Julien Bardagi Email & Phone Number

Eindhoven, North Brabant, Netherlands

Eindhoven Area, Netherlands

Upon arriving at MCA's office, I was introduced to an internal project of their own.The project consisted of a web platform for business managers to handle and manage consultants, this involved features such as retrieving information about a consultant (their resume) or send new job positions to the relevant consultants.I had to understand the project from a higher-level point of view before being able to actually work on it and implement new features.I was involved with the backend being developed using AWS Lambdas (implemented using Python) and the frontend as a web interface developed using React in TypeScript (JavaScript superset).The source code is hosted on a private Git repository, project management and issue assignment is handled using GitLab.Based on my responsibilities, my goal was to implement API endpoint controllers to fetch data from the back-end and serve them to the front-end, this is done using Lambdas, and abiding by RESTful principles.I've implemented the first actual rest API call of the project, using React for the front-end and a sample Lambda on the back-end.Following this: more REST API methods were implemented using Lambdas to enable CRUD operations on various business objects, triggering SQL requests to fetch data.I kept providing Python tests scripts with Lambdas to test their related http endpoint.Tools involved: AWS web console, Git, Emacs, Python, SQL, React TypeScript

Région De Marseille, France

Kast® is a video recording and broadcasting solution for courses and conferences alike.It has an integrated Pan-Tilt-Zoom camera filming the speaker, as well as a display input to capture its computer Powerpoint/Keynote presentation, it also captures audio through a jack line and/or microphone input. The solution is provided with a tablet application (Android and iOS) to remotely control the system and be provided with live video feedback.I was working within a team of up to 4 software developers and engineers, we worked as a SCRUM team following Agile methodology, having daily meetings and using ZenHub: a project management tool integrated with GitHub.I was in charge of the multimedia processing part on the backend, which involved video composing, video incoding and video streaming to different outputs, this was mainly handled using gstreamer in C.I worked within a team of developers and engineers, cooperated with them and agreed on the best course of action when it came to interfacing our different parts and layers of the product.Working on a system with limited resources proved challenging, as I had to find workarounds to reduce computational overload, such as using hardware accelerated implementations of video encoders, avoiding multiple color-space conversion and use native Android graphics capabilities for video composing (OpenGL ES).I also learned and used a significant amount of tools and technologies throughout each iteration of the product, ranging from web frameworks (with Django in Python) to multimedia processing libraries (especially gstreamer).Technologies involved: Cerbero, gstreamer, glib, C, adb, OpenGL ES, Buildroot, git, bash, JavaScript, ffmpeg, Python, Django, nginx, OpenCL.

Marseille Area, France

SCIRENA was a research project financed by Veolia and the regional Water Agency (“Agence de l’eau”).I was responsible of designing and implementing a fish detection, tracking and species-recognition system to use on videos filmed in the Mediterranean Sea.This required me to get up to date with computer vision and image analysis methods, I did so by checking various scientific publications to catch up on the state of the art in terms of real-time object detection and image segmentation.I Delivered a prototype developed in C++, using OpenCV, implementing the following features:- A motion-based object detector capable of cancelling camera panning and tilting (ie: non-static cameras) to some extent.- An additional object detector using OpenCL to highlight sparsely disposed objects on an homogeneous background (fishes).- A basic object classifier (from OpenCV) to label detected fishes depending on their species.I also delivered a report that I kept up to date as I was searching for solutions and trying new methods and algorithms, citing all the relevant source material and references as well.I learned OpenCL for device-agnostic hardware acceleration of some computation, as well as dealing with scientific publications regarding computer vision and image analysis, implemented some methods and tried them out.Tools involved: C++, OpenCV, OpenCL, git

Lam (Astrophysic Laboratory Of Marseille) , France

My mission consists primarily in developing scripts to seek and refine information in astrophysical data, such as 2D galactic maps and spectrum data cubes.Both the nature of those input data and the information to be extracted lead to the use various algorithms based on 2D image analysis methods, combined with 1D data analysis (in the case of spectrum analysis), the ability to detect some patterns in the images is the key.Methods and ways to proceed are discussed with astrophysicists in order to best fit their needs.The work is done in Python, using libraries like Astropy (Astrophysical data handling), scikit-image (Image analysis) and scikit-learn (Machine Learning).

Région De Marseille, France

Design and development of an image analysis system performing object and person detection and recognition on videos (in C++ using OpenCV).

Région De Marseille, France

Implementation of additional features in a Java/JEE project (Struts framework and Sencha Ext JS framework).Deployment of a showcase site powered by Drupal 7.

Engineer In Computer Science, Networks And Multimedia, Computer Software Engineering, Graduated

Dut Src, Computer Science, Graduated