Learning outcomes
This is a laboratory course in which the students perform numerical computations during each session and complete problem sets as homework. Students bring their laptop computers to class, and an institutional license allows for MATLAB to be installed on each student's computer. Although the focus of this course is on computational methodologies, the students receive training in the identification of the types of experimental data, the appropriate computational approach for the data set, and the types of questions that can be addressed with a particular data set and computational strategy.
Brief description of content
The course is divided into three parts
I - Systems biology: Teach contemporary methods used in systems biology for dynamic modeling. Teach methods for mathematical analysis of biological systems and simulation outputs. Demonstrate how dynamical mathematical models can provide insight that cannot be gained from experiments only.
II - Robotics and computer vision: This part presents an overview of methods for mathematical analysis of robotics in practice and research with topics including vision, motion planning, mobile mechanisms, kinematics, inverse kinematics, and sensors.
III - Integrative approach. Finding and understanding common features in biological and physical engineered dynamic systems.