Euan Goodbrand

I am a PhD student at the Visual Geometry Group at the University of Oxford.

Previously, I worked as a Machine Learning Engineer at Mercedes-AMG PETRONAS Formula One Team, where I developed ML systems for aerodynamic simulation and race strategy. I received my MSc in Computing (AI & Machine Learning) from Imperial College London in 2024.

My research interests include computer vision, 3D reconstruction, neural rendering, and physics-informed machine learning.

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Research

I'm interested in computer vision, machine learning, and their applications to real-world problems. Some papers are highlighted.

SLB
Malware
Detection
Deep Learning from Imperfectly Labeled Malware Data
Fahad Alotaibi, Euan Goodbrand, Sergio Maffeis
ACM CCS, 2025
paper / code

SLB is a framework designed to robustly train deep learning–based malware systems while simultaneously refining dataset labels, achieving significant improvements on noisy malware datasets.

Education

2026 — Present PhD in Computer Vision
University of Oxford, Visual Geometry Group
2024 MSc Computing (AI & Machine Learning) — Distinction
Imperial College London

Design based on Jon Barron's website.

Euan Goodbrand

ML Engineer — Mercedes F1/Spatial & Physical AI

Euan Goodbrand

Machine learning at the limit

I am a Machine Learning Engineer at the Mercedes-AMG PETRONAS Formula One Team, with a passion for simulations, graphics, and visual effects. The scene behind this text is a live, decorative field — the same blend of motion, data, and engineering intuition that shows up in my work on and off the track.

Machine Learning Engineer at Mercedes-AMG PETRONAS Formula One Team, focused on high-performance ML, simulation, and visual systems.

Day to day I turn telemetry, simulations, and engineering data into systems that support decisions at trackside and in the factory — where lap-time margins are milliseconds and models have to be as disciplined as the car. That same appetite for rigorous ML, performance, and physics feeds how I think about graphics pipelines, procedural worlds, and numerical simulation outside F1.

I build ML tools that turn race and simulation data into fast, reliable decisions on and off track.

Recent Updates

Catch up with my latest adventures and career milestones.

Portfolio

Projects shown as a graph — nodes that share a discipline are connected. Hover for details, click to open. Use the filters to highlight a cluster.

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