Clément Morin

Train State-of-the-Art AI models with optimisation
of hyperparameters and real-time usage for
efficient integration in highly demanding
AI-enabled medical device
Expertise in general computer vision, data
analysis, and machine learning/deep learning
algorithms deployment and optimization
Develop, maintain and upgrade AI-enabled
medical software devices for real-time edge
computing

Proposal, conception and production launch of
deep-learning algorithms catered to different
issues:
Images – segmentation and classification by CNN
and Transformers
Time-series – prediction and maintenance
Data mining and data cleaning – implementation
of a database and of a new BI tool, anomaly
detection, software optimisation

Developed segmentation and classification AI models for teeth characterisation, including hyperparameter optimization for real-time usage. Created database systems to support AI-enabled multilabel/multiclass segmentation for a medical device.

Built and optimized AI-enabled software for CBCT image classification aimed at early osteoporosis detection. Collaborated with clinicians to evaluate medical-added value and implemented image-processing algorithms for efficient real-time edge computing.

Grade: 4

Activities and societies: Student

Master’s degree (double diploma) in Artificial Intelligence. Covered proposal, conception, and production launch of deep-learning algorithms tailored to different medical and health engineering issues.

Grade: 4.0

Activities and societies: Student

Engineering school studies focused on medical and health engineering applications of deep learning. Worked on image segmentation and classification using CNNs and Transformers, and on related deep-learning approaches for health problems.

Preparatory classes with a mathematics major and physics & chemistry focus. Included training in time-series prediction and maintenance, data mining and data cleaning, and implementation of a database/BI tool and anomaly detection.