PhD student, ADASP team, LTCI
Machine learning for music, specifically musical version identification (cover song identification). PhD under a CIFRE agreement with Claimy, a Paris music-tech company working on royalty recovery.
Current role
Work experience
Machine learning intern
Improving active noise cancelling systems using representation learning.
DSP intern
Digital modeling of magnetic tape recorders of the 70s and 80s, from electronics measurements to final DSP implementation.
Developer, Battle Lab Terre (STAT division)
Designed and operated the main real-time GPS refereeing/judging system aiding the national CoHoMa challenge organisation team.
Research intern
Explored applications of vision algorithms to aid the visually impaired.
Education
PhD, Télécom Paris
ADASP team, LTCI. École doctorale de l'Institut Polytechnique de Paris. Machine learning for music, under a CIFRE agreement with Claimy.
ATIAM Master, IRCAM / Sorbonne University / Télécom Paris
Acoustics, signal processing, and computer science (machine learning) applied to audio.
Engineering degree, Signal and Artificial Intelligence, ENSEA Cergy
Digital signal, image and audio processing, machine learning, and real-time implementation on embedded platforms.
Prépa MPSI/MP, Lycée Malherbe, Caen
Graduate-level mathematics, physics and computer science.
Projects
Neural dissection
Feature visualization in neural networks (GoogleNet, GANSynth).
Real-time audio effects on STM32
Bit-crusher, feedback delay, compressor.
Digital electronics simulator
For engineering students, at pharoahjardin.com/ajen.
Analog polyphonic synthesiser with arpeggiator
Project for an audio course.
Skills
- Fields
- Machine learning, deep learning, real-time systems, signal processing, computer science.
- Programming
- Fluent in C, Python, Java, HTML/CSS/JS. Familiar with Swift, OCaml, C++. Experience with LaTeX typesetting.
- Languages
- Fluent: English, French. Basic: Spanish, Japanese, Italian, Tamil.