curriculum vitae

University of Aberdeen – BSc in Computing Science and Mathematics

• Grade: First Class
• Undergraduate Thesis: "Stylistic Models for Authorial Recreation: A Comparison of Transformer-based Language Models for Author-Styled Latin Text Generation", supervised by Dr. Ehud Reiter
• Relevant Coursework: Languages and Computability, Artificial Intelligence, Intro to Machine Learning and Data Mining, Algorithmic Problem Solving, Intro to Data Management for Data Science, Research Methods, Principles of Software Engineering, Software Engineering and Professional Practice, Linear Algebra I-II, Analysis I-IV, Complex Analysis, Differential Equations, Nonlinear Dynamics and Chaos Theory I, Group Theory, Galois Theory, and Modelling Theory

Rensselaer Polytechnic Institute – Computer Systems Engineering

• Started my undergraduate education at RPI before transferring to the University of Aberdeen

Fordham Preparatory School – High School Diploma

Research Software Engineer @ Northeastern University

Demonstrator (Teaching Assistant) @ University of Aberdeen

• Led tutorial sessions for CS2522 Algorithms and Data Structures

Summer Analyst @ Goldman Sachs

• Worked on an internal web app, following a scrum methodology using Jira
• Created components for the front end in Typescript and React with 100% test coverage in Jest
• Wrote the back end in Java using Springboot, deployed on AWS ECS Fargate, and rewrote the same functionality in Python, on AWS Lambda

Data Science Intern @ ReSource Pro

• Researched and applied machine learning models to Insurance Documents to automate laborious processes
• Developed three key models: one that can discern the type of insurance document provided currently used on thousands of documents daily, one that could determine the type of Acord Document File, and a proof of concept joint Part-Of-Speech Tagger and Neural Network Dependency Parser to generate Insurance Policy Document Summaries

Using Machine Learning to reduce localisation errors for automated radiotelemetry systems

• Quadrat Undergraduate Research Experience Placement @ University of Aberdeen
• Supervised by by Dr. Justin Travis
• Worked on applying Machine Learning to reduce localization errors for automated radiotelemetry systems to track animals
• Using Python (PyTorch, Scikit, NumPy) I improved the initial multilateration error from over 150m to 60m

Simulating Chess Playstyle

• Undergraduate Research @ Rensselaer Polytechnic Institute
• Led Undergraduate Research Project, Aleph Naught, which aimed to simulate the playing style of a chess player given their historical games
• Culminated in a Proof of Concept that won Best Implementation and Potential for Growth at IvyHacks, an online Hackathon co-hosted by Ivy League universities with 1500+ participants, in Oct 2020
• Built the FrontEnd in Vue.JS, and both the model, a Binary Classifier that determines how likely a position would be played, and the BackEnd were written in Python using TensorFlow, NumPy, Scikit, and Flask.

• North American Merit Scholarship (2021)
• Findlay Walker Scholarship (2020)

• University of Aberdeen Intelligent Plant Inform Prize (2022) for the project Bumpr developed as part of the Software Engineering Course
• University of Aberdeen Jenkyns Prize in Greek/Latin Language (2022) for attaining the highest marks in the study of Greek or Latin language
• University of Aberdeen Black Prize (2022) for being the best Latin scholar
• University of Aberdeen’s Chancellor’s List (2021)
• Received Two Classwide Awards at Fordham Prep (2018):
  • The School’s First Recipient of Excellence in both Latin and Ancient Greek
  • Excellence in Fordham University Coursework, for my success in CISC 3060: Introduction to Robotics, concurrently taken in my senior year of high school.

• University of Cambridge’s Hex Cambridge: People’s Choice & Wolfram Award (2021)
• Ivy League Hackathon IvyHacks: Best Implementation and Potential for Growth (2020)
• CalTech’s HackTech: Best COVID-19 Awareness & Prevention Hack & Best Use of Google Cloud (2020)
• Cornell University’s Big Red Hacks: Best Technical Feat (2018)
• Google Code-In: 8^th in Moving Blocks Organization (2016)
• United Nation’s Unite for Humanity Hackathon: 1^st (2016)
• Penn State App Competition: 3^rd place (2016)
• DefHacks(NY): HackerEarth Award for Best Problem-Solver Application (2016)

Bumpr

• Made a tinder-esque app for people to buy used cars on a team using an Agile workflow
• Used React Native for the Frontend and Flask, Firebase, & Open-Cv in Python for the Backend

Chadvice

• Created an Android Application that, utilising Natural Language Processing and Machine Learning, provides analysis of your dating app conversations in real-time, gauging their interest and the likelihood of getting ghosted
• Developed the Frontend in Java and the Backend in Python, hosted on Google Cloud

Coronadvisor

• Trained an Artificial Neural Network and XGBoost Regressor, based on our engineered daily data from Johns Hopkins, to predict confirmed cases and deaths in given regions due to COVID 1 year into the future, visualised on Esri
• Used Pandas, Scikit, TensorFlow, Flask, arcGis, Google Maps Geolocation API, HTML, CSS, and JavaScript

Check It

• Built a plagiarism detector that analyses the writing style of a new essay and compares it to the writing style of the student that submitted it
• Built the Frontend as a C# WPF Application and applied NLP methodology in Python to create the model