Quentin Labernia, Developer in Vichy, France
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Quentin Labernia

Verified Expert  in Engineering

Statistics Developer

Location
Vichy, France
Toptal Member Since
November 7, 2022

Quentin graduated from two top universities in France and Japan. He specialized in artificial intelligence, machine learning (ML), and data science. To him, a deep understanding of your field of application and business processes is the key to success. Quentin possesses a strong sense of commitment. The core value he wants to bring to projects is confidence, the conviction that you can achieve even more with your services, products, and business.

LinuxWindowsComputer VisionAgileArtificial Intelligence (AI)Machine LearningPythonData MiningWeb DevelopmentGoC++Node.jsDeep LearningPyTorchTensorFlow

Portfolio

Corpy&Co
Machine Learning, Artificial Intelligence (AI), Computer Vision...
Tohoku University
Artificial Intelligence (AI), Applied Mathematics, Data Science, Data Inference

Experience

Statistics - 10 yearsPython - 10 yearsData Science - 8 yearsArtificial Intelligence (AI) - 7 yearsMachine Learning - 7 yearsComputer Vision - 6 yearsCloud - 5 yearsGo - 4 years

Availability

Part-time

Preferred Environment

Linux, Windows, Amazon Web Services (AWS), Azure, Python, Go

The most amazing...

...software I’ve developed was for a medical device that helps doctors find brain aneurysms.

Work Experience

Senior AI Researcher, Team Manager, and System Administrator

2019 - PRESENT
Corpy&Co
  • Developed cloud software as a medical device and managed the project from scratch. Based on a state-of-the-art machine learning model, the software can assist radiologists in diagnosing brain aneurysms, even the smallest ones.
  • Participated in elaborating Japanese national guidelines to define good practices for AI usage. These were adopted as part of a framework managed by the Japanese Advanced Institute of Science and Technology.
  • Designed and installed a complete data infrastructure used by all employees for R&D and production deployment, including networking, servers, data clusters, continuous integration, and a testing platform.
  • Built a fluid simulation pipeline that can extract blood vessels from MRI scans, create the mesh, and run computational fluid dynamics simulations to obtain stress, velocity, and pressure inside the vessels.
Technologies: Machine Learning, Artificial Intelligence (AI), Computer Vision, Medical Imaging, Linux, Azure, Cloud, Node.js, Microservices Architecture, Deep Learning, Physics Simulations, Simulations, Datasets, PyTorch, Text Generation, Fine-tuning, Data Inference, DeepSpeed, Back-end, Object Detection, Object Tracking, Machine Learning Operations (MLOps)

Research and Teaching Assistant

2017 - 2019
Tohoku University
  • Developed a computer vision system for robots to find survivors during earthquake recovery operations.
  • Published a paper at a top conference workshop on large-scale taxonomy problems using machine learning (ML) and data science algorithms. Used by eCommerce websites to retrieve information in large tree structures.
  • Taught discrete mathematics and algorithms to undergraduates.
Technologies: Artificial Intelligence (AI), Applied Mathematics, Data Science, Data Inference

Explanable AI Software as a Service

https://confide.tech
Developed software to support companies in building trustable AI models and understanding their data. Created the conception and development of the software at various levels. Set up initial research, proof of concept (PoC), quality control, infrastructure and maintenance, and the overall service architecture.

Behavioral Data Analysis Algorithm

https://hal.archives-ouvertes.fr/hal-01551395/document
Created a method for discovering duplicates in behavioral data. Used to match different video game users to the same player. Led as the main author of the article. Published at the 2017 international conference on industrial engineering and other applications of applied intelligent systems.

Image Augmentation for Automobile Part Manufacturing Company

A research project in collaboration with one of Japan's biggest car manufacturing companies. The project aims to apply generative models to perform data augmentation on pictures of car parts in a controlled fashion.

AI Cloud Software as Medical Device

An AI cloud software that aims at detecting cerebral aneurysms. The aneurysms are found using an object detection algorithm inside MRI and CT scans. The algorithm achieves a very high recall rate, i.e., virtually no aneurysms are missed.

I was the project manager and team leader, participating in all phases of research and development of the software and making sure regulatory constraints were properly considered. I managed to upgrade the process inside the company to comply with ISO international standards and good practices.

Languages

Python, Go, C++

Libraries/APIs

Node.js, PyTorch, TensorFlow

Paradigms

Data Science, Microservices Architecture, Agile

Platforms

Linux, Windows, Azure, Arduino

Other

Applied Mathematics, Computer Vision, Artificial Intelligence (AI), Machine Learning, Statistics, Data Mining, Deep Learning, Datasets, Fine-tuning, Data Inference, Generative Adversarial Networks (GANs), Back-end, Object Detection, Object Tracking, Machine Learning Operations (MLOps), Medical Imaging, Web Development, Cloud, Data Management, Physics Simulations, Simulations, Text Generation, DeepSpeed

2016 - 2019

Master's Degree in Information Technology

Tohoku University - Sendai, Japan

2012 - 2018

Master's Degree in Computer Science

Institut National des Sciences Appliquées de Lyon - Lyon, France

AUGUST 2022 - PRESENT

Data Management for Clinical Research

Coursera