Principal AI Engineer

Medtronic, Surgical Robotics

About me

Hey! My name is Felix and I am currently a Principal AI Scientist/Engineer within Surgical Robotics at Medtronic.

I am currently researching machine learning and computer vision methods for visual reasoning for surgical robotics. In particular; I focus on the development of novel transformer architectures for multi-task learning whilst I also investigate spatiotemporal models and the use of semi-supervision for training. I have also helped develop novel models to power real-time surgical video processing algorithms and have written production ready code for training, validating, deploying and exporting our models.

Previously, I was at Babylon Health where I was developing methods for learning patient representations from health records whilst also researching methods across modular and disentangled representation learning.

Before Babylon Health, I was a post-doc at UCL working with M. Jorge Cardoso where I developed fundamental methods in deep learning and multi-task learning. I developed multiple learning schemes for multi-task learning, with oral presentations at MICCAI 2018 and ICCV 2019.

I initially was a PhD student under the supervision of Prof. David Hawkes at CMIC UCL and Prof. John Hurst at the Royal Free Hospital. I developed numerous algorithms for the quantitative analysis of Chronic Obstructive Pulmonary Disease (COPD) from three-dimensional Computed Tomography scans using supervised and unsupervised learning methods.

  • Representation Learning
  • Multi-task Learning
  • Modular/Mixture of Expert Models
  • Sparse Neural Networks
  • PhD in Medical Computer Vision, 2017

    University College London

  • MSc in Biomedical Engineering, 2012

    University of Oxford

  • BEng in Mechanical Engineering, 2011

    University College London

Selected Publications

For a complete list, please visit my Google Scholar webpage


Principal AI Scientist/Engineer
Nov 2021 – Present

Developing machine learning models for processing surgical videos for AI-assisted surgery. Responsibilities include:

  • Researching and developing machine learning algorithms to process surgical videos
  • Contributing production-ready code for R&D and deployment of models for production
  • Responsible for supervision of junior team members and UCL Machine Learning MSc students
Senior Research Scientist
Jun 2019 – Nov 2021

Developing machine learning models to help build products for AI-driven health care. Responsibilities include:

  • Developing tools to learn patient representations from health data for dynamic risk stratification
  • Researching methods across fair representation learning, domain generalisation and modularity in neural networks
  • Contributing scientific insight towards long-term strategic product vision
Research Associate
Jun 2017 – Jun 2019

Deep learning and multi-task learning algorithms for computer vision and medical image computing.

  • Researched and developed fundamental methods for multi-task learning applied to computer vision and medical image computing
  • Applied algorithms to a range of applications such as MR to CT image synthesis and organ-at-risk segmentation in MR-only radiotherapy planning
  • Work published as orals at MICCAI 2018 and ICCV 2019
  • Contributed to NiftyNet: an open-source Tensorflow library for deep learning in medical image analysis