cv

General Information

Full Name Rufus Behr

Education

  • 2020 - 2023

    UK

    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
  • 2018 - 2019

    USA

    Rensselaer Polytechnic Institute – Computer Systems Engineering
    • Started my undergraduate education at RPI before transferring to the University of Aberdeen
  • 2014 - 2018

    USA

    Fordham Preparatory School – High School Diploma

Work Experience

  • August 2023 -
    present

    Remote

    Research Software Engineer @ Northeastern University
    • Infrastructure as Code: automated course creation process for professors that wanted to use our High Performance Computing (HPC) Cluster by interfacing with Canvas, creating UNIX accounts and groups, and populating the filesystem with ACLs and quotas; this automation freed $\sim$10 hours a week for sysadmins at the start of semesters
    • Developed and containerized tools for sysadmins and users of the cluster -- including, among other things, enabling user interaction with our filesystem quotas using identd for authentication, research group management, and an http server to redirect our servers update requests to a local mirror
  • Jan 2023 -
    May 2023

    Aberdeen, UK

    Demonstrator (Teaching Assistant) @ University of Aberdeen
    • Led tutorial sessions for CS2522 Algorithms and Data Structures
  • Summer 2022

    London, UK

    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
  • Jun 2018 -
    Dec 2020

    Qingdao, China,
    & Remotely

    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

Other Research Experience

  • Summer 2022

    UK

    Using Machine Learning to reduce localisation errors for automated radiotelemetry systems
  • Autumn 2019

    USA

    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.

Honors and Awards

Technical Projects

  • 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