Background & Focus

A brief look at my path
& what I'm exploring.

I am Youssef Assis, a Machine Learning Engineer with a PhD in Computer Science.
My work bridges academic research and applied engineering, focusing on how Computer Vision and AI can help solve meaningful challenges in healthcare.

Academic Foundations

Higher Education in Morocco

I completed my undergraduate studies at FST Beni Mellal, followed by a Master's degree at INSEA Rabat. My specialization focused on Mathematical Modeling and Intelligent Systems.

This academic path provided a solid quantitative background, with coursework covering data analysis, signal processing, and initial exposure to Machine Learning (ML) and artificial intelligence methods.

I then moved to France for an internship in NLP, marking my first hands-on experience in applied research.

Early Research Experience

Natural Language Processing

During an internship at ICube / INSA Strasbourg, I contributed to the development of a question-answering system for structured PDF reports.

This work involved the use of BERT and provided practical exposure to transformer-based models and modern NLP pipelines.

PhD in Medical AI — INRIA Nancy

Building on this initial experience, I pursued a PhD in France with a focus on medical applications of machine learning. The objective was to better understand how computational methods can support clinical practice and decision-making.

In collaboration with the Tangram teamand CHRU Nancy, I worked on systems for detecting intracranial aneurysms from 3D TOF-MRA imaging data. My research explored the integration of prior knowledge into CNNs and attention-based models, with a particular focus on data-centric approaches for handling imbalanced clinical datasets.

Industry Transition

R&D at DentalMonitoring

After completing my PhD, I joined DentalMonitoring in Paris, where I work on applying computer vision and AI techniques to healthcare use cases.

In my current role, I contribute to the development and evaluation of machine learning models used in dental care workflows at DentalMonitoring. This work builds on my research background and focuses on connecting state-of-the-art methods with practical clinical applications.

Academic Service & Side Work

Peer Review and Projects

I serve as a peer reviewer for journals related to my research area. This helps me stay engaged with current work and continue learning through regular reading of scientific papers.

Alongside this, I work on small personal projects, mainly focused on building web applications and experimenting with new ideas.

Hard Skills & Technical Landscape

The languages, frameworks, and tools I use to design, train, and deploy models.

Deep Learning & AI

Designing, training, and evaluating models for 2D and 3D computer vision tasks.

PyTorchScikit-learnTransformersCNNs

Medical Imaging & AI

Handling standard volumetric formats and interacting directly with clinical visualization software.

DICOM & NIfTIMONAISimpleITKTorchIO3D Slicer

MLOps & Pipelines

Ensuring strict reproducibility, experiment tracking, and clean model deployment into production.

DockerMLflowW&BGit CI/CDDVCPoetry

Model Validation

Evaluating model safety and efficacy against strict clinical standards and regulatory frameworks.

BootstrappingFDA GuidanceNon-inferiorityMetrics

Languages & Core

Writing performant, production-ready code for both research prototyping and system integration.

PythonCJavaScriptMATLABLinux

Soft Skills & Core Principles

The methodologies and collaborative approaches that guide my work.

Data Awareness

I pay attention to data quality, bias, and imbalance, especially in sensitive domains like medical imaging.

Collaboration

I work with domain experts and engineers to align solutions with real-world constraints and needs.

Documentation

I document work clearly to support understanding, reproducibility, and team collaboration.

Complete Timeline

A chronological record of milestones, publications, and professional roles.

March, 2026

Featured in Science et Avenir

My PhD work on brain aneurysm detection was featured in Science et Avenir (p. 58).

October, 2025

Journal of Neuroradiology Publication

Our research on collaboration between AI and radiologists was accepted for publication in the Journal of Neuroradiology.

July, 2024

R&D Engineer at DentalMonitoring

Transitioned to an industry role in Paris to focus on deploying, monitoring, and evaluating predictive models used in dental care.

April, 2024

IJCARS Journal Publication

Our research on automated detection was accepted for publication in the IJCARS journal.

March, 2024

PhD Defense

Successfully defended my thesis on Intracranial Aneurysm Detection, bridging deep learning with clinical realities.

October, 2023

MICCAI STAR Award

Shared our research at MICCAI (Vancouver) and received the STAR award for our technical contribution to medical image computing.

June, 2023

MICCAI Conference Publication

Our work was accepted for publication in the MICCAI 2023 conference proceedings.