Hello, I am Ben!

Student and aspiring robotics engineer passionate about innovation, coding, and exploring new challenges.

Learn more about me
  • Name: Benjamin Dupont
  • School: ETH Zürich
  • Age: 23 Years
  • Hometown: Annecy, France

I am a master's student in Mechanical Engineering at ETH Zurich, but it's not just about machines for me. I'm all into robots, making things smart with machine learning, and figuring out how to get robots to do cool stuff on their own. I've had some awesome times putting this into action with the AMZ Racing team and picking up real skills through university projects and internships. Coding's my thing, especially when it's about making robots smarter or more autonomous!

Off the clock, you'll find me being active or chilling out in my own ways. I've been into sports for ages, like badminton, mountain biking and hiking, and I keep fit with regular gym sessions. I'm also kinda hooked on cooking up healthy meals. But there's more - I love things that fly! From drones to gliders it's amazing up there. F1 races? Huge fan. They're all about pushing limits and tech, which is super cool to me. Plus, I get to mix this love for speed and tech with my studies.

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My Education

  • ETH Zurich (Eidgenössische Technische Hochschule Zurich)

    Master of Science (MSc) in Mechanical Engineering | 2022 - Present
    • Specializing in robotics, machine learning, and autonomous systems. Coursework includes robotics (planning, controls, state estimation and computer vision), machine learning and AI, but also a few minor courses on aerodynamics and fluid mechanics.
    • During my semester project I worked on developing a dynamic obstacle detection algorithm for collision avoidance for autonomous racing GoKarts
    • My master thesis topic was on UWB (Ultra-Wideband) anchor initialization for drone localisation using a robust and general approach for optimising the estimated position and generating optimal drone trajectories to refine the estimate
    • Achieved an outstanding academic performance with an average of 5.45/6 in my Master's degree program.

  • EPFL (École Polytechnique Fédérale de Lausanne)

    Bachelor of Science (BSc) in Mechanical Engineering | 2019 - 2022
    • Graduated with a top tier average of 5/6. Served as a teaching assistant for Physics 1 and Calculus 2, providing academic support and guidance to undergraduate students.

  • NTNU (Norwegian University of Science and Technology)

    Exchange Student | 2021 - 2022
    • Completed a full-year exchange at NTNU, focusing on advanced engineering coursework, which broadened my perspective and strengthened my cross-cultural adaptability.

My Experience

  • Computer Vision Research Intern - On-board Perception for Future Mars Rotorcraft

    NASA Jet Propulsion Laboratory | Pasadena, California (USA) | January 2025 - July 2025

    • Developed and tested structure-from-motion-based 3D mapping algorithms to identify landing hazards on complex terrains.
    • Designed and implemented visual-inertial state estimation algorithms for navigation in GPS-denied and low-texture environments.
    • Integrated image-based localization systems for map alignment using orbital data to enhance autonomous operations.
    • Deployed and validated perception algorithms on embedded hardware aboard a UAV Mars rotorcraft surrogate.
    • Utilized coding expertise in C++, Linux, and ROS for embedded systems development and real-time algorithm implementation.

  • Teaching Assistant at ETH

    Institute for Dynamic Systems and Control | Zurich, Switzerland | April 2024 - December 2024

    • Teaching assistant for the robotics class “Duckietown” at ETH.
    • Hardware preparation and maintenance, base software stack development and adaptation using ROS and docker, creation of programming exercises, student support and project grading.

  • Student Formula 1 operation room support

    Kick Sauber Formula 1 Team | Hinwil, Switzerland | Feb 2024 - July 2024

    • Supported operations during Formula 1 Grand Prix weekends, analyzing tire and brake data to prepare detailed performance reports.
    • Developed and maintained automated data analysis scripts using MATLAB and Python to streamline workflows.
    • Conducted competitive analysis on tire management strategies for data-driven insights.

  • AMZ Racing

    Head of Controls | Zurich, Switzerland | Aug 2023 - Feb 2024

    • Recruitment of the new team, including interviewing, process, and selection
    • Management and guidance of the controls group, including team and module strategy overview
    • Code reviewing in C++ and Python, and concept suggestions and validation

  • AMZ Racing

    Controls Engineer | Zurich, Switzerland | Sept 2023 - Aug 2023

    • Led the design and enhancement of high-level Model Predictive Control (MPC) using C++ and ROS, enabling our custom-built Formula Student race car to navigate cone-delimited tracks autonomously at optimal speeds.
    • Tuning of the controller for speed and reliability using knowledge of race car vehicle dynamics as well as post-test data analysis on logs for debugging and to strive for optimal performance.
    • Competition against other Formula Student teams during summer around Europe.

  • ALR Aerospace

    Aircraft Performance Engineer | Zurich, Switzerland | Feb 2023 - June 2023

    • Aircraft aerodynamic and performance data analysis using Python.
    • Processing aircraft trajectory data extracted from flight simulation
    • Applying flight mechanics knowledge to post-process the data
    • Development of numerical methods for data reduction and filtering

  • Teaching Assistant at EPFL

    Mechanical Engineering Department | Lausanne, Switzerland | Sept 2020 - July 2021

    • Assisted in exercise sessions for Physics 1 and Calculus 2, supervising and supporting student learning

Projects

Click on any project to learn more

Semester Project: Obstacle Detection for Racing Go-karts

Developed a dynamic occupancy grid using a Particle Filter for obstacle detection in autonomous racing go-karts as part of a semester project at ETH Zurich's IDSC group. Leveraged LIDAR point cloud processing and clustering, outlier rejection and an EKF for motion compensation.

Master thesis: Online UWB Anchor Initialization for Autonomous Drone Localisation

Explored online initialization of Ultra-Wideband (UWB) anchors to enable precise navigation for autonomous drones during my Master thesis at AAU's CNS group (University of Klagenfurt, Austria). Direct supervision from Prof. Stephan Weiss. Tested the implementation on real hardware in the Dronehall to confirm the great results from the simulation setups.


Neural Network from Scratch

Small project to practice my understanding of a simple Neural Network architecture by coding the forward and backward propagation myself without using Tensorflow (only Numpy)

Toy Car Simulator

Created a toy car simulator featuring a 4-wheel vehicle model with a Pacejka tire model to simulate the dynamics and navigate Formula Student-like tracks using PID and pure pursuit controllers. Ongoing work involves transitioning to reinforcement learning-based control.

Various Machine Learning Projects

Completed four comprehensive projects from ETH Zurich's Introduction to Machine Learning course, covering topics such as regression, classification, clustering, and neural networks. Achieved full points in all four exercises


Differential Drive Robot Intersection Navigation In Duckietown

As part of the Duckietown lecture at ETH Zurich, developed and implemented a computer vision-based algorithm for autonomous navigation on multiple "Duckiebots." The system enabled the robots to use computer vision to recognize different types of intersections, stop accurately at stop lines, make navigation decisions, and interact with other Duckiebots by interpreting indicators and yielding the right of way. The Duckiebots successfully identified the correct exit, navigated intersections, and followed road lanes to their next destination, demonstrating the power of computer vision in decision-making and path-following tasks.

Full Monocular Visual Odometry Pipeline

Implemented a visual odometry pipeline to estimate camera trajectories and reconstruct 3D landmarks. Utilized two-view geometry for initialization, KLT tracking with forward-backward verification, P3P RANSAC for robust pose estimation, and continuous landmark triangulation. Enhanced the system with local bundle adjustment to combat scale drift and a keyframe-based approach for improved robustness. Evaluated the pipeline on Parking, KITTI, and Malaga datasets with 85-95% tracking success rate, achieved high local trajectory consistency even during complex camera motions.


State Estimation Filters

Developed an extended Kalman filter and a particle filter to estimate a car's state using data from intermittent sensors, as part of an exercise in the Recursive Estimation course at ETH Zurich.

Reinforcement Learning for Controlling a Formula Student racecar (Ongoing)

Integrated the vehicle dynamics model from the AMZ Racing team's simulator into the Toy Car Simulator. Trained a Proximal Policy Optimization (PPO) MLP model to control the car and navigate through tracks, as part of ongoing work to enhance control systems using reinforcement learning techniques.

My Extracurriculars



AMZ Racing

Core Team Member at AMZ Racing


AMZ Racing is a passionate team of engineering students dedicated to designing, building, and racing single-seat cars in the Formula Student competition. With a focus on pushing the limits of innovation, the team strives for victory in a high-stakes environment.

I joined AMZ Racing initially as a Controls Engineer, where I was responsible for developing the high-level autonomous control algorithm that allowed our race car to drive without a driver. This involved developing a model predictive controller and integrating it with various systems such as traction control, whilst tuning and testing the controller to contribute to the car's overall performance.

In my second year, I transitioned to the role of Controls Team Lead, guiding the team through a particularly successful season — one of the most successful in the association's 15-year history. Under my leadership, we achieved significant technical milestones thanks to a robust pipeline, and our team's collaboration and innovation were key to our success.

Throughout my time at AMZ Racing, I had the privilege of working alongside highly motivated, like-minded, and incredibly bright fellow students. This experience not only enriched my technical knowledge but also deeply influenced my career path. The challenges, teamwork, and problem-solving involved in Formula Student helped me refine my interests in robotics, an area I am now passionate about pursuing in my professional career.




FPV Drone Pilot & Builder


As an FPV drone pilot and builder, I design and assemble high-performance drones. My work includes soldering, wiring, and configuring flight controllers to ensure optimal drone performance. I also enjoy flying drones in my spare time, which has helped me develop hands-on skills in electronics, aerodynamics, and troubleshooting in general.

FPV Drone




Glider Flying

Glider Enthusiast and Pilot


During the summer months when my schedule permits, I pursue a small hobby: glider flying. With over 20 flight hours accumulated so far, I've developed a deep appreciation for the unique challenges and joys of engineless flight. Soaring through thermal currents and ridge lifts has given me practical insights into aerodynamics that complement my theoretical knowledge.

Glider flying serves as both a recreational escape and an opportunity to experience the principles of flight mechanics firsthand. The precision required in reading weather conditions, managing energy, and executing landings has challenged my situational awareness and decision-making skills—qualities that transfer well to my engineering work.





Travel & Photography


My passion for exploration extends beyond engineering into travel and photography. Using my Sony camera, I enjoy capturing landscapes and cultural moments while shooting in manual mode to have complete creative control over my images. My travels have taken me across diverse landscapes and cultures—from hiking in the Swiss Alps during weekends to exploring the vast wilderness of US National Parks.

During my exchange in Norway, I seized the opportunity to experience the country's beautiful fjords and northern landscapes. I've also visited Egypt and discovered ancient architectural wonders and immersed myself in its rich historical context. These experiences not only broaden my perspective but also provide creative inspiration that influences my approach to engineering challenges.

Travel Photography