cv

Vibert Thio

website | github | linkedin | vibertthio [at] gmail

Vibert’s main interests are using audio/music machine learning for helping people express themselves.

Experience

2021 – now Senior Machine Learning Engineer ByteDance

• Working on Music AI for music creation.

2020.10 – 2021.03 Research Intern ByteDance

• Worked with Speech, Audio & Music Intelligence (SAMI) Team to developed creative applications for musical expression.

2020.6 – 2020.9 Research Intern Google Brain

• Worked with Magenta and Google Arts & Culture.
• Applied machine learning to make music easier to play with, e.g. Lo-Fi Player.

2019.4 – 2020.4 Software Engineer FRM

• Designed and implemented experimental features. It involved frontend (JavaScript, WebGL, and interactive design), and backend (legacy PHP, Phalcon framework, web socket, MySQL, and Redis).
• iOS app (React Native, React, Redux, and IoT).

2018.8 – 2019.7 Research Assistant Music and AI Lab

• Built 7 different projects with musical machine learning model. Two of them are featured on Magenta, Google Brain.
• Published academic paper to IUI2019 and NIPS2019.

Press Coverage

• MIT Tech Review
• The Verge
• Engadget
• #1 on Hacker News

Publications

• “Neural Loops”. Vibert Thio, Chris Donahue. NIPS Creativity, 2019.
• “A minimal template of interactive web-based demonstrations for musical machine learning ”. Vibert Thio, Hao-Ming Liu, Yin-Cheng Yeh, and Yi-Hsuan Yang . IUI , 2019.

Education

2019 - 2021 New York University

• Master Degree, “Interactive Telecommunication Program”

2013 - 2017 National Taiwan University

• Bachelor of Engineer, “Electrical and Electronics Engineering”