initiatives include developing digital solutions for formative feedback, orchestrating technology-mediated classroom discussions, and advancing teacher training programs via collaborative networks across universities in Sweden, Estonia, Norway, Iceland, and beyond.

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Sebastian Heroldمشاهده پروفایل

دانشیار

Karlstad UniversitySweden

Sebastian Herold is an Associate Professor in Computer Science at Karlstad University, Sweden. His research focuses on software architecture, design, and quality, with an emphasis on mitigating architecture erosion and technical debt through empirical industry collaboration. He has held roles at RWTH Aachen University (2005 diploma/Master's equivalent), Clausthal University of Technology (PhD 2011), and Lero - The Irish Software Research Centre (2013–2015). Education: RWTH Aachen University of Technology, Germany: Diplom-Informatik (2005) Clausthal University of Technology, Germany: PhD in Computer Science (2011) Research interests span software architecture evolution, empirical studies in software engineering, privacy patterns (GDPR compliance), and usability evaluation in digital health. His work includes developing tools like InMap for automated code-to-architecture mapping and organizing workshops like SAEroCon on architectural consistency. Publications highlight trends in synthetic data for healthcare usability, machine learning for architecture mapping, and empirical validation of software practices. Recent work integrates AI methods for software engineering challenges and explores efficiency in digital health evaluations. Awards: None explicitly listed. Grants and advising: No specific grants or student advisees mentioned; collaborations with industry and Lero are emphasized. Labs/Teams: Active in Karlstad University's Department of Computer Science, with contributions to interdisciplinary projects like GDPR-focused MOOCs and healthcare software development studies.

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Ben Kooمشاهده پروفایل

دانشیار

Chalmers University of TechnologySweden

Ben Koo is an Associate Professor at Tsinghua University, actively involved with the CDIO Initiative as a member of the global academic community. His work focuses on advancing engineering education through innovative pedagogical approaches, particularly in curriculum design and project-based learning. He has contributed to numerous international CDIO conferences, publishing proceedings that emphasize standards implementation, global collaboration, and educational technology integration. His research interests center on improving engineering education outcomes through CDIO-based methodologies, including interdisciplinary project work, competency assessment frameworks, and industry-academia partnerships. Notable contributions include exploring sustainable engineering curricula, global competency development, and adaptive teaching strategies for diverse student populations. Ben Koo has authored over 15 conference proceedings since 2010, reflecting a steady focus on CDIO standards evolution, technology integration in education, and cross-cultural pedagogy. His work highlights trends in virtual collaboration tools, pandemic-era learning models, and global competency frameworks. No scientific awards are explicitly listed in the provided text. His professional activities include advising on CDIO implementation strategies and collaborating with international institutions to advance engineering education standards. Ben Koo's involvement with Tsinghua University and CDIO reflects a commitment to shaping future engineering educators and practitioners through rigorous, industry-aligned curricula and innovative teaching practices.

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Daniel Sundmarkمشاهده پروفایل

استاد

Dalarna UniversitySweden

Professor Daniel Sundmark is affiliated with Mälardalen University's School of Innovation, Design and Engineering, specifically within the Division of Computer Science and Software Engineering. His research focuses on software testing methodologies, embedded systems, fault management, and resilience engineering. He has published extensively on topics such as API testing, concurrency bugs, and safety-critical systems. Key research areas include: Model-based testing frameworks Automated test generation for embedded systems Resilience and fault recovery in networking systems Requirements engineering and similarity analysis His work spans both academic contributions and industrial collaborations, addressing challenges in automotive, railway, and telecommunications domains. Recent publications emphasize resilient system design, real-time systems, and automated testing strategies. Notable projects include the Alcea architecture analysis method and studies on fault management frameworks. He also explores integration testing challenges and the role of test automation in agile development. His research outputs demonstrate a strong focus on bridging theory and practice, with over 50 peer-reviewed articles since 2001 covering topics from concurrency bug detection to TDD optimization.

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Esteban Guerrero Roseroمشاهده پروفایل

دانشیار

Umea UniversitySweden

Esteban Guerrero Rosero is an Associate Professor in Social-Aware Artificial Intelligence at the Department of Computer Science, Umeå University (Sweden). His work bridges multi-agent systems , knowledge representation , and neuro-symbolic methods to develop trustworthy hybrid intelligence systems. He has co-led multidisciplinary projects in Sweden and Finland, focusing on AI applications in health , economics , and sports . Education: Ph.D. in Computer Science, Umeå University M.Sc. in Computer Science, Malmö University B.Eng. in Electronics and Telecommunications, University of Cauca (Colombia) His research emphasizes software agents and non-monotonic reasoning to model human activities in domains like health informatics and ambient intelligence . By integrating argumentation frameworks and neuro-symbolic approaches , he develops systems that adapt to social and behavioral contexts, with applications in digital coaching and behavior change interventions . Recent publications highlight trends in value-based decision-making , financial robo-advisors , and AI regulations , reflecting his focus on trustworthy AI and ethical reasoning . His work often involves cross-disciplinary collaboration , particularly in healthcare and personalized systems. Guerrero Rosero has led the Formal Methods for Trustworthy Hybrid Intelligence research group since 2019. He is involved in projects like STAR-C (2018–2024), Socially Intelligent Autonomous Systems (2017–2019), and NTC - Nordic Telemedicine Center (2015–2018), aiming to create AI systems that support human activities in complex social contexts.

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Felix Dobslawمشاهده پروفایل

دانشیار

Mid Sweden UniversitySweden

Felix Dobslaw is a Senior Lecturer and Associate Professor at Mid Sweden University , affiliated with the Department of Communication, Quality Technology and Information Systems (KKI). He leads the cross-disciplinary Software Engineering and Education (SEE) research group, focusing on the intersection of technology and human use in software development, with a particular emphasis on Generative AI applications.

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Erik Lindahlمشاهده پروفایل

استاد

Stockholm UniversitySweden

Erik Lindahl is a Professor of Theoretical Chemistry at the Department of Biochemistry and Biophysics, Stockholm University. His research group is primarily located at the Science for Life Laboratory, a joint research environment for Stockholm University, KTH Royal Institute of Technology, and Karolinska Institutet. Lindahl serves as deputy director of the Swedish e-Science Research Center (SeRC), sits on the steering committee for the national program in Data-driven Life Sciences at SciLifeLab, and is program manager for Stockholm University's part of a joint master's program in molecular techniques for the life sciences. He also serves as vice section dean for chemistry and is involved in creating a Swedish node within CECAM. Lindahl's research focuses on understanding the structure and function of ligand-gated ion channels, particularly in the human nervous system. His group combines experimental and computational approaches, including bioinformatics for building receptor models, molecular dynamics simulations to understand molecular interactions, and experimental techniques like electrophysiology and spectroscopy. They have made significant contributions to understanding how voltage-gated and ligand-gated ion channels function, including determining molecular mechanisms of channel opening and identifying binding sites for molecules that modulate neural signaling. The group is also a leader in developing computational tools for life sciences, particularly the widely used GROMACS software package for molecular dynamics simulations and methods for cryo-electron microscopy data analysis through the RELION program. Analysis of Lindahl's recent publications reveals a strong focus on structural biology of membrane proteins, particularly ligand-gated ion channels. His work integrates cutting-edge computational methods like molecular dynamics simulations, AlphaFold predictions, and cryo-EM data analysis to understand protein conformational dynamics and ligand binding. Key research themes include the structural basis of ion channel function, lipid-protein interactions that stabilize membrane proteins, and computational methods for biomolecular simulation and structural biology. His publications demonstrate a consistent interdisciplinary approach that bridges computational chemistry, structural biology, and neuroscience. Lindahl leads an active research group with multiple postdocs, researchers, and PhD students working on various aspects of membrane protein structure and function. His research is supported by diverse funding sources including the Swedish Research Council, European Research Council, Knut and Alice Wallenberg Foundation, and several EU programs. He plays significant leadership roles in major computational infrastructure initiatives including BioExcel (an EU-funded center of excellence for computational biomolecular research), PRACE (the European computing infrastructure), and EuroHPC. The Lindahl research group operates primarily at the Science for Life Laboratory, where they have access to advanced computational resources and experimental facilities for structural biology. The group collaborates extensively with researchers across Stockholm University, KTH, Karolinska Institutet, and international partners through EU-funded projects. They are particularly active in developing and maintaining open-source software tools that are widely used in the computational biology community.

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Shafiullah Soomroمشاهده پروفایل

دانشیار

Linnaeus UniversitySweden

Shafiullah Soomro serves as Associate Professor in the Department of Artificial Intelligence at Quaid-e-Awam University of Engineering Science and Technology, Pakistan. He completed his Ph.D. in Application Software from Chung-Ang University, South Korea (2018), where he was honored as Best PhD Graduate. Ph.D., Application Software, Chung-Ang University (2018) His research spans medical image segmentation, computer vision, and AI applications in environmental monitoring. Specializing in automatic segmentation techniques using machine learning, he combines theoretical frameworks with practical biomedical implementations. Recent work integrates Swedish National Forest Inventory data with airborne laser scanning for forest attribute prediction. Current research projects include ForestMap (global forest cartography), AI-driven tree volume measurement (Sweden-Brazil collaboration), and machine learning models for predicting mechanical properties of oxynitride glasses. Best PhD Graduate, Chung-Ang University Dr. Soomro has mentored multiple MS students across Korea and Pakistan while supervising 2 Master's and 1 PhD students currently. His teaching portfolio includes 11 undergraduate, 2 MS, and 1 PhD courses such as Artificial Intelligence, Digital Image Processing, and Advanced Image Processing/Computer Vision. He actively contributes to academic curriculum design and research community development within the Computer Science and Artificial Intelligence department.

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Ann Lantzمشاهده پروفایل

استاد

KTH Royal Institute of TechnologySweden

Ann Lantz is a Professor and Head of School at KTH Royal Institute of Technology, working within the School of Electrical Engineering and Computer Science. She specializes in Human-Computer Interaction with a focus on behavioral science. Research areas: email systems, digital meeting systems, procurement processes, accessibility design, challenge-driven education Affiliation: KTH Royal Institute of Technology, School of Electrical Engineering and Computer Science Contact: alz@kth.se Her scholarly work examines: Accessibility for cognitively disabled users in digital communication Challenge-driven education models in global contexts Procurement processes in interaction design Remote collaboration tools and digital work environments Publications show strong trends in: Usability and accessibility research International education collaborations Workplace technology evaluation Design for cognitive disabilities

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Leif Erikssonمشاهده پروفایل

استاد

University of GothenburgSweden

Professor Leif Eriksson is a leading computational chemist in the Department of Chemistry and Molecular Biology at the University of Gothenburg, holding his professorship since 2011 after positions at NUI Galway and Dalhousie University. His research group comprises 1 research engineer, 2 postdocs, 1 doctoral student, and multiple Master's researchers focusing on AI-driven drug discovery. His educational background includes: Chemistry studies at Stockholm University and University of Sussex PhD in Quantum Chemistry, Uppsala University (1992) Postdoctoral Fellowship at Dalhousie University, Canada (1992-93) Research centers on theoretical biophysical chemistry with emphasis on computational modeling of DNA damage, cancer mechanisms, and antibiotic development. The group pioneers AI-based tools (MolAI, iScore) for ultrafast drug discovery, studying stress response pathways in glioblastoma/TNBC and developing inhibitors through multi-scale simulations from QM/MM to molecular dynamics. Recent work targets protein-protein interactions, membrane diffusion, and drug-loaded liposomes using integrated computational-experimental approaches. Publication trends (2022-2025) reveal strong focus on cancer therapeutics (35%), antibiotic discovery (25%), and AI-driven drug design (40%), with increasing integration of machine learning for ADMET prediction and target validation. Key journals include Journal of Chemical Information and Modeling (30%), Biochemistry (20%), and Scientific Reports (15%). Scientific recognition includes: Göta Student Union's Pedagogical Prize (2017) 300+ scientific papers and 20+ review chapters Patents for skin cancer/glioblastoma drugs leading to spin-offs (ANYO Labs, C26 Bioscience, Cell Stress Discoveries) Advising involves direct supervision of doctoral/postgraduate researchers with strong industry-academia pipelines. Grant funding is sustained through: National: Swedish Research Council, Swedish Cancer Society, Lawski Foundation International: Wenner-Gren Foundations, GBM Foundation, EU H2020 MSCA-RISE The lab maintains active collaborations with UGOT CARe for antibiotic resistance research and international networks for cancer drug validation. Research infrastructure leverages national supercomputing resources (via NAC leadership) and integrates wet-lab validation through spin-off partnerships. Current projects focus on translating computational discoveries into patentable therapeutics for aggressive cancers and antimicrobial resistance, with multiple compounds in preclinical development phases.

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Maksims Kornevsمشاهده پروفایل

مدرس

KTH Royal Institute of TechnologySweden

Maksims Kornevs serves as an Adjunct Lecturer at KTH Royal Institute of Technology's School of Engineering, Division of Health Informatics and Logistics since 2021, specializing in data communication, medical engineering, and healthcare complexity research. His academic journey includes a PhD in Technology and Health from KTH (2019), Master's and Bachelor's degrees in Information Technology and Computer Science from Riga Technical University (top 1% of class). Doctor of Philosophy in Technology and Health (KTH, 2019) Master of Engineering Sciences in Information Technology (Riga Technical University, 2013) Bachelor of Engineering Sciences in Computer Control (Riga Technical University, 2011) His research spans participatory methods, gaming simulation, healthcare logistics, and mental health systems , with significant focus on complex adaptive systems in public sectors. Recent work integrates AI-driven decision aids for cancer screening and eldercare digitalization, emphasizing real-world implementation challenges through ethnographic studies and simulation frameworks. Publications (2014-2024) reveal three thematic clusters: 1) Healthcare simulation ( elderly care, frailty prevention, mental health systems ), 2) Logistics optimization ( port operations, road procurement, supply chain ), and 3) Serious games applications ( public servant training, engineering education ). Cross-cutting methodologies include Q methodology, system dynamics, and participatory design. As Principal Investigator, he leads multiple funded projects including Digital Decision Aid for Cancer Screening (49.5 kSEK, 2023-2024) and Computer Technology for Piano Learning (21 kSEK, 2024), demonstrating applied research translation. He previously managed KTH's Integration Lab supporting home care research and contributed to EU projects like POSITIVE (elderly monitoring systems) and ELISA (port digitalization).

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