Ruari
Molyneux

Education

Queen Mary University of London

Sound and Music Computing MSc - Distinction | SEP 2023 - AUG 2024

Audio Programming

Developed real-time audio effects using C++ and the JUCE framework.
Grade: 98%

Music Informatics

Explored music signal processing concepts including beat tracking, audio identification, and chord/pitch recognition.

Fundamentals of DSP

Studied DSP theory, including sampling, spectrum analysis, and filter design, with practical applications in MATLAB.

Digital Instrument Design

Designed and prototyped digital musical instruments by combining music, design, and engineering methodologies.

Sheffield Hallam University

Computer Science BSc - 2:1 (69.4%) | SEP 2018 - MAY 2021

Work Experience

Sonic Baume | Software Engineer

OCT 2024 - JUN 2025

  • Collaborated with an Ex-BBC lead research engineer to design and implement a SaaS product for personalized audio production.
  • Researched and developed algorithms integrating Large Language Models to analyse transcripts, music, and sound effects.
  • Collaborated with a UX/UI design agency to assess and refine wireframes, resulting in a more intuitive user experience.
  • Technologies: Typescript, Next.js, Node.js, Tailwind CSS, AWS, Generative AI.

Simpleweb | Software Engineer

FEB 2022 - FEB 2023

  • Designed and implemented tools on decentralized platforms.
  • Created a Slack-based colleague rewards system with internal tokens.
  • Developed a workspace/desk optimization system for Bath University using carbon reduction incentives.
  • Engineered full-stack solutions using Next.js, Express.js, and Laravel.
  • Participated in client meetings to refine project requirements.
  • Delivered projects using LEAN and AGILE methodologies.

Skills

Audio Development: C++, JUCE, DSP, Python, MATLAB

Web Development: React, Next.js, Typescript, Tailwind CSS, Node.js, SQL

Ops/Other: GIT, Docker, AWS

Personal Projects

Geometric and Visual Reverb
  • Synthesizing room reverb using geometry mapping, image recognition, and DSP techniques.
  • Technologies: Python, MATLAB.
Beat Tracking
  • Dynamic programming algorithm for efficient beat detection.
  • 77% accuracy on a ~600 file dataset, evaluated in ~2 minutes.
  • Technologies: Python.
Audio Identification
  • Implementation of an industrial-strength audio search algorithm, also known as the Shazam algorithm.
  • 80% accuracy on a 200 file dataset.
  • Technologies: Python.
Schroeder FDN
  • Feedback Delay Network and Schroeder all-pass comb filter reverb plug-in.
  • Technologies: C++, JUCE.
Scattering Delay Network
  • Efficient room acoustic simulation implementation.
  • Technologies: Python.
a_bowl_of_grain
  • A digital musical instrument mapping a physical grain of sound to a virtual grain in a granular synthesiser.
  • Technologies: MaxMSP, Arduino.
Social Planner
  • A web app suggesting routes and venues for evenings out.
  • Technologies: Typescript, PHP, Next.js, Laravel 8, Tailwind CSS, MySQL.
Depop Refresher
  • A Chrome extension automating the task of refreshing Depop listings.
  • Technologies: Typescript, React, Nest.js, MySQL.
Glastonbury Set Finder
  • A web app suggesting festival performances based on Spotify liked tracks.
  • Technologies: Next.js, Tailwind CSS, Spotify API.

Interests