Teaching
I teach undergraduate courses on signals, robotics, optimal control and machine learning at the Department of Electrical & Computer Engineering, University of Patras. Each course page has the syllabus and the week-by-week slides, notes, exercises and code.
Estimation and filtering from noisy data: least squares, multidimensional signals, maximum-likelihood and Bayesian estimation, nonlinear least squares, Wiener and Kalman filtering.
Syllabus & materials →Rigid-body motion, screw theory, forward and inverse kinematics, Jacobians, trajectory generation, rigid-body and open-chain dynamics, and velocity/force control of manipulators.
Syllabus & materials →Numerical optimization, LQR, dynamic programming, MPC, trajectory optimization, DDP/iLQR and optimal control on manifolds — implemented from scratch and deployed on real robots.
Syllabus & materials →Continuous- and discrete-time signals, LTI systems, Fourier analysis, sampling, the DFT/FFT and digital filter design — taught hands-on, with every concept implemented and tested in code.
Syllabus & materials →Mobile robots and motion planning, Lie groups for poses and trajectories, Bayesian filtering and SLAM, optimization-based and whole-body control, and legged locomotion.
Syllabus & materials →Machine learning and neural networks, optimization for training, deep models for vision, uncertainty and Gaussian processes, latent-variable and generative models, and zero-order optimization.
Syllabus & materials →