CV

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Research Internship

During my research internship at Satellite Applications Catapult (supervised by Dr Cristian Rossi), I applied physics aware machine learning to industrial remote sensing, developing models that leveraged physical properties such as temperature and soil moisture to detect and characterise cement production facilities in China. This experience directly informed my subsequent work on embedding physical signal properties as inductive bias in deep learning architectures.

• Deep Learning Coupled with Earth Observation Data Exploration of Polluting Plants Detection
  • 10 Jan 2022 - 10 Apr 2022
  • Satellite Applications Catapult
  • Duties included: Deep Learning and Earth Observation Satellite Data.
  • Supervisor: Dr Cristian Rossi
  • Publication

British Academy

As part of the Predictive Analytics Lab (PAL), I contributed to a British Academy-funded project on Satellite/Aerial Image Scene Segmentationon satellite and aerial image scene segmentation. In this context, I designed deep learning models for land use classification and multi-domain, multi-temporal data integration, using large scale real world imagery to study robustness between domains. Please see the demo below.

Teaching Assistant

• Computer Vision (G6032)
  • Level: Second Year
  • Winter-Spring 2020
  • Duties included: Coursework Marker - Tutorial Helper
• Automation and Mechatronics (875H1)
  • Level: Masters
  • Winter-Spring 2019
  • Duties included: Tutorial Helper
• Industrial Automation Systems (H7121)
  • Level: Third Year
  • Winter-Spring 2019
  • Duties included: Tutorial Helper
• Advance Electronic Systems (524H1)
  • Level: Masters
  • Autumn 2018
  • Duties included: Tutorial Helper - Created lab documentation, set up the lab equipment.

Industry

Prior to my doctoral studies, I worked as a Control and Automation Design Engineer in the oil and gas industry. This role provided hands on experience with sensor driven systems, signal acquisition, control architectures, and safety critical software development, shaping my long standing interest in how physical processes, sensing constraints, and system design interact with data driven models.

• Control and Automation Design Engineer (Oil and Gas)
  • 18 September 2006 - 18 May 2013
  • Rockwell Automation
  • Duties included: Full Software and Hardware Life Cycle, Functional Safety, Systems Sensing and Control, Communications, Project Planning and Management.

Education

I completed an EPSRC-funded PhD at the University of Sussex supervised by Prof. Andy Philippides and Prof. Novi Quadrianto, where my research focused on salient feature representation, domain adaptation, and semantic segmentation. This work laid the foundations of my current research agenda by investigating how feature representations degrade under domain shift and how architectural design choices influence generalisation.

• PhD in Deep Learning Aerial Scene Analysis: Extracting Salient Features for Domain Adaptation and Semantic Segmentation Tasks, University of Sussex, 2023
• MSc Modern Digital Communications Systems, University of Sussex, 2006
• BEng Honours Electronics with Communications Engineering, University of Brighton, 2005