Nour Karoui

With expertise in computer vision and deep learning, I conduct research focused on human-computer interaction, particularly in medical environments. My experience includes developing solutions using neural networks for tasks such as video anonymization and image segmentation. I combine a strong technical foundation with a keen focus on domain-specific needs.

Fixed-term contract: Researcher Ph.D.

Intelligent Systems and Robotics Institute (ISIR) | Paris, France

Research focus on applying Neural Networks and Computer Vision to touchless interactions in minimally invasive surgeries.

Internship: AI Engineer in Surgery

Karl Storz Endoskope | Tuttlingen, Germany Research and development of a system for automating the anonymization of endoscopic (videos)

data using supervised learning.

Assessing data quality impact of supervised learning model accuracy including:

• Data labeling for supervised learning.
• Image data pre-processing (sampling, data augmentation).
• Training, optimization and deployment of supervised learning models.
• Evaluation of the fairness of results and implementation of confusion matrices.

Internship: Mechanical Engineer - Orthopedics Department

Institut Mutualiste Montsouris Hospital | Paris, France Modeling the kinematic alignment and studying the mechanical constraints of total knee prostheses.

Ph.D. in Human Computer Interaction and Machine Learning

Sorbonne University | Paris, France Designing and developing interfaces for minimally invasive procedures using Deep Learning techniques.

October 2023 – Expected graduation: 2026

Master's degree in electronics and automation: Health Engineering - Medical Device Technologies

Sorbonne University | Paris, France – With Highest Honors September 2021 – September 2023

Computer science: Python programming, Image processing, Artificial Intelligence.

Electronics: Digital signal processing, Sensors for embedded systems, Automation.

Biotech: Medical Imaging (MRI, EEG and Ultrasound), Cardiovascular Technologies, Biomechanics, Locomotor Devices.

F U R T H E R E D U C A T I O N :

Summer School in Machine Learning:

University of Oxford, AI for Global Goals | Oxford, United Kingdom

MLx Fundamentals: May 2024

• Strengthening foundational ML and DL knowledge, focusing on mathematics, statistical modeling, and optimization.
• Exploring factorization techniques and practical ML applications.
• Developing coding skills, emphasizing algorithms and analysis.

MLx Representation Learning: July 2024

• Exploring advanced representation learning and generative AI.
• Gaining practical experience in computer vision and NLP techniques.
• Expanding expertise in neural network architectures and activation functions.

MLx Health & Bio: July 2024

• Investigating ML and DL applications in healthcare and biomedical sciences.
• Studying statistical/probabilistic ML and advanced representation learning.
• Acquiring knowledge of wearable devices for human-computer interaction.