I am currently a Doctoral Researcher at the Centre for Centre for Advanced Spatial Analysis, UCL, working on modelling flows of loyalty card data and total revenue to grocery retailers across the UK. I am interested in exploring how Data Science and Software Engineering can be used to support our understanding of the built environment and how we can use this to improve the way in which we interact with the city around us. I have expeirence working with a variety of different technologies including Python, React, Java and Javascript and have created websites, data science projects and Android Apps. Below you will be able to see some of the works that I have been doing in my spare time.

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Shopping List Application

My lastest project has been the creation of a shopping list application which is currently available on the Google Play Store. The aim of this project was to develop android application development skills. The code repository for this application can currently be found on GitHub and I hope to continue to build on this in the near future. This application currently has:

  • The ability to add items
  • The ability to delete individual items
  • The ability to mark items as in the basket
  • The ability to delete grouped items
  • A how to use the application page

UK Transport Profiles

This project was created as part of my MSc in Smart Cities and Urban Analytics that was subsequently moved onto AWS. This website was developed as part of a distributed team with the aim of identiyfing different transport profiles across the UK by their transport mode usage and accessibility. This was achieved using publicly available data on travel to work in the 2011 census on data on different transport modes accessibility. The website is currently hosted on an AWS lightsail instance, for which Python was used for the data Analysis, SQL is used to host the transport data, and the front-end being built with JTML, css and Javascript. The website, along with further details of the project can be found here.

Medium articles

As part of my interest in Data Science I have regulalry published medium articles on topics and areas of interest. This includes Data Science projects that have used tools and techniques that I have learnt or was interested in. Notable projects include:

Further articles on Medium can be found on my Medium profile.

Head of Science for the UCL Data Science Society (2021-2022)

In July 2021 I took on the position of the Head of Science for the UCL Data Science Society. In this role I built on the work of the previous Head of Science to expand the societys set of workers from 12 to 23 and updated five further workshops. I was supported by 2 Science Executives who helped to create and deliver these workshops throughout the first and second term of the year to the largest student led Technology focused society at UCL. Additionally, all workshops that were delivered during the year were built into a series of Medium articles to increase our exposure. To date, these articles have reached over 200,000 views beyond UCL. A summary of these workshops can be found on Medium here. Workshops that I created include:

And those that I updated throughout the year include:

Development Planning Unit Alumni Website

Myself and a colleage were commissioned to produce an alumni website for the Development Planning Unit, UCL, to allow their alumni to interact with each other on a dedicated platform. For this I developed a continuous pipeline that updated the website data based on a firebase database of new alumni sign-ups using GitHub action, and created a dashboard that allowed the department to accept or reject new users alongside visualise website usage statistics. This was created over a period of two weeks where the following tasks were completed:

  • A python script was created that geocoded the locational information of users into a GeoJSON that could be served up to the website to use in the Mapbox visualisation.
  • A GitHub action was set up to load in new data from the firebase database every 12 hours into the Python script, which would then create a refreshed GeoJSON
  • A Plotly Dash dashboard was created and hosted on Heroku that would give the department the ability to visualise usage statistics including active users and where they are located. Additional functionality included a downloadable table that contained contact information for users who wished to be included on regular corresponence, and an interactive table that provided the department the ability to accept or reject users based on their profile information which would then feed into the GitHub Actions work in that only verified users would be displayed on the maps created

The website has been successfull running for the past year and successfully hosts over 300 active users.


Since starting my Masters in Smart Cities and Urban Analytics in 2019, and throughout the PhD, I have participated in, and been ranked, in several hackathons. These include:

  • Hex Cambridge (2021): My team competed in Hex Cambridge desigining a website to be able to identify and map hostile architecture based on a submission and computer vision tagging algorithm. In this project I was responsible for deployment of the Flask application to the Google Cloud Platform and integration with the AdAstra Database. We were awarded the Wolfram Award and Best use of DataStax Astra. Our submissino can be found on the MLH website here.
  • CASA Hackathon (2021): My team competed in the CASA-Hackathon to geocode and analyse residential address data for Dubai for JLL. Our team, on geocoding over 90% of the addresses, was awardded first place. After geocoding the data, we began to explore the data and performed a cluster analysis of sales over the 10 year period of the data. I was responsible for geocoding the data using Open Street Maps and performing the clustering analysis.
  • Citadel Data Open (2022) World Finals: Our team competed at the Citidal Data Open world Finals in examining plastic pollution across the world. Out solution utilised a spatial interaction model solution to determine the potential for changes in plastic trade across the world and hence identify future hotspots for increased plastic pollution based on existing plastic pollution policies. Our final report and notebook can be found here. I was responsible for developing and applying the spatial inetraction model to the data to predict plastic trade flows in 2030.

Technologies and Skills

Below you will find descriptions and links to some of the tools and skills that I routinely use and that I am comfortable with.

  • GitHub

    Here you will find a link to my GitHub account and my repositories for my differnt projects. I have used this for version control for my projects, I manage the UCL Data Science Society GitHub page, I have worked collaboratively in large teams using GitHub and I have used GitHub Actions to create a continous workflow for the DPU Alumni website. I have been a Postgraduate Teaching Assistant on the Introduction to Programming Module, which teaches Python, on the Smart Cities and Urban Analytics MSc.

  • Python

    Python is the dominant language that I work in using libraries such as: Pandas, Matplotlib, Seaborn, Plotly, SciKit-Learn, Statsmodels and Geopandas. Most of work tends to involve geospatial data so geospatial libraries such as Geopandas, PySal and others tend to be used.

  • SQL

    SQL is a language that was used for Transport Profiles across the UK project to deliver the flows to the map page. I also helped teach this language on the Spatial Data Capture, Storage and Analysis Module for the Smart Cities and Urban Analytics MSc, along with developing a SQL workshop for the UCL Data Science Society.

  • AWS / Microsoft Azure

    I have familiarity with AWS as the UK Transpot Profiles website is currently hosted on an AWS lightsail instance which I continue to manage on behalf of my group. I also recently received my Azure Data Fundametals Certificate for Azure.

  • HTML, CSS, Javascript, R

    These are all technologies that I encountered in my MSc Smart Cities and Urban Analytics for which I recieved a distinction in all modules, including those using these technologies in their final assessment. While I do not currently use these in my workflows, I am familiar with them and I could continue to develop these skills in the future.