Career Profile
With more than two years of experience of deploying machine learning models into production, my experience in embedded software development makes me a particular good fit for machine learning applications that require highly optimized runtimes.
Experiences
Development and optimisation of real-time on device speech recognition libraries.
Development of machine learning solutions for lung cancer detection on CT scans. - Research and development of a medical data generation pipeline using GANs - Nodule detection and segmentation with DL models (Unet 3D, Retina Unet) - Building a cloud solution for inference integrated with ITK-SNAP (visualisation tool)
| Team: Power sytems, Cognitive system Lab |
| Internship supervisor: Jean-Armand Broyelle |
Design and development of a massaive data acquisition pipeline on Power9 servers.
- Integration of an FPGA accelerator with CAPI
- Integration of Nvidia GPU
- Study and development of Proof Of Concepts integrating FPGA and GPU with optimized data transferts for clients
| Team: Power sytems, Cognitive system Lab |
| Internship supervisor : Jean-Armand Broyelle and Bruno Mesnet |
Development of hardware accelerators (FPGA) for Deep Learning algorithms.
- Development of RTL kernels (VHDL - Vivado and SDAccel)
- VHDL components verification with GHDL and GTKwave using UVVM
- OpenCL programming
- Code generator development to support multiple networks architecture acceleration (Python and TCL)
| Team: Big Data & Cybersecurity department (Extreme Big Data team - Hardware acceleration) |
| Internship Supervisor: Alban Bourge |
Projects
Here are some projects I made during my academic path.