جستجوی استاد راهنمای دانشگاهی

Alexander Hollbergمشاهده پروفایل

دانشیار

• Sustainable Design
• Optimization Processes
• Stakeholder Interaction
• +۴ مورد دیگر

Alexander Hollberg is an Associate Professor in the Division of Building Technology at Chalmers University of Technology, within the School of Architecture and Civil Engineering. His academic role focuses on Computational Sustainable Design, emphasizing the development of digital tools for sustainable building and urban design. He holds a PhD in Parametric Life Cycle Assessment (2016) from Bauhaus University Weimar, an MSc in Architectural Engineering (2011), and a BSc in Civil Engineering (2008) from Technical University of Munich (TUM). His research interests include Sustainable Design Optimization, Stakeholder Interaction, Artificial Intelligence, and Life Cycle Assessment (LCA). He co-founded CAALA, a software and consulting startup in Munich, Germany, advancing tools for real-time environmental performance evaluation in early design stages. Recent work includes studies on digital twins for urban planning, robust renovation strategies, and AI-driven facade optimization. Hollberg was promoted to Docent (Associate Professor) in Computational Sustainable Design in 2022, focusing on bridging computational methods with sustainable environmental transitions. His collaborative projects address tool development for stakeholder engagement, BIM integration, and circular economy frameworks in construction. Key Projects: Development of Bombyx and Twinable tools for real-time LCA and urban simulation Leading the Nordic Build-LCA PhD forum and BIM-based LCSA applications Contributions to IEA EBC Annex 72 guidelines on life cycle environmental impacts Education Background: PhD in Parametric Life Cycle Assessment, Bauhaus University Weimar, 2016 MSc in Architectural Engineering, Bauhaus University Weimar, 2011 BSc in Civil Engineering, Technical University of Munich, 2008 His research outputs prioritize early design-stage decision support through parametric modeling and AI, with a focus on carbon neutrality and material circularity in construction.

• Software Metrics
• Model Driven Software Development
• Empirical Software Engineering
• +۵ مورد دیگر

Miroslaw Staron is a Professor of Interaction Design and Software Engineering at Chalmers University of Technology. He maintains a unique 50/50 work arrangement, spending half his time on field research at Ericsson while holding his academic position. His research bridges academic theory with industrial practice through collaborations with major companies including Volvo Car Corporation and Volvo Information Technology. His research spans several key areas in software engineering: Software metrics and measurement systems in industry Model driven software development and empirical studies Defect prediction in software projects Requirements engineering in model-based development Applications of AI and machine learning in software engineering Automotive software development and security Staron's recent work demonstrates a strategic shift toward integrating AI technologies into software engineering processes, with particular focus on automotive applications. His publications from 2024-2025 reveal expertise in generative AI applications for code review automation, testing methodologies, and requirements engineering, showing how these technologies can transform traditional software development practices while addressing domain-specific challenges in automotive systems. Current research projects include: Kvantdatorer för framtidens mobilitetslösningar (2025-2027) Automatiserad och designoptimerad programvarukonstruktion/kodgenerering (2025-2029) Förvandla fordonsarkitektur med hjälp från AI (2021-2023) Arkitektonisk design och verifiering/validering av system med maskininlärning komponenter (2020-2024) With 78 publications documented in Chalmers' research database, Staron has established himself as a significant contributor to evidence-based software engineering research with strong industrial relevance.

• Total Productive Maintenance
• Artificial Intelligence
• Multi-Criteria Decision Making
• +۳ مورد دیگر

Ebru Turanoglu Bekar is a Senior Lecturer at the Department of Industrial and Materials Science, Chalmers University of Technology, specializing in Smart Maintenance and Production Systems. She contributes to the Production Service Systems & Maintenance research group. Research Interests: Total Productive Maintenance (TPM), Artificial Intelligence applications in manufacturing, Multi-Criteria Decision Making, Performance Measurement systems Recent Focus: Development of data-driven algorithms for predictive maintenance, integration of digital twins in industrial contexts Key Projects: Factory SensAI (2025–2028) - Data integration for AI in manufacturing Trustworthy Predictive Maintenance TPdM (2022–2025)

Jelena Zdravkovicمشاهده پروفایل

استاد

• Requirements Engineering
• Enterprise Modeling
• Business Process Management
• +۶ مورد دیگر

Jelena Zdravkovic is a Professor and Head of the Department of Computer and Systems Sciences (DSV) at Stockholm University. She leads the PRECIS research group which focuses on Process, Requirements, Enterprise, Capability, and Information Systems modelling. Her work spans theoretical and practical aspects of enterprise and IT solutions with a particular emphasis on digital transformation. Professor Zdravkovic's research interests center around Digital Business Ecosystems , Digital Twins , and Data-driven Requirements Engineering . Her work in Enterprise Modeling explores capability-oriented and consumer-oriented approaches to requirements engineering. She investigates how digital transformation and big data can be leveraged to improve requirements elicitation processes, and how organizations can model and manage complex digital business ecosystems. Her research has significant implications for how businesses can adapt to rapidly changing technological environments while maintaining resilience and competitiveness. Her recent publications reveal a clear trajectory toward integrating artificial intelligence with digital modeling techniques, particularly in the context of smart buildings and business ecosystems. There's a consistent focus on how data-driven approaches can transform traditional requirements engineering practices, making them more responsive to the velocity and variety of digital data sources. Her work bridges theoretical modeling with practical applications across various industries including healthcare, energy, and transportation. Professor Zdravkovic has been actively involved in mentoring PhD students, including supervising research on the Management Framework of Resilient Digital Business Ecosystems. She has participated in numerous national and international projects focused on interoperability and model-driven engineering, securing research funding for innovative work at the intersection of business and technology. She leads the PRECIS research group which deals with theories, methods and tools for analysis and design of organizational and IT solutions in congruence. The group's research covers three key topics – Enterprise Modelling, Business Process Management, and Conceptual Modelling. Their work brings together academic rigor with practical applications to solve real-world business challenges through innovative information systems approaches.

• Sustainable Manufacturing
• Industry 4.0
• Industry 5.0
• +۵ مورد دیگر

Morteza Ghobakhloo is a Senior Lecturer and Researcher at Uppsala University , affiliated with the Department of Civil Engineering and Industrial Engineering (Industrial Engineering) and the Institute for Research on Conflicts of Goals in Sustainable Social Transition . His email is morteza.ghobakhloo@angstrom.uu.se . He focuses on digital transformation, sustainability, and human-centric technologies. Research Interests: Morteza’s work bridges Industry 4.0/5.0 , Sustainable Manufacturing , and Generative AI applications. His studies explore blockchain, big data analytics, and smart technologies in supply chain resilience, energy efficiency, and organizational innovation. Article Trends: Recent publications highlight Industry 5.0’s role in sustainable supply chains, AI-driven healthcare optimization, and blockchain for socioenvironmental solutions. He employs hybrid methodologies like PLS-fsQCA, ANN, and simulation modeling across sectors including energy, healthcare, and tourism.

• Battery technology
• Materials science
• Electrochemistry
• +۷ مورد دیگر

Kristina Edström is a Professor at Uppsala University, specifically affiliated with the Department of Chemistry, Structural Chemistry unit at Ångström Laboratory. She is a leading expert in battery technology and electrochemistry, with extensive research on lithium-ion and sodium-ion batteries, solid-state electrolytes, and surface chemistry of battery components. Current research focuses on battery interfaces (SEI/CEI), polymer-ceramic composite electrolytes, and sustainable battery materials Key methodologies include X-ray photoelectron spectroscopy (XPS), neutron diffraction, and molecular dynamics modeling Recent publications (2024-2025) investigate: boron-modified solid electrolytes, self-healing polymer electrolytes, aqueous Li-ion systems, and manufacturing sustainability for batteries. Her work shows strong emphasis on improving battery safety, efficiency, and environmental impact. Leadership roles include participation in Battery 2030+ research initiatives and NordBatt conferences. She has contributed to developing standardized experimental workflows combining neutron/synchrotron techniques with AI-driven battery research.

• Computational Mechanics
• Wind Turbine Dynamics
• Railway System Dynamics
• +۴ مورد دیگر

Håkan Johansson is a Professor in the Dynamics division of the Department of Mechanics and Maritime Sciences at Chalmers University of Technology. His research focuses on computational methods to analyze controlled mechanical systems, with applications in wind turbines, heavy vehicle drivelines, and wave propagation in soft biological tissues. Professor Johansson's primary research interests include computational mechanics, wind turbine dynamics, railway system dynamics, biomechanics, condition monitoring systems, optimization methods, and structural dynamics. His work bridges theoretical computational methods with practical engineering applications across multiple domains, particularly in renewable energy systems and transportation infrastructure. Analysis of his publication record reveals a strong focus on computational modeling applied to real-world engineering problems. His recent work demonstrates significant contributions to wind turbine technology, railway infrastructure monitoring, and biomechanical modeling. The publications show a consistent pattern of applying advanced computational techniques to solve complex mechanical system challenges, with increasing emphasis on digital twin technology and model-based condition monitoring systems. Professor Johansson leads or participates in multiple research projects including 'Towards Digital Twins of the Human Body for Personalized Safety' (2025-2026), 'AI-Driven Constrained Optimal Control for Bi-manual Loco-Manipulation' (2024-2029), and 'A Digital Twin for Durability to Accelerate Development and Enable Predictive Maintenance' (2024-2027). His research has received funding from various sources including VINNOVA, Wallenberg AI program, and Swedish Wind Power Technology Center. His research group focuses on computational methods for mechanical systems with applications across multiple domains. The work involves developing advanced computational models, validation through experimental data, and implementation in real-world monitoring and optimization systems. Current efforts emphasize digital twin frameworks and model-based condition monitoring for various engineering systems.

• Aerospace Engineering
• Mechanical Engineering
• Robust Design
• +۴ مورد دیگر

Anders Forslund is a researcher at Chalmers University of Technology, specializing in Product Development with a focus on aerospace and mechanical engineering. His work bridges theoretical research and practical application in multidisciplinary design. Department: Product Development Key Collaborations: VINNOVA, EU Horizon 2020, AIAA, ASME His research interests revolve around robust design and uncertainty modeling for aerospace structures. He develops simulation platforms to minimize geometric variation in welded components and optimize turbine lifecycle robustness. His work integrates genetic algorithms , 3D scanning , and PLM systems for multidisciplinary convergence. The 15 most recent publications span 2011–2018, covering welding optimization , geometric robustness , simulation frameworks , and sustainable aerospace design . Key trends include bridging CAD/point cloud gaps , virtual trimming , and set-based design in collaborative platforms. Anders participates in grants and projects such as: TOICA (2013–2016): EU-funded thermal-driven aircraft design. ELISE (2018–2018): Vinnova-funded electric aviation. Design av de aerodynamiska egenskaperna för ett elektriskt flygplan (2021–2022): Chalmers-led aerodynamic R&D. He has contributed to research teams in propulsion, thermal sciences, and acoustic engineering, collaborating with experts like Rikard Söderberg and Lars Davidson.

• Business Process Management
• Process Mining
• Object-Centric Process Mining
• +۶ مورد دیگر

Amin Jalali is an Associate Professor of Computer and Systems Sciences at Stockholm University, specializing in business process modeling, analysis, and management. He is affiliated with the Department of Computer and Systems Sciences within the Faculty of Social Sciences, where he serves as a board member and manages three graduate courses: Business Process Design and Intelligence, Business Process and Case Management, and Data Warehousing. Institution: Stockholm University Department: Department of Computer and Systems Sciences (DSV) Research Groups: Natural Language Processing Research Group and PRECIS (Process, Requirements, Enterprise, Capability, Information Systems modelling) His research focuses on business process analysis through model-based and data-driven techniques, with particular emphasis on process simulation, process mining, event knowledge graphs, and object-centric process mining. He has led numerous research projects across healthcare, education, and finance domains. His work includes significant contributions to the development of NLP methods involving large language models, with focus on privacy, explainability, and domain adaptation. Jalali's research output shows a strong trend toward practical applications of process mining techniques, particularly in healthcare contexts like drug-drug interaction analysis and elderly care. More recently, his work has expanded into blockchain applications for fraud detection, motor imagery signal classification, and advanced object-centric process mining approaches. His publications span both theoretical contributions to business process management frameworks and practical implementations in real-world settings. He has extensive industry experience in designing and implementing Business Intelligence and Big Data Analytics solutions, which informs his academic work and teaching approach. His research has been published consistently from 2012 through 2024, demonstrating sustained scholarly productivity in his field. Dr. Jalali has contributed significantly to the development of tools and libraries for process mining, including the dfgcompare library for process variant analysis and implementations for object-centric process mining. His work bridges academic research with practical applications, particularly evident in healthcare projects like the DDIs-Graph system for identifying drug-drug interactions.

• Industry 4.0
• Resilience Engineering
• Sustainability in Production Systems
• +۳ مورد دیگر

Arpita Chari is a Research Fellow at Chalmers University of Technology, specializing in Virtual and Digital Production Systems. Her work bridges Industry 4.0, Resilience Engineering, and Sustainability in Production Systems, focusing on integrating digital technologies to enhance resource efficiency and enable lean circular manufacturing. Her research explores the implementation of resilient and sustainable practices in manufacturing, emphasizing dynamic capabilities, digital platforms, and supply chain optimization. Key projects include the Digitala Stambanan initiative and the Produktion2030 strategic innovation program, which address sustainability transitions and systemic resilience. 2024 Highlights: Analyzed dynamic capabilities for resilience-sustainability integration, characterized battery lifecycle challenges, and modeled risk prioritization in supply chains. 2023 Themes: Digital platform adoption, battery production systems, and value chain sustainability in the Digitala Stambanan project. 2022–2021 Foundations: Developed frameworks for green manufacturing, circular supply chains, and stakeholder-driven sustainability in textiles.

Huizhong Caoمشاهده پروفایل

پژوهشگر

• Cognitive Ergonomics
• Mental Workload
• Manufacturing Digitalization Innovation
• +۵ مورد دیگر

Huizhong Cao is a researcher at Production Systems , Chalmers University of Technology. With a background in architecture and sustainable urban planning, she bridges design and technology through projects involving XR platforms , digital twins , and human-centered design . MSc in Sustainable Urban Planning (Chalmers) BSc in Architecture (Wuhan University) Her research focuses on mental workload assessment , XR interface design , and sustainable smart cities . Key projects include: RILIK - Immersive learning framework XR-TBP - Extended reality training for battery production TRIREME - Digital & Green Skills development DIGITALIS - Cognitive work optimization Recent publications analyze: VR interface design for collaborative manufacturing XR applications in environmental sustainability Digital twin integration with IoT Scientific recognition includes: IPOET Scholarship LEXUS Design Award Finalist KTH Innovative Incubator Program UIA-HYP Cup Third Prize She has contributed to UX design and XR development across multiple projects, often combining participatory design with game engine technology . Contact: huizhong@chalmers.se | huizhongcao1@gmail.com

• Game Development
• Serious Games
• Game Analytics
• +۷ مورد دیگر

Henrik Engström is a Professor of Informatics at the University of Skövde, affiliated with the School of Informatics and Department of Information Technology. He holds a PhD in Computer Science from the University of Exeter. His research focuses on game development processes, serious games, and interdisciplinary collaboration in game design. Engström has led multiple projects, including the Game Tech Academy and Sweden Game Arena initiative, aiming to leverage game technology for societal challenges in health, education, and industry. He coordinates the Game Development Master's Programme and has published extensively on topics like game analytics, inclusive design, and mobile game publishing strategies. His work often bridges academia and industry, emphasizing practical applications in training simulations and healthcare. Education: PhD in Computer Science (University of Exeter) Key Projects: Sweden Game Arena, Game Hub Scandinavia, Digital Parental Support Tools Research Interests: Game design processes, serious games for health, inclusive game development, and mobile game business models Engström’s research outputs span over two decades, with notable contributions to understanding game development challenges, stress detection in games, and the application of AI in game narratives. His book Game Development Research (2020) synthesizes empirical insights from industry practices. He collaborates internationally, including with Japanese and Scandinavian institutions, to advance educational game models and industry-academia partnerships. His articles highlight trends in data-driven decision-making for indie game publishers, the psychological impact of game design on player experiences, and leveraging game jams for addressing heavy societal topics. Engström also leads grants focused on digital health tools for expecting parents and sustainable urban planning via game-based participation. Labs/Teams: Key contributor to the Sweden Game Conference and collaborator with Game Tech Academy, fostering innovation in game-based solutions for societal challenges.

Farzin Golzarمشاهده پروفایل

استادیار

• Sustainable Energy Systems
• Artificial Intelligence Applications in Environmental Science
• Circular Economy
• +۳ مورد دیگر

Farzin Golzar is an Assistant Professor at KTH Royal Institute of Technology, affiliated with the Heat and Power Technology Division under the Digital Futures Faculty. His research focuses on sustainable energy systems, AI-driven environmental solutions, and circular economy strategies. He is part of a cross-disciplinary initiative at Digital Futures, addressing societal challenges through digital technology innovation. Key research interests include energy transition pathways for oil-dependent economies, optimization of renewable energy systems (e.g., solar-battery hybrids), and AI applications for CO₂ emission prediction. He also explores urban circularity through waste stream management and landfill site identification using GIS-AHP frameworks. His work spans technical-economic analyses of energy systems, battery degradation modeling, and symbiotic food-energy systems (e.g., biogas from manure for greenhouses). Recent studies emphasize climate policy implications and long-term sustainability in urban environments like Stockholm and Curitiba, Brazil. Advising and grants details are not explicitly provided in the text. He collaborates with institutions like RISE Research Institutes of Sweden and Stockholm University through Digital Futures. His lab/center, Digital Futures, is based at Osquars Backe 5, Stockholm.

• Software Engineering
• Decision Models
• Framework Evolution
• +۶ مورد دیگر

Michael Mattsson is a Professor in the Department of Software Engineering at Blekinge Institute of Technology (Faculty of Computing). His research focuses on software engineering practices, particularly in decision models for asset selection, framework evolution, and software architecture evaluation. Industrial collaboration and empirical validation are central to his work. Research Themes: Decision models, framework stability, quality attribute trade-offs, and industrial software evaluation. Projects: Completed the VITS project on test data visualization and contributed to the ORION project (funded by the Knowledge Foundation). Publications: Key topics include asset selection surveys, framework evolution comparisons, and systematic mapping studies in software engineering.

• Automation Engineering
• Production Simulation
• Multi-Objective Optimization
• +۷ مورد دیگر

Amos H.C. Ng is a Professor of Automation Engineering at the School of Engineering Science, University West (Högskolan i Skövde). His academic qualifications include BEng, MPhil, and PhD degrees, complemented by professional certifications such as Chartered Engineer (UK) and membership in the Institution of Engineering and Technology (UK). His research focuses on production simulation, multi-objective optimization, simulation-based innovization, and digital human modeling, with applications in manufacturing systems, Industry 4.0, and smart manufacturing. Ng has contributed to over 150 publications since 2000, spanning topics like decision support systems, maintenance optimization, and reconfigurable manufacturing. His work integrates simulation, data mining, and evolutionary algorithms to address challenges in production systems, including bottleneck analysis, energy efficiency, and human-robot collaboration. Notable projects include developing the Mimer knowledge discovery tool and frameworks for digital twin applications in production lines. His research emphasizes practical industry applications, collaborating with organizations to improve production processes through advanced methods like trend mining and cloud-based optimization. Ng also serves as a course coordinator and contributes to educational initiatives in automation engineering.