CV

Basics

Name Christodoulos Benetatos
Label Research Scientist
Email [email protected]
Phone (585) 406-8092
Url https://cbenetatos.com

Work

  • 2022.06 - 2022.08

    Santa Clara, CA

    Research Scientist Intern
    ByteDance Inc.
    • Developed generative models (VAE and Transformers) to improve various automatic music generation pipelines.
  • 2020.08 - 2020.11

    Seattle, WA

    Research Scientist Intern
    Kwai Inc.
    • Conducted multimodal modeling of dance videos focusing on visual beat tracking and real-time body gesture recognition.
    • Created a real time digital audio effects suite in C++ (JUCE) for iOS.
  • 2018.09 - 2024.12

    Rochester, NY

    Research Assistant
    University of Rochester, AIR Lab
    • Developing novel AI tools (algorithms and prototypes) to assist in the music making process using generative models.
  • 2018.01 - 2018.08

    Athens, Greece

    Software Engineer
    Metis Cyberspace Technology
    • Designed algorithms for real-time remote monitoring and performance assessment of equipment onboard vessels.

Education

  • 2018.09 - 2024.12

    Rochester, NY

    PhD
    University of Rochester
    Electrical and Computer Engineering
    • Focus Areas: Deep Learning, Music and Audio Signal Processing
    • Supervised by Prof. Zhiyao Duan
  • 2011.09 - 2017.12

    Athens, Greece

    BSc and MEng
    National Technical University of Athens
    Electrical and Computer Engineering
    • Thesis: A Brain Computer Interface (BCI),using Steady State Visual Evoked Potentials (SSVEP), for the task of maze navigation.
    • Supervised by Prof. A. G. Stafylopatis and Dr G. Siolas

Publications

Skills

Programming Languages
Python
C++
JavaScript
Java
Matlab
Frameworks
Pytorch
JUCE
Vue.js
Spring
Instruments
Classical Guitar
Flute
Mandolin
Cajon
Music Production
Reaper
Sample Library Programming

Languages

Greek
Native speaker
English
Fluent

Projects

  • 2023 - Present
    Guitar Score Reduction as a Reinforcement Learning Problem
    • Framed the task of guitar score reduction as a combinatorial optimization problem and used Proximal Policy Optimization (PPO) to solve it.
    • Designed novel rule-based and data-driven reward functions to guide the learning process.
    • Used a transformer-based RL agent that operates on scores represented as graphs.
  • 2023 - Present
    HARP
    • Lead Developer
    • HARP lets users of Digital Audio Workstations (DAWs) access large state-of-the-art deep learning models using cloud-based services without breaking the within-DAW workflow.
  • 2021 - 2023
    Euterpe: A Web Framework for Interactive Music Systems
    • Enabled researchers without JavaScript expertise to easily deploy musical agents on the web.
    • Supported real-time audio/MIDI synchronization and data visualization.
    • Re-Implemented various deep-learning musical agents using Euterpe and gave a tutorial in ISMIR 2023.
  • 2020 - 2021
    Draw and listen!
    • Built a sketch-based system for music inpainting enabling users to draw a melodic contour and hear them realized instantly.
    • Derived a new melody disentanglement scheme: melody = contour + rhythm + context.
    • Designed a VAE architecture that realizes the above disentanglement.
  • 2021 - 2022
    Score Following for Event Augmented Live Performances
    • Implemented a modified ODTW algorithm for real-time audio-score alignment.
    • Developed a UI to visualize the alignment and activate events.
    • Used OSC to send event in real-time a TouchDesigner instance for triggering sound and video effects
    • Deployed the system in a mini-concert with the TableTopOpera.
  • 2019 - 2020
    BachDuet
    A human-machine duet improvisation system.
    • Designed a RNN model for real-time musical counterpoint improvisation.
    • Trained on duets extracted from Bach Chorales.
    • Implemented a prototype system and demoed it live at various venues.