Webinar on Cybergenetic Systems: Mechanistic and Data-Driven Adaptive Control | Sci Machine Learning

This webinar explores the rapidly evolving field of cybergenetic systems, an interdisciplinary area that integrates biology, control engineering, computational science, and artificial intelligence to enable the intelligent monitoring, analysis, and regulation of living systems. The session provides a comprehensive introduction to how mechanistic models, data-driven adaptive control, controller design techniques, and Scientific Machine Learning (SciML) can be combined to understand, predict, and control complex biological processes. Participants will gain insights into the principles of system identification, feedback and adaptive control, hybrid modeling frameworks, and real-time biological regulation. The webinar also highlights the growing role of machine learning in enhancing model development, improving prediction accuracy, and enabling robust decision-making in biological systems. By integrating first-principles biological knowledge with modern data-driven approaches, cybergenetic systems offer new opportunities for advancing synthetic biology, biotechnology, and intelligent bioengineering applications. *Topics Covered:* • Cybergenetic Systems and Biological Control • Mechanistic Modeling of Biological Processes • Data-Driven Adaptive Control Strategies • Controller Design and dynamical systems (eg. System of ODEs) • Scientific Machine Learning (SciML) • System Identification and Real-Time Adaptation • Hybrid Modeling and Intelligent Decision-Making This session is ideal for researchers, students, and professionals interested in systems biology, synthetic biology, computational science, bioengineering, artificial intelligence, and control systems engineering. #CybergeneticSystems #Cybergenetics #ScientificMachineLearning #SciML #SystemsBiology #SyntheticBiology #AdaptiveControl #ControllerDesign #ComputationalScience #ControlSystems #MachineLearning #Bioengineering #ArtificialIntelligence #ResearchWebinar