Find Academic Supervisors

• Artificial Intelligence
• Data Science
• Generative AI
• +7 more

Jan Kirenz is a Professor at Stuttgart Media University of Applied Sciences (HdM Stuttgart) and a freelance Consultant, Lecturer, and Data Scientist specializing in Generative AI and data science. With a strong academic foundation, he earned a Doctorate (Dr. oec. publ.) from the Graduate School of Business at the University of Zurich and a Diploma in Business Administration (Operations Research) from the University of Tübingen. His work bridges the gap between technical complexity and practical application, focusing on transformative AI integration for businesses. His research interests center on Generative AI, Machine Learning, and Digital Transformation, with a particular emphasis on Prompt Engineering, agentic AI, and MLOps. He collaborates with companies such as Mercedes-Benz Group, EnBW, and Alfred Kärcher SE & Co. KG to develop tailored AI strategies and solutions. His practical approach ensures measurable results and actionable strategies for enhancing competitiveness. Jan leverages advanced tools and frameworks, including Google Gemini, OpenAI ChatGPT, Anthropic Claude, Hugging Face, Kubeflow, and cloud platforms like Microsoft Azure and Google Cloud AI. He is active in GitHub repositories related to AI development, with a focus on the Model Context Protocol and other cutting-edge technologies. His current projects prioritize practical AI applications for business processes, from prototyping to deployment.

• Software Engineering
• Machine Learning Operations (MLOps)
• Cyber-Physical Systems
• +4 more

Prof. Dr. Klaus Schmid is a Professor in the Department of Software Systems Engineering at the University of Hildesheim, part of the Faculty of Mathematics, Natural Sciences, Economics, and Computer Science. His research focuses on Machine Learning Operations (MLOps), software product lines, adaptive systems, and variability modeling. He leads projects such as EXPLAIN and ReGaP, emphasizing explainable AI and industrial MLOps integration. His work addresses challenges in Cyber-Physical Production Systems (CPPS), including data management, model calibration, and domain knowledge integration. Key research interests include MLOps architecture design, variability modeling transformations (e.g., UVL to IVML), and incremental verification techniques for software product lines. He has published extensively in venues like IEEE ETFA, IEEE Software, and SPLC conferences. Notable achievements include a Best Paper Award for work on control patterns in self-adaptive systems. Collaborations with industry partners highlight his focus on bridging academic research and practical industrial applications. Prof. Schmid’s contributions extend to tool development, such as EASy-Producer for variability-aware software ecosystems, and frameworks for environment modeling in adaptive systems. His research addresses both foundational challenges (e.g., syntax-preserving slicing) and applied topics like MLOps platform comparisons and industrial case studies in Industry 4.0.

Patricia LagoView profile

Professor

• Software Engineering
• Software Architecture
• Software Sustainability
• +4 more

Patricia Lago is a Professor at the Vrije Universiteit Amsterdam, where she leads the Software and Sustainability (S2) research group in the Computer Science Department. She serves as a member of the IEEE ICSA and ECSA Steering Committees, and is the Steering Committee Chair of the ICT4S conference series. Dr. Lago is also the initiator of the Computer Science Master Track in Software Engineering and Green IT, and the director of the Master Information Sciences program. Dr. Lago earned her PhD in Control and Computer Engineering from Politecnico di Torino and a Master in Computer Science from the University of Pisa, both in Italy. Her research focuses on creating software engineering knowledge that makes software better, smarter, and more sustainable. She emphasizes industrial relevance and practical application, focusing on the 'real' needs of practice through collaboration with partners from both private and public sectors. Her specific research areas include software architecture, sustainability, software design and modeling, and software quality assessment. Dr. Lago's recent publications demonstrate a strong trend toward sustainable software engineering, with particular emphasis on energy efficiency, green architectural patterns, and sustainability assessment frameworks. Her work bridges theoretical research with practical applications, especially in areas like robotics, machine learning systems, and cloud computing, where sustainability considerations are increasingly critical. Dr. Lago co-founded the Green Lab, a collaborative space where researchers, students, and companies work together to measure the energy footprint of software solutions. She has been actively involved in numerous conferences and workshops related to software sustainability, serving in leadership roles including as NIER Co-Chair at ICSE 2021.

• Software Systems Engineering
• Industrial Internet of Things (IIoT)
• MLOps
• +9 more

Carsten Wenzel M.Sc. is a researcher at the Software Systems Engineering (SSE) department of the Institute of Computer Science at the University of Hildesheim. His work focuses on advanced software engineering practices within Industry 4.0 , including MLOps , Industrial IoT , and Cyber-Physical Production Systems . He contributes to projects like DevOpt , which explores controlled emergence in distributed systems, and IIP-Ecosphere , developing AI-integrated platforms for industrial applications. His research also intersects with Smart Energy Systems and Edge Computing , emphasizing interoperability and performance optimization. Key Research Areas : Model-driven realization of industrial digital twins Integration of machine learning operations in manufacturing Scalability of Industry 4.0 platforms Performance analysis of IIoT systems Emergent system control architectures Collaborative Projects : DevOpt : Combines distributed and centralized control for adaptive energy networks IIP-Ecosphere : Creates open-source IIoT platforms for cross-company AI-driven production HAISEM-Lab : Focuses on hardware-optimized AI applications and developer training Infrastructure & Outreach : Works with partners like Siemens AG , pdv-software GmbH , and Phoenix Contact on demonstrators at events such as Hannover Messe and ETFA 2024 . The department maintains tools like EASy-Producer for product line engineering and MetricHaven for quality analysis.

Engin ErenView profile

Research Fellow

• Machine Learning
• Deep Learning
• Experimental Particle Physics
• +3 more

Engin Eren is a Software Developer at Helmholtz Imaging since 2023, with a background in experimental particle physics and machine learning research. He previously worked at DESY, contributing to proton structure measurements and CMS group operations at CERN, followed by a private-sector stint as a DevOps engineer. PhD in experimental particle physics (2018), focusing on the Compact Muon Solenoid (CMS) experiment at DESY. Postdoctoral research at DESY (2018-2021) under the Helmholtz AI grant, specializing in Machine/Deep Learning R&D and MLOps for imaging detectors in future linear collider experiments. Current role involves advancing imaging pipelines, deep learning applications, and fostering collaborations with research units at Helmholtz Imaging. His research interests span Machine Learning , Deep Learning , Imaging Detectors , and Scientific Computing , with a focus on integrating AI into experimental physics workflows. Scientific Awards: Helmholtz AI grant (fellowship for postdoctoral research). Engin supports Helmholtz Imaging's IT infrastructure and leads innovation in deep learning pipelines. He is based at DESY's Hamburg campus (Notkestrasse 85, D-22607 Hamburg) and collaborates with DESY IT – Research and Innovation in Scientific Computing (RIC) .

• Artificial Intelligence
• Software Engineering
• Industrial Internet of Things
• +4 more

Christian Severin Sauer is a researcher at the Software Systems Engineering (SSE) group within the Institute of Computer Science at the University of Hildesheim . His work focuses on integrating Artificial Intelligence (AI) with Industrial Internet of Things (IIoT) platforms, particularly in Industry 4.0 applications. He specializes in Case-Based Reasoning (CBR) systems, Self-Organizing Systems , and MLOps for industrial contexts. Education : PhD in Computer Science from the University of West London (2016). Key Projects : DevOpt (controlled emergent systems), IIP-Ecosphere (AI-driven IIoT platforms), HAISEM-Lab (hardware-optimized AI applications). His research explores hybrid control paradigms combining centralized and distributed systems , with applications in smart energy grids and cyber-physical production systems . He has co-authored 15+ papers on topics like performance evaluation of BaSyx middleware , AI in Industry 4.0 , and knowledge formalisation for industrial processes . Recent work includes best practices for MLOps and federated learning in IIoT platforms . Collaborations with industry leaders like Siemens AG , pdv-software GmbH , and Phoenix Contact highlight his commitment to bridging academic research with real-world applications. He actively contributes to open-source tools like myCBR and IIP-Plattform, emphasizing data literacy and experience mining in industrial ecosystems.

Ralf LübbenView profile

Professor

• Computer Networks
• Network Performance Evaluation
• Network Measurements
• +7 more

Ralf Lübben is Professor of Business Informatics specializing in Operating Systems and Computer Networks at Flensburg University of Applied Sciences. He serves as Deputy Head of FLAIR (Flensburg Artificial Intelligence Research) and as Scientific Director of KI-Infrastructure & MLOps. His organizational responsibilities include leadership roles in the KI4FUAS initiative and the KI Application Center (KIAZ), where he focuses on Data Science and Artificial Intelligence infrastructure development. Education: Dr.-Ing. (2013) from Gottfried Wilhelm Leibniz Universität Hannover M.Sc. in Electrical Engineering and Information Technology - Computer Engineering (2007) from Gottfried Wilhelm Leibniz Universität Hannover Dipl.Ing. (FH) in Electrical Engineering - Information Technology (2005) from Private Hochschule für Wirtschaft und Technik Vechta/Diepholz/Oldenburg Lübben's research spans multiple dimensions of computer networking with particular emphasis on performance evaluation methodologies. His work integrates traditional network analysis with cutting-edge machine learning techniques, creating novel approaches for network optimization. Current research directions include transport protocol enhancements, network virtualization techniques, IoT network architectures, and applying AI to solve complex networking challenges. His recent projects explore GPU virtualization in edge computing environments and federated learning applications for vehicular communication systems. Analysis of Lübben's publication history reveals a strong trajectory from traditional network performance evaluation toward AI-integrated networking solutions. Early work focused on TCP congestion control and network measurement methodologies, while recent publications demonstrate increasing integration of machine learning techniques. His 2024 publications show particular emphasis on applying federated learning to vehicular networks and developing novel approaches for GPU virtualization in edge environments, reflecting the convergence of AI and networking research. Lübben actively supervises student projects with published project ideas spanning networking and eHealth domains. His networking project portfolio includes multi-path network access solutions, AI-based network path prediction, and LoRaWAN IoT gateway deployment. The eHealth projects demonstrate interdisciplinary applications of his networking expertise to healthcare contexts. As leader of the FLAIR research group, Lübben oversees infrastructure development for AI research at the university. His technical blog posts reveal hands-on expertise in deploying Kubeflow and Kubernetes infrastructure, with specific focus on GPU integration for machine learning workloads. The group maintains strong industry connections, particularly evident in their work on vehicular communication systems that builds on Lübben's prior industry experience at Robert Bosch GmbH.

Christoph ReichView profile

Professor

• Middleware
• Network Technologies
• IT Security
• +5 more

Christoph Reich is a Professor at Furtwangen University (HFU), Germany, actively engaged in research and teaching within network technologies, IT security, and cloud computing systems. His academic profile reflects strong industry-relevant expertise in cyber-physical systems and industrial digitalization. Research interests include: Middleware Network Technologies IT Security Cloud Computing Quality of Service Ambient Assisted Living Distributed Software Architectures IT Management Recent publications (2020-2023) demonstrate concentrated focus on machine learning and blockchain applications in Industry 4.0 contexts. Key thematic clusters include distributed decision trees with corruption resistance, verifiable ML models via blockchain, real-time anomaly detection in industrial networks, and secure ML pipelines for manufacturing. Work consistently addresses security vulnerabilities, robustness requirements, and quality-of-service metrics in cyber-physical production systems. Scientific awards: None listed in available documentation. No information provided regarding student advising, research grants, laboratory affiliations, or collaborative teams. Office hours are conducted by appointment at Campus Furtwangen, Room C 2.08.