Alexandru Buburuzan

Alexandru Buburuzan

Research Scientist Intern

FiveAI

Bio

👋 I am Alex, a Research Scientist Intern at FiveAI, an autonomous driving company now part of Bosch, where I’m advised by Dr. Puneet Dokania.

I recently graduated with a BSc in AI from The University of Manchester. I completed my dissertation, supervised by Prof. Tim Cootes, on counterfactual generation using diffusion inpainting models for diverse perceptual modalities (see MObI and AnydoorMed).

My journey in computer vision began at 16 when I joined Rayscape, a medical imaging startup. I later continued there for two years as a Research Engineer, with a focus on domain generalisation, before moving to FiveAI, in Cambridge. As a year-long Research Engineer Intern, I published work on multimodal sensor fusion and synthetic data generation for autonomous driving, advised by Dr. Romain Mueller.

Interests
  • Computer Vision
  • Multimodal Perception
  • Autonomous Driving
Education
  • BSc (Hons) Artificial Intelligence with Industrial Experience, 2021 - 2025

    The University of Manchester

Publications

Evidence of a cognitive bias in the quantification of COVID-19 with CT: an artificial intelligence randomised clinical trial

Nature Scientific Reports | Radiologists overestimate COVID-19 lung involvement on CT due to a psychophysical bias, yet AI support …

Evidence of a cognitive bias in the quantification of COVID-19 with CT: an artificial intelligence randomised clinical trial

Experience

 
 
 
 
 
Five AI
Research Scientist Intern
May 2025 – Present Cambridge, UK
 
 
 
 
 
Five AI
Research Engineer Intern
Jun 2023 – Jun 2024 Cambridge, UK
Diffusion models for scene editing and multimodal sensor fusion for 3D object detection.
 
 
 
 
 
Rayscape
Research Engineer
Jul 2021 – Jun 2023 Remote
Developed a CE-marked algorithm for lung nodule segmentation, deployed in over 100 hospitals.
 
 
 
 
 
Rayscape
Machine Learning Intern
Mar 2020 – Sep 2020 Timisoara, Romania
Build a time-efficient AI model for the detection of intracranial haemorrhages meant for speeding up the triaging process.