Teaching and Supervision

I have taught and supervised students at ETH Zurich and DTU in control, automation, modeling, and experimental methods. My teaching approach combines rigorous mathematical foundations with hands-on laboratory and project work.

ETH Zurich

Quad-Rotors and Control Experiments Lab (2023–2024)

Role: Lecturer and laboratory lead Audience: ~120 undergraduate students per year Subjects: Quad-rotor dynamics, state estimation, control design, sensor integration, experimental validation

I was the principal teacher and lab manager for this undergraduate course, which combines control theory lectures with hands-on quad-rotor laboratory experiments. Students implement state estimation and control algorithms on physical quad-rotor platforms, bridging the gap between theoretical control design and real-world experimental validation.

Control Experiments Lab — IfA/PSL (2023–2024)

Role: Lab manager and lecturer Audience: ~200 students across IfA/PSL laboratory courses Subjects: Control system design, system identification, real-time implementation, experimental methodology

I coordinated and taught the IfA/PSL control experiments laboratory, managing experimental setups, supervising student groups, and ensuring safe and effective laboratory operations across multiple course sections.

CAS ETH in Applied Technology in Energy (2021)

Role: Teaching assistant Audience: Continuing education professionals Subjects: Energy technology, applied control, system integration

I supported this continuing education course for industry professionals, contributing to lectures, exercises, and project supervision.

DTU Compute

Special Course: Microgrid Optimization (2019)

Role: Lecturer Audience: Single-student special course (graduate level) Subjects: Microgrid modeling, optimization, model predictive control

I designed and delivered a special course on microgrid optimization, guiding a graduate student through advanced topics in optimal control and energy system modeling.

Dynamic Programming (2018)

Role: Teaching assistant Audience: Primarily graduate students Subjects: Dynamic programming, optimal control, reinforcement learning foundations

I assisted with lectures, exercises, and exam preparation for this graduate-level course on dynamic programming and optimal control methods.

Stochastic Adaptive Control (2018)

Role: Teaching assistant Audience: Primarily graduate students Subjects: Stochastic systems, adaptive control, system identification

I supported this graduate course through exercise sessions, project guidance, and examination assistance.

Supervision

Student supervision (thesis projects, research internships, and co-supervision) is not yet documented in the available evidence. This section will be updated when supervision records are confirmed by the owner.

Teaching Philosophy

My teaching is grounded in the principle that control, automation, and modeling are best learned through the integration of theory, computation, and physical experimentation. I design learning experiences where students move from mathematical foundations through simulation to real hardware, developing both analytical rigor and practical engineering judgment.

Public Course Artifacts

Links to public course materials, syllabi, and project repositories are not yet available. This section will be updated as materials are published or linked.