Background

• PhD Mathematics for Real-World Systems - University of Warwick (2023)
• MSc Mathematics for Real-World Systems Distinction - University of Warwick (2016 - 2017)
• BSc Mathematics with Economics 1st Class - Loughborough University (2013 - 2016)

My main focus has been on applied mathematics but I have had exposure to a variety of mathematical techniques. The economics component of my undergraduate degree allowed me appreciate the balance between mathematics and the real world. During my education, I have used Maple, C++, R, MATLAB, Python, and Julia.

Current Research

I am interested in applying data science to financial data, and am currently using convolutional neural networks to infer house prices from a range of sources consisting of image data. Technology has advanced rapidly over the past decade, as well as the volume of images available online. Combining newly developed computer vision algorithms with big data could provide us with new insights regarding house prices. My supervisors are Suzy Moat & Tobias Preis from Warwick Business School and my industry partner is the Office for National Statistics. I use Ubuntu (Linux) and Python 3 for the majority of the time.

Previous Projects

Using Deep Learning Tools To Infer House Prices From Geograph Images (2019-2020)
Suzy Moat (University of Warwick), Tobias Preis (University of Warwick), and Mario Gutiérrez-Roig (University of Warwick)

• Combining convolutional neural networks with Geograph images to develop models that infer ONS house prices
• Worked with Python 3 and used SCRTP HPC facilities

 

Using Deep Learning Tools To Infer House Prices From Zoopla Images (2018-2020)
Suzy Moat (University of Warwick), Tobias Preis (University of Warwick), and Mario Gutiérrez-Roig (University of Warwick)

• Combining convolutional neural networks with indoor Zoopla images to develop models that infer ONS house prices
• Worked with Python 3 and used SCRTP HPC facilities

Nowcasting House Prices With Google Trends (2018-2019)
Suzy Moat (University of Warwick), Tobias Preis (University of Warwick), and Federico Botta (University of Warwick)

• Using Google Trends data and the UK House Price Index to develop models that nowcast house prices
• Mainly worked with R to clean data and develop models
  
  

Using Deep Learning Tools To Infer House Prices From Google Street View Images (2017-2018)
Suzy Moat (University of Warwick), Tobias Preis (University of Warwick), and Mario Gutiérrez-Roig (University of Warwick)

• Combining convolutional neural networks with Google Street View images to develop models that infer ONS house prices
• Worked with Python 3 to build on the MSc project and identify important factors
  
  

MSc Project: Using Deep Learning Tools To Infer House Prices From Google Street View Images (2017)
Suzy Moat (University of Warwick), Tobias Preis (University of Warwick), and Mario Gutiérrez-Roig (University of Warwick)

• Combining convolutional neural networks with Google Street View images to develop models that infer ONS house prices
• Worked with Python 3 to clean big data and develop models
  
  

MSc Study Group: Modelling Ecologies Of Financial Investors: Exploring The Impact Of Momentum Investment On Financial Stability (2017)
Robert MacKay (University of Warwick), Nicholas Beale (Sciteb), and Richard Gunton (Sciteb)

• Developing a simplified model of the financial market, including assets and investment strategies
• Worked with MATLAB to develop models and incorporate various market strategies

---

Work Experience

Data Science Intern, Spectra Analytics (March 2019 - June 2019)

I learned and applied a variety of data science techniques that are not covered by my PhD, and observed the process of a data science project in industry from start to finish. Techniques learned include web scraping and app development.

Technical Support, Warwick Mathematics Institute (September 2018 - present)

• Mathematics for Real-World Systems Technical Support
• Taught Course Centre (TCC) Technical Assistant

I provide technical support for the Mathematics department at the University of Warwick. Support includes Linux set-up, HPC support, and coding questions. I also manage the MathSys social media accounts.

Big Data Analytics, Warwick Business School (January 2018 - present)

• Big Data Analytics: Behaviour Science Laboratory Assistant
• Big Data Analytics: MOOC Assistant

I help MSc students with R coding problems and general big data queries in the laboratory, and maintain the online forum for the MOOC.

Quantitative Analysis for Management, Warwick Business School (October 2018 - present)

• Quantitative Analysis for Management I: Seminar/Workshop Tutor
• Quantitative Analysis for Management II: Seminar/Workshop Tutor
• Microsoft Office Specialist Excel 2016 (April 2018)

For both QAM I and QAM II, I am a seminar tutor for three groups of ~25 students. I teach 1st-year undergraduates how to solve a variety of quantitative problems and promote group work. QAM II involves using Microsoft Excel 2016, which I became certified in in 2018.

Introduction to GPU Programming Summer School 2018

I assisted with the summer school by checking the material before use and assisting with the tutorial sessions. I provided technical support and answered questions.

---

Extra Activities

Data Science For All (September 2021 - December 2021)

• I collaborated with researchers from around the world to apply data science to understand the perception of work-from-home of those affected during the pandemic
• I also networked with data scientists in industry to understand how it can be applied to real-world problems

Data Study Group, The Alan Turing Institute (December 2018)

• I participated in the 'Player Pathways' project proposed by PlayerLens - understanding career paths that deliver success for professional football players and clubs - at the Alan Turing Institute
• We were provided with player data and applied machine learning tools to identify career pathways for players

Severn Trent Water Hackathon (June 2018)

• I participated in a hackathon at the Severn Trent Water headquarters in Coventry
• We were provided with multiple data sets and processed the data to find insights

Kaggle SQL Scavenger Hunt (February 2018)

• I often use Kaggle to learn new data science techniques, and followed the scavenger hunt to learn SQL as a beginner
• During my internship at Spectra Analytics, I developed my SQL skills further through practical application

ARCHER Online Message-passing Programming with MPI (February 2018)

• To learn about parallel programming, I followed the ARCHER course online using C++
• I have learned techniques for parallalising code and high-performance computing that I use in my PhD

UQ&M Data Study Group 3, University of Warwick (December 2017)

• I participated in the 'Machine Learning for Wind Energy Modelling' project proposed by Zenotech - explore how well machine learning methods might be able to infer the interaction patterns and consequent power production from sites, given sufficient training data
• We were provided with data from wind turbines and applied machine learning tools to identify patterns, such as neural networks

Machine Learning Reading Group, University of Warwick (October 2017)

• I gave a 30-minute talk at the MLRG at the University of Warwick
• My talk discussed my MSc project to infer house prices from Google Street View images using convolutional neural networks

Introduction to Machine Learning Summer School, University of Warwick (June 2017)

• I participated the summer school to broaden my knowledge on machine learning
• The mathematics behind a neural network was described and I coded a simple neural network

European Study Groups with Industry 130, University of Warwick (September 2017)

• I briefly participated in the ESGI130 at the University of Warwick