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Curriculum Vitae

Education

  • University of EdinburghSep 2022 – Sep 2023
    Data Science MSc· 2023
  • University of GroningenSep 2020 – Jul 2022
    Philosophy BA· 2022
  • University of GroningenSep 2017 – Jul 2021
    Astronomy BSc· 2021

Skills

Core Engineering

  • Design and implement end-to-end ML/data workflows from ingestion to prototype deployment.
  • Implement data quality controls: schema enforcement, automated validation, experiment lineage, and tracking.
  • Ensure reproducibility with containerised environments (Docker/Podman), deterministic builds, and automated CI/CD pipelines.
  • Collaborate effectively in coding projects using modern workflows and review practices.

Data Science & Machine Learning

  • Design and train machine learning models, including deep learning architectures.
  • Apply statistical, probabilistic, and Bayesian methods for analysis and prediction.
  • Develop workflows for data preprocessing, feature engineering, and model evaluation.

Data & Platform

  • Scale experimentation with Ray and optimise GPU throughput.
  • Model domain knowledge via semantic graphs (RDF/SPARQL, ontology design).
  • Manage storage and analytical layers (Ceph, PostgreSQL, Apache Jena, Apache Iceberg).

Tooling & Ecosystem

  • Languages: Python (primary), R, MATLAB; working knowledge of Rust.
  • Development & Collaboration: Git workflows, reproducible environments (Fedora Silverblue, containerisation), cloud platforms (GCP); experienced with AI-assisted development (GitHub Copilot).
  • Libraries & Frameworks: • Machine Learning & AI: PyTorch, PyTorch Lightning, scikit-learn, Pyro, Ray, Darts, GluonTS. • Data Analysis & Visualization: pandas, NumPy, Matplotlib, seaborn. • Databases & Storage: SQL (Postgres, GCP SQL), Supabase, Apache Jena, Apache Iceberg, Ceph.

Soft Skills

  • Strong work ethic, logical thinking, and flexibility developed through academic, professional, and volunteer roles.
  • Effective communicator of complex technical concepts to diverse audiences; demonstrated through teaching and collaborations with non-technical stakeholders and domain experts.
  • Adaptable between research and production contexts; delivers iteratively with a record of successful execution.

Employment

  • Lead Machine Learning EngineerJul 2024 – November 2025
    xRI - Urban Robotics & Analytics
    • Architect and implement robotics data pipelines enabling robust high-volume ingestion for analytics and model training from ROS robots.
    • Design and run machine vision experiments.
    • Design and implement schemas for both relational and graph (linked data) databases.
    • Translate technical design, progress and trade-offs to various stakeholders.
    • Provide technical leadership: architecture and project design, system and code reviews, mentoring.
  • Research EngineerNov 2023 – Jul 2024
    xRI - Urban Robotics & Analytics
    • Developed sensor drivers for ROS robots.
    • Collaborated on the development of a system for deploying, monitoring and updating a ROS robot in the field.
    • Designed and deployed distributed compute and storage clusters accelerating data processing and ML experimentation.
  • Student MentorSep 2021 – Jun 2022
    University of Groningen
    • Provided academic and personal support to undergraduate students.
  • Physics Lab Teaching AssistantSep 2021 – Nov 2021
    University of Groningen
    • Guided students through physics lab experimentation; enforced methodical data collection, graded reports and provided constructive feedback.
  • Linear Algebra Teaching AssistantNov 2020 – Feb 2021
    University of Groningen
    • Led tutorials teaching linear algebra fundamentals; graded problem sets and exams with constructive feedback.

Key Projects

Design and implementation of a linked data ontology DOB

xRI Open Linked Data Standards Project

  • Co-developed a domain ontology for representing data collected by the robotics platform about the built environment.
  • Implemented the ontology and deployed it to a triplestore now hosting over 500 million triples.
  • Enabled scalable semantic queries and integration across a number of open datasets e.g. OS OPEN UPRN, NHS ODS, ONS Statistical Geographies.
  • Open-sourced the ontology, available at GitHub for community use and extension.

Built Environment Scanning System

xRI Robotics Platform for Urban Data Collection

  • Collaborated on the design and implementation of a multi-sensor data collection platform mounted on a car for urban data collection.
  • Developed a novel ROS driver for radiometric temperature capture from a thermal camera.
  • Ported prototype ROS code to a production system deployed on vehicles in the field.
  • Developed an encrypted and robust sneakernet system for data offload and transfer from the vehicles to data centre.
  • Led the development of a data ingestion and processing pipeline handling tens of terabytes of data per week.

Identification of highly boosted H→γγ decays with the ATLAS detector using deep neural networks

MSc Dissertation (3 months)

  • Developed a deep neural network jet tagger to identify highly boosted H→γγ decays in ATLAS data.
  • Implemented an adversarial mass-decorrelated classifier reducing mass-sculpting bias in signal discrimination.
  • Published research on the CERN Document Server.
  • Presented approach to ATLAS and CMS working groups at CERN.