THE FIELD OF SIMULATION MACHINE-LEARNING AND OPTIMIZATION
Learn techniques of modeling and simulation, numerical methods, and their implementation on physical problems motivated by real-world phenomena that engineers and scientists are likely to encounter in their careers involving energy systems, materials engineering, structural analysis, dynamics, controls, etc.
- Master the concept of “optimal” and Classical Gradient-based Methods
- Master modern machine-learning, evolutionary computation and genetic algorithms
MODELING AND SIMULATION OF AUTONOMOUS SYSTEMS-SWARMS OF UAVS
Learn about the modeling of swarm “agents”, their dynamics and numerical methods to describe their motion. Learn how to train a swarm using machine-learning optimization.
- Master the methods needed to simulate dynamics of large-scale systems
- Master application of modern optimization methods
MODELING AND SIMULATION OF ADVANCED MANUFACTURING 3D ROBOTIC PRINTERS
Learn how to model and simulate more complex systems, such the dynamics of a 3D printing robot, along with multiphysical electrodynamic control and machine-learning for system training/optimization.
- Apply methods of heat-transfer and dynamics simultaneously
- Master kinematics of robots