Nathan Touboul

Experience

• Software Developer, Grass Valley Canada Oct 2024–present

  Design, development, and maintenance of major software components in C++ for video and audio broadcast solutions. Provides technical guidance and participates in all stages of the software development lifecycle. Applies software engineering best practices including unit testing, code review, and continuous integration.

• Software Developer, CGI – Hydro-Québec Apr 2024–Oct 2024

  Developed server-side C and client-side C++ code for Hydro-Québec’s CED project (Centre d’Exploitation du Réseau — network operations centre). Added new features and fixed defects for electricity outage management. Developed the backend of a new web application in C#, .NET, and REST APIs within the WebCED team.

• Software Engineer, Velo3D Dec 2022–Nov 2023

  Developed C++ and Python software to control electronic and pneumatic systems for metal 3D printers, spanning multiple multi-threaded processes across embedded systems. Implemented a process-critical monitoring and override interface accessible from the main QML UI, enabling customers and manufacturing engineers to qualify new printers reliably. Enhanced oxygen correction using multi-sensor filtering, reducing build failure rate. Upgraded the laser controller firmware’s BKM framework with additional configurations, introduced the latest sensors and controls into the simulator for next-generation printers, and reworked powder bed recoating using asynchronous pneumatic controls. Worked in an agile team with Jira, Git, pull request reviews, and CI/CD via Jenkins.

• Software Engineer, Qualcomm Mar 2022–Dec 2022

  Developed APIs in Python and C++ to support internal libraries, improving software functionality and system performance. Used OpenCL, OpenGL, and EGL to enable graphical features on embedded systems. Conducted validation of Qualcomm’s internal camera APIs against the latest chipset firmware builds. Built an audio capture and playback tool for Linux-based virtual machines using the ALSA library.

• Machine Learning Engineer Intern, Kapaix Ltd Summer 2021

  Worked at a Big Data Management company handling time-series data from energy companies. Designed and trained neural network architectures to detect anomalies in large-scale data flows, focusing on amplitude and frequency patterns. Preprocessed the dataset with variable-frame histograms, applied PCA and k-means for initial analysis, then built two concurrent models — a classifier and an autoencoder using dense layers and CNNs — to compensate for limited training data. Implemented in Python with Keras, TensorFlow, and Pandas.

Education

• Illinois Institute of Technology, Master of Engineering 2021

  Coursework focused on advanced robotics (SLAM, Kalman filters, path planning), machine learning (neural networks, image recognition, data-driven control), and applied mathematics. Completed a research project in the Navigation Laboratory on lidar-based localization of autonomous vehicles in low GNSS availability environments, applying Error Correction Codes (Hamming and BCH) to solve the landmark misassociation problem and deriving a Misdetection Error Model for Probability of Hazardously Misleading Information.

• INSA Lyon, Master of Science, Mechatronics 2020

  Five-year engineering program covering advanced robotics and active controls, numerical and experimental analysis, dynamics and system control, vibrations, mechanical design, materials, and fluid/thermal mechanics. Thesis completed at the LaMCoS laboratory in collaboration with Safran Aircraft Engines, developing an algorithm to generate NURBS-based fillets between CAD volumes for turbojet blade geometry, merging CAD and FEA through isogeometric analysis.

• CPE Lyon, Bachelor of Engineering, Electronics and Computer Science 2019

  Programming — Analog and digital systems (microcontroller implementation) — Electronic architectures (VHDL design on FPGA).

Projects

• Path Finding Algorithms C++, Qt

  Real-time visualization of path-finding algorithms built with C++ and the Qt framework.

• Lidar-Localization of Autonomous Vehicle LiDAR, Localization, Matlab

  Navigation integrity and safety in low GNSS availability areas using a Velodyne Puck LiDAR sensor for landmark detection and IMU drift compensation.

• VGG vs ResNet TensorFlow, Python

  Blood cell classification comparing VGG16 and ResNet50 architectures using TensorFlow and image data generators.

• Graph SLAM Python

  Hand-coded Graph SLAM algorithm applied to the Victoria Park dataset.

• Drive Cycle and Autonomous Vehicle PID, C++

  Autonomous vehicle following a standard EPA drive cycle via PID-based longitudinal controls.

• 3-Axis SCARA Robot Simulink, Dynamics

  Kinematic and dynamic modeling of a 3-axis SCARA robot with active controls implemented in Simulink.