جستجوی استاد راهنمای دانشگاهی

• Cyber-Physical Systems
• Machine Learning
• Self-Adaptive Systems
• +۴ مورد دیگر

Dr. Ilias Gerostathopoulos is an Assistant Professor at the Faculty of Science, Vrije Universiteit Amsterdam, affiliated with the Network Institute and the Department of Information Management & Software Engineering. He specializes in self-adaptive systems, cyber-physical systems, and machine learning operations (MLOps). His work focuses on software architectures for autonomous systems, decision-making under uncertainty, and experiment-driven adaptation frameworks. He teaches courses such as 'Fundamentals of Adaptive Software' and 'Information Management', emphasizing practical applications of adaptive systems and data-driven decision-making. Gerostathopoulos has been awarded the Best Presentation Award (2021) for contributions to evaluating self-adaptive systems. His research addresses challenges in industrial self-adaptation, MLOps architectures, and robotics. Key research themes include: Architecture-based self-adaptation in robotics and CPS MLOps frameworks and systematic analysis of AI systems Uncertainty management in autonomous systems Experiment-driven learning and tool development Notable contributions include the ExpEngine tool for workflow optimization and the ReBeT framework for robotic systems. His work bridges theoretical software engineering with practical industrial implementations.

Justus Bognerمشاهده پروفایل

استادیار

• Microservices
• Artificial Intelligence
• Software Engineering
• +۳ مورد دیگر

Justus Bogner is an Assistant Professor at the Faculty of Science, Vrije Universiteit Amsterdam, affiliated with the Software and Sustainability (S2) department and the Network Institute. His research focuses on microservices architecture, AI/ML system sustainability, and software engineering practices. He teaches courses like Service Oriented Design and Software Design. Research Interests: Bogner’s work explores the intersection of AI and sustainable software engineering, including energy-efficient microservices, explainable AI (XAI), and MLOps architectures. He emphasizes empirical studies, systematic mappings, and controlled experiments to address challenges in software quality, design patterns, and trade-offs between performance and environmental impact. Awards: Best Presentation Award (2021) Distinguished Artifact Award (2024) Distinguished Artifact Award (2024) Distinguished Paper Award (2024) Grants/Advising: His work has been supported by grants focusing on empirical software engineering and sustainable AI. He collaborates on datasets analyzing technical debt in AI systems and green AI practices.

A.E. Zaidmanمشاهده پروفایل

استاد

• Software Testing
• Test Amplification
• Mutation Testing
• +۶ مورد دیگر

A.E. Zaidman is a Professor in the Software Technology department at Delft University of Technology's Faculty of Electrical Engineering, Mathematics and Computer Science. His research focuses on software testing, code quality, and developer tooling, with recent emphasis on socio-technical factors, environmental impacts of testing, and GitHub Actions workflows. Key Research Areas Test amplification (developer interactions with automated testing) Code smell detection and its impact on software quality Empirical studies in open-source software testing AI/ML applications in test generation and analysis Scientific Awards Best Artifact Award (2022) Best Emerging Results Paper Award (2018) Best ERA paper award (2015) Best tool demo paper award (2017) ICPC 2009 Best Paper Award Recent Publications 2025: Systematic mapping of qualitative software testing methods 2025: Industrial language engineering case studies using Spoofax 2024: Environmental impact analysis of Java testing 2024: GitHub Actions workflow smell investigations

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

Nishant Saurabh is a tenured Assistant Professor at the Department of Information and Computing Sciences , Utrecht University , Netherlands. His research focuses on resource and data management , application scheduling , performance modeling , and optimization in large-scale hybrid distributed systems including Cloud, Edge, and Quantum computing. Recently, he has expanded into ML workload scheduling and causal performance attribution across the Cloud-Edge continuum. Research Expertise : Distributed Systems and Cloud Computing Quantum-HPC Middleware Systems Performance Modeling and Optimization ML/AI Workload Scheduling Cloud-Edge Continuum Architectures Observability Frameworks Scientific Leadership : Associate Editor, Springer's Journal of Cloud Computing Editorial Board, Frontiers of AI book series IBM HPC-Quantum Working Committee member Workshop Chair, IEEE IPDPS 2025 Supervision : He has supervised 16+ Master/Bachelor students on projects including container migration, reinforcement learning for serverless computing, and quantum middleware evaluation. Current PhD students include Diogo Landau (Performance Observability), Nathan Keyaerts (LLM Methods), and Negar Alizadeh (Energy Efficiency).

Andrea Capiluppiمشاهده پروفایل

دانشیار

• Open Source Software
• Software Development
• Software Maintenance
• +۳ مورد دیگر

Andrea Capiluppi is an Associate Professor at the University of Groningen's Faculty of Science and Engineering, Department of Software Engineering — Bernoulli Institute. His research focuses on open source software, software development processes, natural language processing, and machine learning applications in software engineering. He holds roles including Member of the Board of Examiners and Member of the Governing Board of the Thematic Digital Competence Centre (TDCC) for NES. Research interests span open source technologies, software component analysis, software maintenance, and applying NLP to software traceability. His work bridges empirical studies with practical software engineering challenges, such as developer sentiment analysis and legacy code refactoring. He has published over 110 papers, contributing to areas like technical debt detection, code obfuscation impact, and academia-industry collaboration models. No awards are explicitly mentioned, but his leadership roles reflect academic and institutional contributions. He advises on software ecosystems and innovation dynamics, with ongoing projects involving automated software classification and traceability in DevOps environments.

Victoria Degelerمشاهده پروفایل

استادیار

• Computer Science
• Artificial Intelligence
• Software Engineering
• +۴ مورد دیگر

Victoria Degeler is an Assistant Professor at the University of Groningen’s Faculty of Science and Engineering, affiliated with the Bernoulli Institute. Her research focuses on AI-driven solutions for complex systems, combining expertise in artificial intelligence, software engineering, and service-oriented computing. She actively contributes to EU Horizon initiatives through her role in evaluating projects for the EC REA and EASME. Her work emphasizes real-world applications such as digital twins for infrastructure optimization, machine learning for IoT systems, and adaptive service architectures. Her research interests span digital twins in water distribution networks, quality-aware IoT processing, and machine learning methodologies. Notable projects include developing self-adaptive service selection frameworks and analyzing human activity recognition biases. She collaborates widely, evidenced by co-authored publications in top-tier conferences and journals.

Damian Tamburriمشاهده پروفایل

دانشیار

• DevOps
• DataOps
• Big Data Software Engineering
• +۷ مورد دیگر

Damian Tamburri is an Associate Professor (Part-time) at Eindhoven University of Technology and the Jheronimus Academy of Data Science (JADS) in s'Hertogenbosch, Netherlands. His work bridges technical, social, and organizational dimensions of DevOps, DataOps, and AI-driven data engineering. Affiliated with JADS' Data Governance group ACM TOSEM Associate Editor Secretary of TOSCA TC, IFIP TC2/TC6/TC8 WG Research Focus: His research explores the intersection of data-intensive systems, service-oriented architectures, and ethical AI. Key areas include: LLMOps and DevOps maturity in industry Federated Learning optimization via SOA principles Decentralized data architecture (data mesh) Dark web illicit content detection using neural networks Publication Trends: Recent work emphasizes operationalizing AI/ML systems in distributed environments, with 80% of 2025 publications addressing services computing challenges. Topics span federated learning (2025), dementia detection (2025), and data mesh governance (2025). Grants & Collaborations: Active in EU-funded research with involvement in Horizon Europe projects (grant 101137301) and Innovative UK partnerships. His studies combine academic rigor with industry insights from major logistics providers. Key Contributions: He has developed novel approaches to: SOA-enhanced federated learning frameworks Hybrid models for dementia early detection Reference architectures for data mesh Label-agnostic neural networks for dark web monitoring

• Supply Chain Management
• Enterprise Architecture
• Business Information Systems
• +۳ مورد دیگر

Jos van Hillegersberg serves as Full Professor in Industrial Engineering & Business Information Systems, demonstrating extensive scholarly contributions with 201 research outputs including 62 articles and 82 conference contributions. His academic profile shows consistent productivity across two decades with significant publication volumes in peak years like 2015 (19 outputs). Research interests center on Supply Chain Management (73% fingerprint weight), Enterprise Architecture, Business Information Systems, and emerging domains like Low-Code Development and AI applications. His work bridges computer science with practical business engineering challenges, particularly in supply chain optimization and digital transformation across multiple sectors. Recent publication trends (2023-2025) reveal strong interdisciplinary focus: agricultural data privacy systems, AI-driven healthcare solutions for diabetes, public sector DevOps optimization, and construction logistics control towers. These works consistently address real-world implementation challenges while maintaining theoretical rigor in enterprise modeling and systems engineering. With an h-index of 28 and 2900+ Scopus citations, Professor van Hillegersberg actively shapes academic discourse through leadership roles including chairing the 11th International Workshop on Enterprise Applications in Finance (FinanceCom 2022). His supervision of 32 students demonstrates commitment to developing next-generation researchers in business information systems.

• Enterprise Architecture
• Software Engineering
• Digital Transformation
• +۵ مورد دیگر

Adina Aldea serves as a Researcher in Financial Engineering at the University of Twente, with a prolific publication record spanning 2013-2025 (37 research outputs, h-index 12, 391 Scopus citations). Her work bridges theoretical enterprise architecture with practical digital transformation initiatives, particularly in public sector organizations and rural communities across Southeast Asia. Her research fingerprint reveals deep expertise in Enterprise Architecture (100% prominence), Models (88%), Design (79%), and Contextual Evaluation (35-49% across subdomains). Current investigations focus on context-capability alignment in DevOps teams, service-oriented rural smartness platforms, and resilience measurement instruments for digital transformation. This work consistently employs case studies and action research methodologies, emphasizing real-world validation in underserved regions like West Java. Recent publications (2022-2025) demonstrate a clear trajectory toward solving practical challenges in public sector IT modernization and rural digital inclusion. Her collaborative approach integrates enterprise architecture principles with community-driven development, producing actionable frameworks for capability alignment and platform implementation. The recurring emphasis on contextual factors highlights her distinctive contribution to adapting theoretical models for complex organizational environments. Scientific Awards: No awards, prizes, or fellowships were documented in the available profile information. Adina Aldea has supervised at least one graduate student as indicated by the 'Supervised Work (1)' metric, though specific details remain undisclosed. Her consultancy engagements—including 'Data as a Service' initiatives (2016) and 'Personal Data Stores' projects (2015)—demonstrate applied research impact in open data ecosystems, though no institutional grant funding is explicitly referenced in the provided materials.

Mairieli Wesselمشاهده پروفایل

استادیار

• Software Engineering
• Computer Supported Cooperative Work (CSCW)
• Open Source Software (OSS)
• +۳ مورد دیگر

Dr. Mairieli Wessel is an Assistant Professor at the Department of Software Science, Radboud University (Netherlands) , focusing on the intersection of Software Engineering (SE) and Computer Supported Cooperative Work (CSCW) . Her research explores how software bots can enhance collaboration in Open Source Software (OSS) communities. PhD in Computer Science from University of São Paulo (USP) (2021) Postdoctoral Researcher at Delft University of Technology (2021-2022) Visiting PhD Student at Concordia University (2021) Her recent work examines GitHub Actions , code review bots , and bot comment analysis . She serves as Guest Editor for IEEE Software and chairs tracks at MSR and CHASE conferences. 2024 Best Runner-up Paper (AST) 2024/2022 Distinguished Reviewer Awards (ICPC, MSR) 2020 IEEE TCSE Distinguished Paper Award (ICSME) Dr. Wessel actively supervises PhD students and develops tools like BotHunter for bot detection. Her practical experience includes software development roles at IBM Research and 4Makers STEM Education .

Damian A. Tamburriمشاهده پروفایل

دانشیار

• DevOps
• DataOps
• Big Data
• +۳ مورد دیگر

Dr. Damian A. Tamburri is an Associate Professor at Eindhoven University of Technology and the Jheronimus Academy of Data Science (JADS), The Netherlands. His research focuses on DevOps and DataOps architectures, properties, and tools from technical, social, and organizational perspectives. He has published over 100+ papers in top journals/conferences on Big Data, Software Engineering, AI Information Systems, and Cloud Computing. Tamburri leads EU-funded projects like S-Cube, MODAClouds, and SODALITE, and serves as ACM TOSEM Associate Editor and Secretary of IFIP TC2/TC6/TC8 WG on Service-Oriented Computing. His work addresses challenges in synthetic data generation, vulnerability management, and DevOps maturity. Tamburri collaborates internationally, contributing to large-scale studies on socio-technical congruence in software development and cloud applications monitoring. His datasets (e.g., on CI/CD practices in cyber-physical systems) and tools (e.g., AnsibleMetrics) are widely shared via repositories like Zenodo and Code Ocean. Tamburri teaches the 'Data Engineering' course since 2018. He advises students on EU projects and actively publishes in venues like ACM Transactions on Software Engineering and Methodology. His research aligns with UN Sustainable Development Goals through innovations in data governance and cloud-native systems.

Katja Tumaمشاهده پروفایل

پژوهشگر ارشد

• Cybersecurity
• Threat Analysis
• Security Design
• +۷ مورد دیگر

Katja Tuma is a Visiting Research Fellow at the Vrije Universiteit Amsterdam, affiliated with the Faculty of Science's Computer Systems department and the Network Institute. Her primary research focuses on cybersecurity, threat analysis, and secure software design. She explores the intersection of human factors, artificial intelligence, and traditional security practices to enhance system resilience. Affiliations: Faculty of Science, Network Institute, Computer Systems Key Research Areas: Threat Modeling, Security Compliance, Large Language Models in Security, Gender Dynamics in Security Training Her work emphasizes practical applications such as automated security repair, validation of security designs using data flow diagrams, and addressing human biases in security decision-making. Tuma has contributed to projects like a training framework for industrial cybersecurity skills and certification mechanisms for software supply chains. Recent publications highlight challenges in using LLMs for code generation, the role of gender in security evaluations, and improving threat analysis replication methodologies. She teaches courses on data structures for AI and security experiments, bridging theoretical concepts with real-world applications. Notable Projects: Personalized Cybersecurity Training Framework (2023), Assurance in Open Software (2020-2023) Her research also addresses emerging areas like AI-augmented security pipelines and uncertainty management in AI-driven threat intelligence, reflecting a commitment to both technical innovation and socio-technical security challenges.

• Artificial Intelligence
• Ontology Engineering
• Internet of Things (IoT)
• +۵ مورد دیگر

João Luiz Rebelo Moreira is an Assistant Professor at the University of Twente, specializing in Artificial Intelligence, Ontology Engineering, and IoT Interoperability. His research focuses on semantic technologies, explainable AI, FAIR data principles, and their applications in healthcare, smart industries, and enterprise systems. He contributes to UN Sustainable Development Goals related to health, smart industries, and sustainable consumption. His expertise includes ontology-driven systems, machine learning workflows, and data governance frameworks. Notable achievements include the FOIS 2018 best paper award for SAREF4health, an ontology for IoT-based healthcare systems. He collaborates internationally on projects like SEMIoTICS (semantic IoT interoperability) and OpenPREDICT (FAIR workflows in drug discovery). Research Interests: Ontology Engineering, Explainable AI, FAIR Data, IoT Standards, Enterprise Architecture Key Projects: OpenPREDICT, SEMIoTICS, Personal Health Trains Collaborations: Port of Valencia IoT EWS, VODAN Brazil Health Network Publications span over 40 works in conferences like EDOC, FOIS, and ER, focusing on semantic interoperability, machine learning explainability, and IoT standardization. He actively reviews for journals and organizes workshops on ontology-driven systems and FAIR data practices. His datasets include work on FAIR protocols (Zenodo) and healthcare data management studies. Current research trends emphasize integrating AI ethics, digital product passports, and data mesh architectures for decentralized systems.

Stijn Hoppenbrouwersمشاهده پروفایل

مدرس

• Data & Knowledge Engineering
• Information Systems
• Data Governance
• +۴ مورد دیگر

Stijn Hoppenbrouwers is a lecturer and researcher at HAN University of Applied Sciences, affiliated with the Data & Knowledge Engineering Research Group. He holds a PhD in Computer Science and has over 30 years of experience in the interplay between language, information, knowledge, users, and systems. His expertise includes data governance, knowledge engineering, and collaborative modeling frameworks. He co-founded the part-time Master's program in Data Science at HAN and collaborates with institutions like Radboud University and TU/e. His research focuses on human-centered design of information systems, integrating socio-technical perspectives with computational methods. Key projects include the Bird's Eye Perspective (BEP27) learning environment, ICAI Lab for Energy Grids (AI-driven energy solutions), and the DEMAND project addressing data integration challenges. He also explores tax rule formalization (RegelSpraak) and healthcare predictive analytics. Stijn is active in knowledge transfer, serving on the ERDF-East expert committee and collaborating with municipalities, government agencies, and industry partners. His work emphasizes practical applications of AI, data engineering, and conceptual modeling in both academic and industrial contexts.

Gayane Sedrakyanمشاهده پروفایل

استادیار

• Artificial Intelligence
• Human-Computer Interaction
• Health Informatics
• +۶ مورد دیگر

Gayane Sedrakyan serves as an Assistant Professor in the Department of Industrial Engineering & Business Information Systems, with research spanning computer science, healthcare, education, and food systems. Her work bridges theoretical frameworks with practical applications of emerging technologies across critical societal domains. Her research focuses on human-centric AI systems, particularly in health equity and educational technology. She investigates semantic interoperability in food systems, low-code security frameworks, and digital feedback mechanisms in post-pandemic education. Key areas include explainable AI for reproductive healthcare, privacy-aware agricultural data platforms, and chatbot integration in learning management systems, all emphasizing user experience and ethical design. Recent publication trends reveal three dominant trajectories: healthcare applications (human-centric recommender systems for health equity), educational innovation (AI chatbots in Education 5.0 and hybrid classroom feedback), and sustainable food systems (cross-sectoral data platforms and semantic tools). Her work consistently integrates process-oriented security in low-code development while addressing societal challenges through interdisciplinary approaches. Dr. Sedrakyan actively contributes to academic discourse through community building, having co-organized the 2023 Workshop on Controlled Vocabularies and Data Platforms for Smart Food Systems, which advanced collaborative research in food system digitization.