I currently work in a law enforcement data science team, with a focus on geospatial analysis. My interests lie in crime analysis, particularly understanding the spatial distribution and concentration of crime, and how these patterns relate to the physical and built environment. More broadly, I’m passionate about leveraging diverse data sources to better understand public safety challenges, inform problem-solving approaches, and evaluate the impact of interventions.

Please note that all content on this site — including blog posts, articles, and opinions — reflects my personal views and not those of any employer, organisation, or affiliation.

Recent Posts

• OSINT: From Raw Text to Strategic Intelligence Assessment with Databricks

  October 12, 2025

  OSINT: From Raw Text to Strategic Intelligence Assessment with Databricks Published 12 October 2025 In law enforcement intelligence, analysts are often required to produce intelligence assessments — drawing from human, technical, or signal sources to inform operational or strategic decisions. While many assessments are case- or criminal organisation-specific, this example...

• Automatically scaling tactical analysis, crime bulletin and Compstat style text summaries

  August 04, 2025

  Automatically scaling tactical analysis, crime bulletin and Compstat style text summaries Published 4 August 2025 This walkthrough details a reproducible pipeline for text summarisation of recent felony offences across New York City using Python, Pandas and SQL. Inspired by Andrew Wheeler’s Data Science for Crime Analysis with Python, an ideal...

• Using Open Data to Explore Boston Crime

  May 07, 2025

  Boston Crime Analysis Mini-Project In this mini-project, I used three tools: PostgreSQL with PostGIS for storing geometry (neighbourhoods, police districts, and census tracts) and data tables (crime incidents, shootings). Python to crawl, load, and incrementally update the crime and shooting datasets from Analyze Boston. Power BI to build a simple...

Recent Maps

• hexseg: simplifying two popular methods used in crime place studies

  February 08, 2026

  hexseg: simplifying two popular methods used in crime place studies Published 8 February 2026 hexseg is a simple Python package I created to simplify generating statistics to prioritise locations for crime reduction efforts. It assists in streamlining two popular count-based methods by creating hexagonal grids or street-segment analyses across geographic...

• Visualising Crime Along Routes: Robbery density along London's Oxford Street

  May 11, 2025

  Visualising Crime Along Routes This example visualises the density of robbery along Oxford Street in London, using open data from police.uk. It’s inspired by the work of Alasdair Rae, who previously shared a technique for mapping elevation profiles along rail and road routes. This is a variation on that approach,...

• London Weapon Homicide and Gang Mapping

  April 19, 2025

  This interactive map explores patterns of weapon-enabled homicides and urban street gang locations across London between 2006 and 2024, using openly available data sources. Click here to view the map (Opens in a new tab) About the Layers The map includes seven layers that can be toggled on/off to explore...