My teaching spans control theory, robotics, dynamics, optimization, and aerospace systems. Across these courses, I aim to connect rigorous mathematical foundations with practical engineering insight, numerical methods, and applications that motivate students from different disciplines.
At Virginia Tech, my courses emphasize control theory, robotics, and automation, while bringing together students from industrial and systems engineering, mechanical engineering, aerospace engineering, and electrical engineering.
ISE/ME 6574, AOE/ECE 6774
This course presents major variations of adaptive control, including model reference adaptive control, indirect adaptive control, L1 adaptive control, prescribed-performance methods, and related architectures. Special emphasis is given to analysis, implementation, and numerical studies of adaptive controllers for uncertain dynamical systems.
ISE/AOE/ECE 5744, ME 5544
This course develops the mathematical foundations of linear dynamical systems through state-space models, stability, controllability, observability, realizations, and feedback design. Students study both the theoretical structure of linear systems and their use in analysis and control of engineering systems.
ISE 4264
This course introduces senior-year undergraduate students to the fundamentals of automation and robotics for classical and modern industrial systems. The class combines theoretical foundations with hands-on exposure to sensing, control, programming, and the operation of robotic platforms in automated environments.
ISE 5314
This graduate course introduces the dynamics, path planning, trajectory planning, and control of robotic manipulators, with selected elements of computer vision and perception. Special emphasis is given to robotic systems that operate in complex industrial environments where precision, repeatability, flexibility, and safety are essential.
At the University of Oklahoma, I taught advanced undergraduate and graduate courses in nonlinear systems, robust control, optimization, mechanical systems, and flight dynamics.
AME 5790/4970
The goal of this course is to analyze dynamical systems whose behavior is governed by nonlinear ordinary differential equations. Topics include existence of solutions, Lyapunov stability theory, partial-state stability, and control techniques such as backstepping, sliding mode control, model reference adaptive control, and feedback linearization.
AME 5790/4970
This course presents control design techniques for linear and nonlinear dynamical systems under uncertainty. Topics include H2, H∞, and mixed H2/H∞ methods, together with sliding mode control, robust adaptive control, and adaptive sliding mode control, all motivated by engineering applications.
AME 5790/4970
In the first part of this course, students are introduced to convex optimization problems such as linear, quadratic, and geometric programming, with emphasis on duality and the KKT conditions. The second part focuses on necessary and sufficient conditions for optimal control of dynamical systems, supported by analytical and numerical examples inspired by practical engineering problems.
AME 5790/4970
This course introduces advanced techniques to model and control multibody mechanical systems such as robotic manipulators and bio-inspired mechanical systems. Students learn how to analyze dynamics, derive models, and design controllers that can be applied to autonomous mechanical systems in realistic engineering scenarios.
AME 5513/4513
This course provides an introduction to flight dynamics and control for aerospace engineering applications. Students study the modeling of aircraft motion, stability, control, and feedback design, while developing the tools needed to analyze and solve practical problems in flight control systems.