• 2nd-Year Engineering Student in Image & Multimedia at ENSEEIHT

• B.Sc. Double Major in Mathematics & Computer Science at Université de Toulouse

Passionate about scientific computing, machine learning, and signal processing, I am aiming for a research and development career in the audio and multimedia fields. My academic background allows me to combine mathematical rigor with the power of software engineering.

• Inverse Audio Synthesis: Design of a deep learning model to infer synthesizer parameters directly from an audio source file.
  • Context: Research internship at the Institut de Recherche en Informatique de Toulouse (IRIT).
  • Tools: Python, PyTorch, Pyo Library, 2D CNNs, DSP.
  • Goal: While current AI trends lean towards direct audio generation, this project proposes an alternative approach—a tool capable of translating an existing sound into a synthesizer patch. The objective is to give control back to artists, allowing them to shape their sounds and preserve their creative freedom.

• Gamma & Beta Functions: In-depth theoretical analysis, analytic continuation, and a 40-page scientific report.
  • Tools: LaTeX, Beamer, Mathematical Analysis.

• Sports Motion Analysis: Development of a keypoint pose estimation pipeline from video frames.
  • Tools: Python, PyTorch, OpenCV, HRNet, LSTM.

• CMMS & VBA Tools: Development of macros to optimize maintenance processes and manage industrial databases over three consecutive summer periods.
  • Tools: VBA, SQL, Excel, Mainti4.

Programming & Scripting:

Data, AI & Tools:

Environment & Formatting:

• LinkedIn: linkedin.com/in/pierre-parodi