Computer Vision Engineer

• Oct 2023 - Present

Computer Vision Engineer

• Jan 2023 - Sep 2023

• Detected a person pose using sparse point cloud data by developing a new data-pipeline for the V2V-Posenet model and training it.• Streamlined development and deployment processes by developing and optimizing Docker images.

Project Lead

• Jan 2022 - Aug 2022

• Led successful projects which strengthened the clients trust and increased the projects contract. • Broke down projects into tasks, planned schedules and led a team of engineers in an agile environment. • Interacted between Tunisian and Japanese teams on a weekly basis to communicate progress. • Sped up the projects delivery process by developing automated CI/CD pipelines using Jenkins. • Led successful projects which strengthened the clients trust and increased the projects contract. • Broke down projects into tasks, planned schedules and led a team of engineers in an agile environment. • Interacted between Tunisian and Japanese teams on a weekly basis to communicate progress. • Sped up the projects delivery process by developing automated CI/CD pipelines using Jenkins.

Computer Vision Engineer

• Sep 2021 - Dec 2021

• Registered a 3D point cloud scene of a hand moving 3D sensor using Open3D and a custom ICP algorithm. • Assisted Rutilea’s client during a 3 days exhibition and optimized the 3D point cloud registration algorithm’s time execution by 15 times, which made it possible to make quick onsite demos. • Developed an algorithm based on research papers to segment 3D low resolution point cloud. • Registered a 3D point cloud scene of a hand moving 3D sensor using Open3D and a custom ICP algorithm. • Assisted Rutilea’s client during a 3 days exhibition and optimized the 3D point cloud registration algorithm’s time execution by 15 times, which made it possible to make quick onsite demos. • Developed an algorithm based on research papers to segment 3D low resolution point cloud.

AI Instructor

• Aug 2019 - Jul 2021

• Animated workshops about python, machine Learning and deep-learning. • Assisted students during their projects’ development. • Animated workshops about python, machine Learning and deep-learning. • Assisted students during their projects’ development.

Data Science Intern

• Nov 2020 - Apr 2021

• Analyzed, cleaned and transformed over 116 million rows of GPS data into a transport timetable CSV file. • Developed an algorithm that rectifies the transport means itineraries to recover over 95% of the data. • Developed a dynamic graph as well as its search algorithm (Uniform-Cost) to solve the earliest arrival and the minimum number of transfer problems within 55 milliseconds on average. • Analyzed, cleaned and transformed over 116 million rows of GPS data into a transport timetable CSV file. • Developed an algorithm that rectifies the transport means itineraries to recover over 95% of the data. • Developed a dynamic graph as well as its search algorithm (Uniform-Cost) to solve the earliest arrival and the minimum number of transfer problems within 55 milliseconds on average.

Data Science Intern

• Jun 2019 - Jul 2019

• Investigated research papers and collaborated with Factory’s team to propose a solution for detecting babies’ cries. • Extracted and transformed features from the baby cries signal such as zero crossing, signal frequency and bandwidth and traained tree-based and regression models to detect if the signal is a baby cry or not with 83% accuracy. • Applyed Stratified Kfold startegy as well as stacking and ensembling techniques to improve the model's accuracy and reduce bias. • Investigated research papers and collaborated with Factory’s team to propose a solution for detecting babies’ cries. • Extracted and transformed features from the baby cries signal such as zero crossing, signal frequency and bandwidth and traained tree-based and regression models to detect if the signal is a baby cry or not with 83% accuracy. • Applyed Stratified Kfold startegy as well as stacking and ensembling techniques to improve the model's accuracy and reduce bias.