Boris Benedikter, Ph.D. Postdoc in Optimal Control & AI for Aerospace Autonomy

Teaching & Mentoring

"Learning is active and adaptive: students build understanding through doing, and I refine teaching through feedback and reflection."

Besides my research activities, I am deeply committed to teaching and mentoring the next generation of engineers and scientists. My approach is grounded in formal pedagogical training I received through the year-long CIRTL Postdoc Pathways Program at University of Arizona, where I developed a reflective, evidence-based teaching practice. I strive to create inclusive and engaging learning environments by connecting complex topics to real-world applications. This philosophy has guided my experience co-teaching a graduate-level course in robotic systems and my ongoing mentorship of undergraduate and doctoral students.

Teaching Philosophy

My teaching philosophy is built on a commitment to creating an inclusive and effective learning environment. It is guided by the following core principles:

Reflective teaching

Reflective & Iterative Practice

I approach teaching as I do research: as an iterative process of setting goals, testing ideas, and using feedback to improve. This reflective practice, informed by the "teaching-as-research" model, allows me to continually refine my methods.

Inclusive classroom

Inclusive & Adaptive Teaching

Recognizing that students learn in diverse ways, I adapt my strategies to create an inclusive environment where every student feels valued. I view student diversity as a resource that enriches the classroom, a principle shaped by my training in evidence-based and inclusive pedagogy.

Motivating students

Motivating Through Real-World Connections

Motivation is key to deep learning. I strive to spark curiosity by connecting course material to meaningful, real-world applications, from NASA's Mars rovers to everyday robotics, to show students the relevance and impact of their work.

Active learning

Active & Hands-On Learning

True understanding comes from doing. I design courses with a strong emphasis on active learning, using hands-on exercises, assignments with opportunities for revision, and open-ended projects that support students to apply their knowledge, problem-solve, and take ownership of their learning.

Evidence of Teaching in Practice

Below are examples of materials I developed for the “Robotic Systems” course, each designed to address a specific learning goal.

Introductory slide for ROS lecture

Sparking Curiosity from Day One

Rather than starting with technical details, my first lecture began with the story of ROS's development, connecting it to real-world applications from NASA's Mars rovers to household robots. This narrative approach was designed to motivate students and help them see themselves as creators of impactful technology.

Slide showing a hands-on exercise

Hands-On Practice

To balance theory with application, I designed hands-on exercises at the end of each lecture. These tasks encouraged students to experiment with concepts on their own time, reinforcing core ideas through active "learning by doing" rather than passive reception of information.

Project-Based Learning

The final project challenged students to apply concepts from across the course in a complex, open-ended scenario: simulating a Mars rover. This approach mirrors real-world engineering practice and assesses students' ability to reason through design decisions and problem-solve independently.

Teaching Mentor Voice

The main instructor of the “Robotic Systems” course, Prof. Fabio Curti, observed my teaching and wrote a letter summarizing his observations.

The letter highlights that we met regularly before and after each lecture to discuss the course content, the students’ progress, and any challenges we encountered. It also emphasizes that I was able to adapt my teaching style to the needs of the students and that I provided clear explanations, comprehensive materials, and fine-tuned exercises and assignments to help students learn effectively.

A screenshot of the observation letter from teaching mentor Prof. Fabio Curti View Mentor Observation Letter (PDF)

Student Voices

To evaluate the impact of my teaching, I collected anonymous student feedback after the ROS module. Their responses highlighted the value of clear explanations and hands-on learning, and provided constructive ideas for future iterations.

“Very good explanation of ROS from the very basic presentations, into more detailed examples. I enjoyed the small mini project Turtlesim as a basic project to learn hands on.” — Graduate Student

“It would be cool if we started doing ROS projects earlier… For example, you could give an sdf file of the world, and have the student write code for the simulation to navigate the course as a step before implementing any reinforced learning.” — Graduate Student

This feedback reinforces my goal of increasing student engagement and providing structured opportunities for experimentation, which I will incorporate in future versions of the course.

Instructional Experience

Pedagogical Training

Mentoring

Mentoring is not just a responsibility alongside research; it is a commitment to a student’s learning, growth, and future. My goal is to foster a collaborative environment where students can develop into independent and impactful researchers.

My approach to mentoring mirrors my teaching philosophy: I see it as a shift from delivering content to guiding and supporting. I aim to create a space where students feel empowered to tackle open-ended challenges, reason through design decisions, and learn through an iterative process of inquiry and reflection. By providing consistent feedback and asking probing questions, I help students build not only their technical skills but also their confidence and creativity.

Doctoral Students

Undergraduate & M.Sc. Theses Co-Advised