Stathis Galanakis

Stathis Galanakis

PhD Student in Imperial College London

Imperial College London

Biography

I am excited to use my industry and academic experience to bring cutting edge Computer Vision research to life. My interests lie in the field of Computer Vision particularly in tackling intricate challenges related to human faces and bodies. These encompass areas such as 3D facial reconstruction from monocular images, facial avatar generation, as well as engaging in dataset creation efforts.

Interests
  • Artificial Intelligence
  • 3D Face Reconstruction
  • Computer Graphics
Education
  • PhD in Artificial Intelligence, 2021-2025

    Imperial College London

  • M.Eng. in Electrical & Computer Engineering, 2019

    National Technical University of Athens

Experience

 
 
 
 
 
Research Assistant in Computer Vision
Imperial College London
March 2025 – Present London
In my role as a research assistant, I investigate diffusion-based techniques, aimed at improving the tasks of skin lesion synthesis, classification, and segmentation.
 
 
 
 
 
Computer Vision Intership
Huawei UK
September 2024 – March 2025 London
I worked as a Computer Vision Intern in Huawei UK, where I focus on 3D facial reconstruction from monocular images using advanced 3D Gaussian Splatting techniques.
 
 
 
 
 
Computer Vision Intership
Huawei UK
January 2022 – January 2024 London
As a Computer Vision Engineer at Huawei UK, I specialized in 3D facial reconstruction from monocular images. In this role, I integrated cutting-edge techniques to advance the field, focusing on enhancing the accuracy and effectiveness of reconstruction methods. My work involved pushing the boundaries of state-of-the-art approaches, such as NeRF and diffusion-based techniques.
 
 
 
 
 
Research Assistant
Imperial College London
February 2021 – January 2022 London
I worked as a Research Assistan(RA) in the project ARISE held by Business School, Imperial College of London. ARISE was a European Union-funded initiative designed to forecast agricultural crop yields within a specific region during targeted time periods. My responsibilities encompassed the utilization of data derived from satellites and weather stations, employing state-of-the-art machine learning algorithms to extract meaningful insights. Additionally, I was tasked with generating synthetic data for regions with limited data availability, ensuring a comprehensive and robust approach to yield prediction.
 
 
 
 
 
Computer Vision Scientist
ArielAI
January 2020 – October 2020 London
My main responsibilities included the design and implementation of cutting-edge automated pipelines for collecting images across the web. These pipelines were instrumental in the creation of novel datasets that accurately represented real-world scenarios. In addition, I took charge of designing and coordinating human annotation tasks for the annotators at ArielAI while ensuring precise and consistent annotations..
 
 
 
 
 
R&D, ML Engineer
Pobuca Ltd
May 2018 – January 2019 Athens
In my capacity as the sole Machine Learning Engineer, I undertook the development of a robust network for automated product recognition within images captured from supermarket shelves. This required designing Computer Vision algorithms and tools for easy annotation and creating both training and detection procedures alongside with back-end support.