Chafic Akar
Research And Development Engineer at BMW Group
Munich, Bavaria, Germany
Summary
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Top SchoolChafic Akar is an R&D engineer based in Munich with five years of experience building production-grade AI and simulation systems for industry leaders like BMW, NVIDIA and Microsoft. He led the world’s largest synthetic image generation pipeline for computer vision applications and champions NoCodeAI tools that bring end-to-end ML pipelines—data preprocessing, training and evaluation—to non-experts. His background spans applied research (PhD in Computer Vision in progress), swarm intelligence and optimization, plus hands-on backend and full-stack engineering from scalable .NET architectures to real-time NLP services. Comfortable leading multinational teams and mentoring students, he combines academic rigor with product-focused delivery and a knack for turning complex simulations into usable industrial solutions. An unexpected strength: a creative media background that informs his practical expertise in visual data, 3D modeling and realistic synthetic data generation.
5 years of coding experience
4 years of employment as a software developer
Master of Engineering - MEng, Software & Networks, 94.3, Master of Engineering - MEng, Software & Networks, 94.3 at Université Antonine - UADoctor of Philosophy - PhD, Applied Computer Vision, Doctor of Philosophy - PhD, Applied Computer Vision at Université Bourgogne Franche-ComtéHigh School Diploma, GS - General Science, Rate: Very Good, High School Diploma, GS - General Science, Rate: Very Good at Collège du Christ-Roi
French, English, German, Arabic
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (26)
image-synthesis10
tensorboard10
darknet9
rest-api9
docker8
object-detection8
automation8
rest8
monitoring8
yolov48
resnet7
dali7
deep-learning7
neural-network6
no-code6
Programming languages (3)
Github contributions (5)
BMW-InnovationLab/SORDI-Data-Pipeline-Reader
Nov 2022 - Nov 2022
SORDI dataset has per frame annotation file in json format. Following tools create a COCO style annotation out of it. Thus the SORDI data can be easily fed into COCO style training pipelines.
Contributions:5 commits in 12 days
cocodatasetobject-detectionsordicomputer-vision
chaficii/home_mortage_app
May 2022 - May 2022
Contributions:2 PRs, 3 pushes, 2 branches in 1 day
distributed-application-developmentapidotnetpersistencysoftware-architecture
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