Biography
Hi! I am currently a Scientist at Amazon Research, working on generative modelling and speech disentanglement of text-to-speech systems on Alexa.
Previously I was a DPhil (PhD) student with Dr. Maurice Fallon at the University of Oxford as part of the Dynamics Robotics Group at the Oxford Robotics Institute. My research interests include SLAM, place recognition, keypoint detection and correspondence estimation, and generative deep learning, specifically diffusion models and transformers. I also interned as computer vision scientist at XYZ Reality working on correspondence estimation algorithms. Prior to that I interned as an applied scientist at Amazon Research working on speech synthesis for Alexa. I completed a MSc Artificial Intelligence degree at the University of Edinburgh and I hold a first class honours degree in computing science from the University of Aberdeen. My free time I spend playing volleyball, travelling and skiing.
Download my resumé.
Interests
- SLAM/SfM
- Keypoint detection in 2D/3D
- Generative learning
- Representation learning
- Geometry
Education
PhD in Robotics and Computer Vision, 2021
University of Oxford
MSc in Artificial Intelligence, 2016
University of Edinburgh
BSc in Computer Science, 2015
University of Aberdeen
Skills
Computer Vision
85%
Machine Learning
85%
Robotics
100%
Deep Learning
92%
Python
95%
Volleyball
84%
Experience
Applied Scientist II
Amazon
Responsibilities include:
- Tech lead of a team on disentanglement technology for Alexa
- Delivered machine learning models at scale to production
- Reserach on state-of-the-art generative models
PhD/DPhil student
University of Oxford
Responsibilities include:
- Developed SOTA algorithms for place recognition, odometry, navigation
- Deployed a LIDAR loop closure detecting system
- Supervised MSc students on 3D deep learning
Computer Vision Scientist
XYZ Reality
Responsibilities include:
- Inventing and evaluating correspondence networks
- Protyping proof-of-concept NeRF
- Patenting SLAM technology
Applied Scientist
Amazon
Responsibilities include:
- Compared efficient generative models
- Worked in a team to create a single universal vocoding model replacing 43 other models
- Researched features for latent representaton of speech signals
Software Developer
Ikiji Ltd
Designed solutions with web frameworks for multiple clients
Featured Publications
Recent Publications
(2023).
InstaLoc: One-shot Global Lidar Localisation in Indoor Environments through Instance Learning.
In RSS.
(2023).
Diffusion-based accent modelling in speech synthesis.
In Interspeech.
(2023).
Modelling low-resource accents without accent-specific TTS frontend.
In ICASSP.
(2021).
Universal Neural Vocoding with Parallel Wavenet.
In ICASSP.
(2020).
𝕏 Resolution Correspondence Networks.
In BMVC.
(2020).
SKD: Keypoint Detection for Point Clouds using Saliency Estimation.
In RAL/ICRA.
(2020).
Online LiDAR-SLAM for Legged Robots with Robust Registration and Deep-Learned Loop Closure.
In ICRA.
(2019).
Learning to See the Wood for the Trees: Deep Laser Localization in Urban and Natural Environments on a CPU.
In RAL/ICRA.
(2018).
Seeing the Wood for the Trees: Reliable Localization in Urban and Natural Environments.
In IROS.
(2018).
Predicting Alignment Risk to Prevent Localization Failure.
In ICRA.