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Alison B. Ma is a driven and versatile professional currently working as a Product Manager at Vydia, where she utilizes her proficiency in cutting-edge audio technology and big data to strategically empower independent music labels. Formerly, she held roles as a Data Engineer & Audio Lead at WellSaid Labs, specializing in applied machine learning and text-to-speech synthesis. In addition to her professional endeavors, Alison actively works on her personal artist project, sound design craft, and entrepreneurial ventures within the audio / music space.


2020 - 2022

Georgia Institute of Technology


Master of Science in Music Technology

  • Music Informatics Research Lab

  • Focus on machine learning for audio, music information retrieval (MIR), and
    sound design for video games

2016 - 2019

Berklee College of Music


Bachelor of Music in Electronic Production & Design, Sound Design for Video Games

  • Focus on sound design for video games and interactive media

Previous education includes:

During her tenure at Georgia Tech, Alison was the recipient of the esteemed College of Design Dean's Fellowship for one incoming graduate student and participated as a member of the Music Informatics Group research lab. At the Berklee College of Music, Alison also garnered the Max Mathews Award amongst other scholarships and honors. Following the end of her time at Georgia Tech, Alison's machine / deep learning research, "Representation Learning for the Automatic Indexing of Sound Effects Libraries", was accepted for publication at the prestigious 23rd International Society for Music Information Retrieval conference hosted in Bengaluru, India (ISMIR 2022). This research featured collaboration with various audio post-production and game audio industry members, conducting novel research on the Universal Category System.

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As a sound designer, Alison is always looking to discover new possibilities for layering, mangling, and morphing sounds. She primarily loves to apply her sound design skills in interactive media applications, finding joy in both asset design and implementation. Unique manifestations of her work can be found at Georgia Tech's Sonification Research Lab where the target application was submersible research vessels and those with impaired sight at the Woods Hole Oceanographic Institute, as well as in her efforts as a contributing member at Itoka by OctAI, an AI/web3/NFT solution to music generation & monetization. She has experience in recording studios, i.e. Prairie Sun Recording. One of her experimental 2-channel sound design works for DSP & voice, Engulf, was presented at the SEAMUS National Conference in 2020.


As a researcher, Alison's interests reside within the field of digital signal processing, music information retrieval, and machine learning for musical applications. Her efforts are motivated by her desire to discover uncharted heights of sonic inspiration, reduce repetitive tasks so that creativity always takes precedence, and understand the fundamental building blocks that make up sound. Currently, Alison has been developing her knowledge in the meta/continual-learning of sound databases as well as generative models for sound synthesis, speech synthesis, and music generation.

Fun facts about Alison:

  • Games I'm playing...

    • It Takes Two, Super Mario Bros. Wonder, Fortnite

  • Go-to instrument: Modular synths!

  • Favorite kind of plug-in: Saturation (post-2021)

  • Latest sound design discovery: GRM Tools Shift for robot voices

  • Guilty pleasure: Organizing data...

  • Niche interest: Personalization through sound design or machine learning

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