جستجوی استاد راهنمای دانشگاهی

Cyrille Arthoمشاهده پروفایل

دانشیار

• Software Engineering
• Formal Methods
• Cybersecurity
• +۵ مورد دیگر

Cyrille Artho is an Associate Professor in the Division of Theoretical Computer Science at KTH Royal Institute of Technology, actively contributing to research in formal methods, software testing, and cybersecurity. His work spans model checking, smart contract security, and concurrent systems verification, with significant contributions to tools like Java Pathfinder and Modbat. PhD from ETH Zurich (2005) with dissertation on multi-threading fault detection Teaches Software Safety and Security, Software Engineering Fundamentals, and supervises degree projects His research focuses on developing formal techniques for safety-critical systems, particularly in blockchain security and distributed applications. Recent work emphasizes smart contract verification, anomaly detection in microservices, and trusted execution environments for secure cloud analytics. The 15 most recent publications reveal a strong trend toward blockchain security (6 articles), formal verification of distributed systems (5), and novel testing methodologies (4), with increasing integration of machine learning for vulnerability detection. As chair of the FTSCS workshop series and contributor to major conferences like ASE and ICST, Artho has significantly shaped the formal methods community. His leadership in organizing workshops demonstrates commitment to advancing safety-critical systems research. Principal investigator for C3.ai DTI Cyber Safety Cage for Networks project Develops Modbat framework for model-based API testing Active in Digital Futures research initiative at KTH

• Distributed Systems
• Machine Learning
• Big Data
• +۳ مورد دیگر

Jim Dowling is a distributed systems researcher at KTH Royal Institute of Technology, focusing on large-scale distributed systems, machine learning, and big data. His work emphasizes improving system dependability, performance, security, and scalability through middleware, peer-to-peer systems, and cloud-native solutions. He leads courses such as Advanced Course in Large Scale Machine Learning and Deep Learning and Scalable Machine Learning and Deep Learning , demonstrating his commitment to education in AI and distributed computing. His research spans topics like feature stores, Kubernetes integration, and AI-driven environmental analytics (e.g., ANIARA project for edge infrastructure automation and ExtremeEarth for Copernicus data analysis). He has contributed to scalable ML pipelines, cloud storage systems (HopsFS-S3), and hyperparameter optimization tools like Maggy. Key projects include the Hopsworks platform for machine learning operations and the development of cloud-native tools for big data analytics. His work bridges theoretical distributed systems research with practical applications in AI, healthcare, and environmental science. He has advised on numerous collaborative initiatives but no formal students are listed. His grants and lab activities are centered around Hopsworks and the ANIARA project, reflecting his focus on scalable, self-managing systems.

Vladimir Vlassovمشاهده پروفایل

استاد

• Machine Learning
• Data-intensive computing
• Cloud computing
• +۷ مورد دیگر

Dr. Vladimir Vlassov is a full Professor in Computer Systems at the Division of Software and Computer Systems (SCS) , Department of Computer Science (CS) , School of Electrical Engineering and Computer Science (EECS) , KTH Royal Institute of Technology , Stockholm, Sweden. He leads the AVA project in ALEC2, an AI-powered system for mental health care. He is a member of the Distributed Computing research group (DC@KTH) . Education & Roles: Holds a PhD and is a member of ACM and IEEE. Previously visited MIT (1998) and UMass Amherst (2004). Teaches courses on Data Mining , Distributed Systems , and Concurrent Programming . Research Interests: Focus on scalable AI, Cloud computing, distributed systems, and NLP for mental health. Projects include ExtremeEarth (Copernicus data analytics) and EMJD-DC (distributed computing PhD program). Grants & Projects: Principal Investigator in ALEC2 (adaptive mental health care) and ExtremeEarth (EU H2020). Led EU projects like ENCORE (manycore systems) and PaPP (embedded systems). Labs & Teams: Directs the Distributed Computing group, contributing to Hopsworks (machine learning feature store) and Maggy (hyperparameter optimization).

Muhammad Usmanمشاهده پروفایل

مدرس ارشد

• Cloud Computing
• Edge Computing
• Distributed Systems
• +۷ مورد دیگر

Dr. Muhammad Usman is a Senior Lecturer at the Department of Mathematics and Computer Science, Karlstad University, Sweden. His research focuses on cloud and edge computing, distributed systems, performance observability, DevOps automation, and networked systems. He holds a B.S. from NUST (Pakistan), and integrated M.S./Ph.D. from GIST (South Korea). He teaches master's-level courses in Distributed Systems and Cloud Computing. His research interests include optimizing container orchestration for edge-IoT workloads, developing AI-driven frameworks for industrial IoT (e.g., AIDA), and enhancing observability of distributed systems through frameworks like DESK and SmartX. His work often addresses challenges in resource efficiency, scalability, and fault detection in edge and cloud environments. Notable contributions include benchmarking lightweight container orchestration platforms, designing cost-effective testbeds for DevSecOps, and creating visualization frameworks for SDN-enabled clouds. His publications span topics from IIoT lifecycle management to intent-based network control. Usman actively collaborates internationally, with projects involving institutions like GIST, Aalto University, and the IEEE community. His work bridges theoretical research and practical applications in edge computing and cloud-native systems.

• Theoretical Computer Science
• Software Engineering
• Computer Security
• +۴ مورد دیگر

Frank Reyes García is a doctoral student and researcher at the Royal Institute of Technology (KTH), affiliated with the Division of Theoretical Computer Science. His work focuses on software engineering, particularly in the areas of dependency management, automated software testing, and DevOps. Assistant for Automated Software Testing and DevOps (DD2482) Assistant for Computer Security (DD2395) Assistant for Introduction to the Philosophy of Science and Research Methodology for Computer Scientists (DA2210) Assistant for Software Engineering Fundamentals (DD2480) His recent research explores breaking dependency updates in software ecosystems, reproducibility challenges, and build analysis techniques. He has published peer-reviewed work in conferences like SANER 2024 and SCAM 2024, alongside non-peer-reviewed contributions such as the SIGBOVIK 2025 submission. Contact: frankrg@kth.se

Benoit Baudryمشاهده پروفایل

استاد

• Software Engineering
• Software Testing
• Blockchain Technology
• +۴ مورد دیگر

Benoit Baudry is a Professor in Software Technology at KTH Royal Institute of Technology (KTH) within the Digital Futures Faculty and Division of Theoretical Computer Science. He also holds a professorship at Université de Montréal. His research focuses on software diversity, testing, and reliable web-based applications, emphasizing experimental approaches using large-scale open-source systems. He leads the CHAINS project (supported by SSF) and holds a Wallenberg AI, Autonomous Systems and Software Program (WASP) research chair. Previously, he directed the CASTOR software research center (2018–2022) and led the DiverSE group at INRIA Rennes, France. Research Interests Baudry's work spans software supply chain security, blockchain node reliability, and production monitoring for test suite improvement. He explores techniques like N-version design for blockchain nodes, binary diversification for WebAssembly, and coverage-based debloating of Java dependencies. His methods emphasize collaboration with industry and empirical validation of software systems. Grants & Projects - CHAINS project (SSF-funded) - WASP research chair - Former leadership of CASTOR and DiverSE groups. Labs & Collaborations Affiliated with Digital Futures, a cross-disciplinary center at KTH collaborating with Stockholm University and RISE. His work addresses societal challenges via digital technology innovation.

Wasif Afzalمشاهده پروفایل

استاد

• Software Testing
• Model-Based Testing
• Embedded Systems
• +۴ مورد دیگر

Wasif Afzal is a Professor at Mälardalen University, affiliated with the School of Innovation, Design and Engineering and the Division of Networked and Embedded Systems. His primary role includes duties as an orientation representative for the school. His research focuses on software testing methodologies, model-based testing, embedded systems, cybersecurity, and blockchain applications, with significant contributions to industrial collaborations. Key research interests include advancing automated testing frameworks, optimizing test case generation and prioritization, and enhancing cybersecurity through innovative approaches like serious gaming for phishing resilience. He has led projects such as the SmartDelta initiative, which addresses automated quality assurance in industrial software systems, and contributed to EU-funded projects like Adeptness for DevOps integration in cyber-physical systems. His recent work explores gaps in software testing education, leveraging machine learning for test reduction, and applying EARS notation for PLC system requirements validation. Over 50 publications reflect his expertise in testing tools, safety-critical systems, and systematic literature reviews in software engineering. Notable projects include developing the Pylc framework for PLC software validation and exploring blockchain applications for food safety. He actively engages in improving test automation strategies and measurable outcomes in safety-critical domains.

Rebekka Wohlrabمشاهده پروفایل

استادیار

• Requirements Engineering
• Software Architecture
• Self-Adaptive Systems
• +۴ مورد دیگر

Rebekka Wohlrab is a tenure-track Assistant Professor in Software Engineering at Chalmers University of Technology (Gothenburg, Sweden) and an adjunct faculty member at Carnegie Mellon University’s Software and Societal Systems Department (S3D). Her research focuses on requirements engineering, self-adaptive systems, and robotics. She leads a research group supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP). Education: PhD in Computer Science and Engineering (Chalmers, 2020), MSc/BSc in Computer Science (Paderborn University, 2016). Postdoc at Carnegie Mellon University (2020-2022). Research interests include requirements conflicts resolution, quality attribute trade-offs, and ethical monitoring in cyber-physical systems. She has published extensively on adaptive systems, architectural tactics, and agile development practices. Notable contributions include frameworks for robot mission planning, security assurance cases, and traceability management in automotive systems. Recent awards include a pedagogical prize from students at Chalmers. She advises PhD students on topics like self-adaptive robotics and WASP-funded projects. Her work spans theoretical research and industry collaboration (e.g., Volvo Cars). Active in conferences like ICSE, RE, and ICSA as a program committee member. Labs/Teams: Leads the Self-Adaptive Systems Research Group at Chalmers, collaborating with WASP and automotive industry partners.

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.

• Software Engineering
• Agile Development
• DevOps
• +۴ مورد دیگر

Binish Tanveer serves as a Senior Lecturer at Stockholm University's Department of Computer and Systems Sciences, located at Nodhuset, Borgarfjordsgatan 12 in Kista. With an active presence in both teaching and research, Tanveer contributes to the academic community through publications and scholarly work in software engineering disciplines. Research interests center around practical software engineering challenges with strong emphasis on agile methodologies, effort estimation techniques, and DevOps practices. The work demonstrates particular attention to the human aspects of software development, including socio-technical dependencies, code ownership models, and sustainable engineering practices that consider developer well-being. Recent publications show a clear progression from foundational work in effort estimation toward more complex investigations of socio-technical systems and sustainable development practices. Analysis of publication trends reveals consistent scholarly output focused on bridging theoretical software engineering concepts with industrial applications. The research portfolio demonstrates expertise in systematic literature review methodologies while maintaining practical relevance to software industry challenges. Key thematic areas include the application of change impact analysis to improve estimation accuracy, investigation of ownership models in collaborative development environments, and exploration of sustainable practices that balance technical requirements with human factors.

Leonardo Iwayaمشاهده پروفایل

مدرس ارشد

• Privacy Engineering
• Information Security
• Human Factors in Technology
• +۴ مورد دیگر

Leonardo Iwaya is an Associate Senior Lecturer in Computer Science at Karlstad University, Sweden, specializing in privacy engineering, information security, and digital health systems. He holds a PhD in Computer Science from Karlstad University (2019) and a Docent degree (2025). His research focuses on privacy impacts of AI-driven health apps, human-centric cybersecurity, and organizational privacy culture. He leads the DHINO (Digital Health Innovation) research group and collaborates internationally with institutions like the University of Adelaide and UFSC (Brazil). Key projects include OPErationalising Human Rights in AI-supported Digital Health (2025–), TRUstworthy huMAN-centric AI (2025–), and NUSO (National Follow-up of Social Services Transition). He teaches courses on computer security, privacy-enhancing technologies, and ethical hacking. His work bridges technical security solutions with human factors, emphasizing practical applications in healthcare. He has published extensively in top venues like IEEE Access, International Journal of Medical Informatics, and NordSec conferences. Research highlights include empirical studies on mHealth app security, privacy impact assessments, and Docker development challenges. He advises students on topics such as ethical hacking and healthcare system usability.

Meiko Jensenمشاهده پروفایل

دانشیار

• Cybersecurity
• Privacy Engineering
• Data Protection
• +۷ مورد دیگر

Meiko Jensen is an Associate Professor at Karlstad University specializing in Cybersecurity, with a focus on privacy engineering, data protection, and GDPR compliance. Her work bridges technical solutions with legal frameworks, emphasizing practical implementations of privacy principles in evolving digital landscapes. Research interests include corporate cybersecurity resilience, privacy-preserving technologies, forensic strategies in advanced networks, and ethical challenges in emerging technologies like the Metaverse. She has contributed to EU-wide initiatives on data sharing models and personal data protection standards, particularly through collaborations with ENISA and academic networks. Recent publications explore ransomware mitigation strategies in Nordic enterprises, consent management systems under the GDPR, and frameworks for privacy engineering. Her work often integrates interdisciplinary approaches, addressing both technical vulnerabilities and regulatory requirements. Notable contributions include protocols for privacy-aware contact tracing in campus environments and methodologies for automating data subject rights fulfillment. Her research underscores the importance of aligning technological innovation with robust privacy protections. Awards and recognitions are not explicitly stated in the provided materials, but her extensive publication record reflects sustained academic impact in cybersecurity and privacy fields. She advises on interdisciplinary projects at the intersection of law, technology, and policy, though student advisees are not listed here. Professional activities include editorial roles and conference participation in privacy and data protection forums.

Eduard Paul Enoiuمشاهده پروفایل

دانشیار

• Software Engineering
• Empirical Research
• Automated Test Generation
• +۷ مورد دیگر

Eduard Paul Enoiu is an Associate Professor at Mälardalen University's Department of Networked and Embedded Systems, affiliated with the Software Testing Laboratory and Formal Modelling and Analysis groups. He holds a PhD from Mälardalen University (2016) and an Engineer's degree from Polytechnic University of Bucharest (2009). His research focuses on software engineering, empirical studies in testing, automated test generation, and model-based verification. He teaches automated testing at master’s/PhD levels and industrial practitioners. Current research includes cognitive aspects of testing, ethical considerations, and applying AI in DevOps security. He advises theses in software testing and embedded systems development. **Education:** PhD in Software Engineering (2016), Mälardalen University Engineer's degree (2009), Polytechnic University of Bucharest **Research Interests:** Automated test generation and optimization Formal verification of embedded systems Cognitive psychology in software testing Requirements engineering and reuse Security validation in DevOps Ethical and human factors in testing **Labs/Teams:** Software Testing Laboratory Formal Modelling and Analysis of Embedded Systems group

Peter Rittgenمشاهده پروفایل

استاد

• Business Process Modeling
• Collaborative Process Improvement
• Information Systems
• +۳ مورد دیگر

Peter Rittgen is a full-time Professor at the University of Borås, affiliated with the School of Business and IT and the Department of Information Technology. He specializes in process improvement with a focus on collaborative business process modeling and serves as Program Manager for the Master's Program in Informatics - Datadriven IT Management. PhD in Computer Science, Linguistics, Business Science, and Informatics (Koblenz and Frankfurt) His research explores group consensus in process modeling, collaboration capability assessment, and the integration of business processes with information systems. He has pioneered metrics for consensus in collaborative modeling and investigated the role of tools in distributed design. His work intersects with software engineering, organizational theory, and data-driven innovation. Recent publications highlight trends in DevOps collaboration, formal process modeling, and ontological frameworks for business systems. He has also contributed to the design of UML-based models and interorganizational process coordination. As project manager for the subproject 'Digital Platforms for Service Innovation' (2016), he bridges academic research with practical IT governance. His career spans over 25 years of modeling methodologies, including UML extensions and language-action approaches.

Markus Borgمشاهده پروفایل

مدرس ارشد

• Software Engineering
• Artificial Intelligence
• Requirement Engineering
• +۵ مورد دیگر

Dr. Markus Borg is an Adjunct Senior Lecturer at the Department of Computer Science, Lund University, and a Principal Researcher at CodeScene. He specializes in software engineering and applied artificial intelligence, with affiliations to the Software Engineering Research Group, LTH Profile Area for AI and Digitalization, and ELLIIT. His roles include project management and supervision within initiatives like the NEXTG2COM Competence Centre. Research focuses on software engineering, AI compliance, requirement engineering, and developer happiness. He contributes to Empirical Software Engineering and IEEE Software . Recent work addresses AI Act compliance challenges, gamification in software tools, and organizational resilience. Received the Best Paper Award in 2015. Leads projects like REFORGE (LLM-assisted refactoring safeguards) and Continuous Quality Assurance for Trustworthy AI. Active in organizing workshops/seminars on AI-assisted development and developer happiness. His research spans 76 publications and involves collaborations across academia and industry.