جست‌وجوی استاد و پژوهشگر

• Human-Machine Interaction
• Intelligent Production Systems
• Data-Driven Process Optimization
• +۱۲ مورد دیگر

Marius Krüger is a researcher at the Chair of Automation and Information Systems at the Technical University of Munich . His work focuses on human-machine interaction, data-driven process optimization, and AI integration in industrial contexts. Specializes in cyber-physical production systems and digital twin technologies Contributes to embedded systems performance analysis and low-code programming assistance Active in construction machinery data transmission and forming process monitoring His publications highlight expertise in: Execution time optimization for adaptive controllers Synthetic data generation for civil engineering machines Regularization techniques in linear regression for quality prediction OPC UA integration for construction machine communication He collaborates on projects like KI.Fabrik , MiProcess2Twin , and CausAIITI , with recent work addressing Industry 4.0 and 5.0 challenges.

• Machine Learning
• Cloud Computing
• Fault Diagnosis
• +۳ مورد دیگر

Chao Yin is a researcher at Shanghai University , Department of Computer Engineering and Science. His work spans multiple domains including Machine Learning, Cloud Computing, Fault Diagnosis, and Supply Chain Optimization. Key research areas: Machine Learning , Cloud Computing , Quantum Computing , Supply Chain Systems , Network Security Scientific Contributions (2024-2025): Developed heterogeneous graph neural networks for automotive supply chain analysis Created MSDF-VAE cloud-edge fault diagnosis framework using transfer learning Proposed quantum metrology methods with Heisenberg-limited precision Designed LARP pseudonym protocol for V2X communication Optimized fog computing resource scheduling with hybrid metaheuristics Prior Work (2012-2023): Contributed to fluid animation feature preservation from single images Developed label distribution learning for facial age estimation Designed erasure coding storage systems for big data Created multi-agent manufacturing networks in cloud environments

Daniel Dollingerمشاهده پروفایل

پژوهشگر

• Embedded Systems
• Safety Critical Avionics Development
• Human-Machine Interface for UAS
• +۱۱ مورد دیگر

Daniel Dollinger is a researcher at the Institute of Flight System Dynamics at the Technische Universität München (Technical University of Munich). His work focuses on embedded systems and safety critical avionics development , with a particular emphasis on human-machine interface design for unmanned aircraft systems (UAS) and future air mobility solutions . He contributes to research in nonlinear and adaptive flight control , flight safety protocols , and trajectory optimization for advanced aerial vehicles. Embedded Systems & Safety Critical Avionics Human-Machine Interface for UAS Flight Control Systems Nonlinear and Adaptive Flight Control Simulation and Flight Safety Sensors and Data Fusion Daniel Dollinger has authored or co-authored multiple publications in prestigious conferences like AIAA AVIATION FORUM, AIAA SciTech, and IEEE/DASC. His research spans topics from control inceptor design for transition VTOL aircraft to model-based systems engineering integration into agile environments. He actively supervises student theses on subjects like hybrid fly-by-wire systems, UAV control protocols, and flight simulation toolchains. His recent work explores urban air mobility and eVTOL aircraft handling qualities , with a focus on simulator-based testing and operator situational awareness . He also investigates digital twin approaches for airborne software certification and lean development methodologies in avionics systems.