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Krzysztof OlińskiView profile

Assistant Professor

• Discrete optimization
• Control optimization
• Optimal control
• +6 more

Krzysztof Oliński serves as an Assistant Professor at the Department of Decision Systems and Robotics within the Faculty of Electronics Telecommunications and Informatics at Gdańsk University of Technology. His academic profile demonstrates a strong focus on control engineering with particular expertise in optimization methodologies for complex dynamic systems. Dr. Oliński's research centers on discrete optimization techniques applied to control theory, with significant contributions to optimal control strategies for nonlinear dynamic processes. His work bridges theoretical foundations with practical industrial applications, particularly in manufacturing and pipeline systems. He has developed innovative approaches including graph-based representations of state-space dynamics and agent-based optimization methods. His keyword profile reveals expertise in computational intelligence, swarm algorithms, and intelligent manufacturing systems, reflecting his interdisciplinary approach to solving complex control problems. An analysis of his publication history from 2007-2012 shows a clear research trajectory evolving from foundational work on fault-tolerant control systems to more sophisticated methodologies like the 'toolgraph' approach. His early publications focused on discrete optimization techniques for control planning, while his later work expanded to include agent-based strategies and integration of natural and artificial intelligence in production systems. His most impactful contributions involve novel representations of state-space dynamics through flow graph structures that enable more effective control strategy design. Dr. Oliński maintains an active research presence with publications in both Polish and international journals including Mathematical Problems in Engineering and the International Journal of Applied Mathematics and Computer Science. His work demonstrates consistent theoretical rigor combined with practical relevance to industrial applications, particularly in intelligent manufacturing systems and pipeline dynamics modeling.

• Software Engineering
• Cloud Computing
• Self-Adaptive Systems
• +7 more

Elisabetta Di Nitto serves as Full Professor at Politecnico di Milano within the Department of Electronics, Information and Bioengineering, teaching Software Engineering 2 and Informatica B (in Italian). Her academic leadership extends to editorial and conference organization roles across premier software engineering venues. Her research program centers on evolving software systems through: Cloud-native application engineering and elasticity management Self-adaptive architectures for dynamic environments Service-centric and autonomic computing paradigms NoSQL database integration and scalability challenges Global/open source development methodologies Dr. Di Nitto has significantly shaped the field through editorial stewardship of ACM Transactions on Software Engineering and Methodology, IEEE Transactions on Software Engineering, SOCA Journal, and Journal of Software: Evolution and Process. She chaired pivotal conferences including ESEC/FSE 2015 (General Chair), SEAMS 2020, ASE 2010, and ServiceWave 2010 (Program Co-Chairs). No scientific awards were documented in the provided materials. Her mentorship encompasses numerous Master's students whose theses address cloud migration frameworks, software forge awareness, QoS optimization in decentralized clouds, and scalable NoSQL relation handling.

Thomas KopinskiView profile

Professor

• Machine Learning
• Deep Learning
• AI Safety
• +6 more

Prof. Dr. Thomas Kopinski is a Professor at the Faculty of Engineering and Economics, South Westphalia University of Applied Sciences in Meschede, Germany. He leads the AI Safety and Collective Intelligence Lab, focusing on cutting-edge research in machine learning applications for industrial and automotive systems. His work bridges academic research and industry collaborations, notably with BMW AG. Research Focus: His team explores: Deep learning architectures for real-time gesture recognition and automotive HMI AI safety protocols and collective intelligence frameworks Industrial applications including predictive maintenance and anomaly detection 3D programming and sensor fusion techniques Team & Students: Current advisees include PhD candidates working on: Bayesian deep learning for predictive maintenance (Felix Neubürger) Generative models for image synthesis (Yasser Saeid) Object recognition in crash test videos (Daniel Gierse) Key Projects: Actively directs WiTraPres and Core Transformer initiatives, with upcoming R&D in AI Safety launching in 2025. Industrial collaborations focus on automotive safety systems and manufacturing optimization.

Yassine OuhammouView profile

Associate Professor

• Real-Time Systems
• Embedded Systems
• Model-Based Design
• +6 more

Yassine Ouhammou is an Associate Professor in computer science at École Nationale Supérieure de Mécanique et d'Aérotechnique (ENSMA), where he is a member of the "Real-Time and Embedded Systems" research team at LIAS laboratory. His work focuses on critical real-time embedded systems with applications in avionics, drones, and control command systems. His research interests include: Software architectures for critical real-time embedded systems Design and analysis of critical real-time systems regarding their temporal performances Model-based design using domain specific languages (MoSaRT, AADL, Capella, Time4Sys) Real-time scheduling and dimensioning Knowledge repositories for expertise capitalization, reuse and reproducibility Collaborative engineering for complex systems design Model-driven engineering and formal methods Dr. Ouhammou's publication record shows consistent contributions to real-time systems, embedded architectures, and model-based approaches. His recent work demonstrates increasing emphasis on drone technology and avionic applications, with numerous collaborations on autopilot design, scheduling optimization, and verification methodologies. His research bridges theoretical computer science with practical aerospace engineering challenges, addressing safety-critical aspects of embedded systems. Professional service includes: PC Member of MEDES 2020, INISTA 2020, WIMS, SADASC 2020 PC Chair of DETECT 2019 General Co-Chair of RTNS 2018 PC Member of multiple international conferences since 2017 Dr. Ouhammou collaborates extensively with researchers in the field of real-time systems, particularly with Emmanuel Grolleau and other members of the LIAS laboratory. His work often involves interdisciplinary teams addressing complex challenges in aerospace and embedded systems engineering, with practical applications in drone technology and avionic systems.