Research + Innovation

Master’s Theses

Students have completed a wide variety of projects leading to master’s theses in music technology, either as EECS students, Media Lab students, or more recently, as Music Technology and Computation graduate students.

• ALPACA: An Algorithmic Pipeline for Automated Contour Annotation of Carnatic Music: A Dynamic Programming Framework for Pitch Segmentation and Note Transcription: Sruthi Parthasarathi, MEng Thesis, September 2025
• Octavio: A Distributed System for the Sensing, Storing, and Retrieval of Piano Playing Data: Ayyub Abdulrezak, MEng Thesis, May 2025
• SongGen: Framework for Controllable AI Song Generation through Interactive Songwriting and Artist Emulation: Ajay Arora, MEng Thesis, August 2024

• Orchestral Conducting in Virtual Reality: Nathaniel Kim, MEng Thesis, May 2023
• Arty: Expressive timbre transfer using articulation detection for guitar: Sebastian Franjou, MEng Thesis, August 2022
• Sensing String Displacement as a Control Modality: Sensor Design and Implementation: Silvia Knappe, MEng Thesis, May 2022
• Beatty: Automatic Tempo Curve Synthesis for Expressive MIDI Track Playback: Madeline Wong, MEng Thesis, May 2022
• Practica: A Music Education Application for Learning Jazz Improvisation: Julia Fiksinski, MEng Thesis, August 2021
• JamNSync: A User-Friendly, Latency-Agnostic Virtual Rehearsal Platform for Music Ensembles: Nanette Wu, MEng Thesis, June 2021