🧑🔬 AI in Science
Artificial Intelligence represents a revolution comparable to agriculture and sedentary life,
the invention of writing or even printing. Those turning points transformed how we interact with the world.
AI now affects all activities. To be honest, I am still not quite sure what intelligence is.
In practice, I think we can say that artificial intelligence is a scientific discipline that enables machines to carry out tasks based on examples rather than instructions.
With DERAISON.AI, I am committed to contributing to international scientific research through blog posts and publications for the scientific community. Since November 2024, I've been pursuing these efforts with new breadth at probabl.ai, whose members I've admired for more than 15 years, ever since that day when I wrote the words import sklearn that shaped my Data Science profession.
✒️ Blog
AI Helpers
Warith Harchaoui, Mohamed Chelali, Bachir Zerroug
AI Helpers is a suite of Python libraries (under BSD License) designed to streamline and improve artificial intelligence (AI) development. Whether you're working on machine learning, computer vision, or natural language processing (NLP), AI Helpers offers utility tools to simplify common tasks in AI-driven projects.
✒️ 💻 Tech Tips
Programming in AI
Warith Harchaoui, Mohamed Chelali, Matias Tassano and Pierre-Louis Antonsanti
The aim of this webpage is to present a basic cheat sheet for programming in Machine Learning (i.e. Statistical Learning, Pattern Recognition, Artificial Intelligence, Data Science) for tremendous applications such as in Computer Vision, Sound Processing and Natural Language Processing.
✒️ 💻 Tech Tips
Dear Teacher
Stanislas, 2021
Warith Harchaoui
Dear Professor,
On the second day of March in the year 2021, my friend Quentin and I paid you a visit in prep school Stanislas in Paris to express our gratitude on behalf of many students for imparting upon us the satisfaction mark. For almost two decades, I have made use of this punctuation, and it has made me feel as though I belong to a guild of enlightened scholars, much like yourself, who continue to teach us even today. [...]
✒️ ❤️ Inspirational Teacher
Value in Data
Think Tank 4eRévolution, 2021
Warith Harchaoui and Laurent Pantanacce
Each industrial revolution is driven by a driving force: a raw material, an energy source,
a creative technology that redefines the economy. Since the 19th century, we can list
steam, coal, oil, electricity, radio, the transistor, computers, and today artificial
intelligence (AI). This fourth industrial revolution is troubling because its commodity is
abstract: data. At the scale of humanity, this seems a more significant milestone than a
means of communication such as radio or the Internet. [...]
✒️ 🧐 White Paper
AI for Business
Rennes School of Buiness, 2021-2025
Warith Harchaoui and Laurent Pantanacce
Filling the gap between AI tech people and team leaders. This course is designed to help business leaders understand the AI business aspects and how to implement it in their organizations. Two seasoned practioners of Scientific and Corporate AI teach the basics of AI for reconciliation of science and business for the sake of company's success.
✒️ 👨🏫 Executive MBA
On Refait le Mac avec Luc Julia, le Papa de Siri 🇫🇷
Electric Dreams, 2020
Olivier Frigara, Luc Julia and Warith Harchaoui
Luc Julia is the special guest on On refait le Mac. This Frenchman, co-creator of Siri, takes a look at his baby and why Apple's voice assistant is having so much trouble growing up. This world expert in artificial intelligence questions its real impact on our future. Should we believe the tech giants who predict that it will revolutionise everything? Should we be afraid? Let's debate!
✒️ 📺 ORLM
An Introduction to Neural Networks for Statisticians 🇫🇷
Université Paris Descartes, École 42, 2020
Warith Harchaoui
From a single neuron, to a layer of neurons, then several layers, sometimes convolutional, and even several opposing neural networks, we are seeing certain aspects of the mystery of intelligence emerge through a technology that is changing the game in almost every area of our contemporary world.
✒️ 🧑🏫 Conference
Favorite Books in Artificial Intelligence
Warith Harchaoui
In the rapidly advancing field of Artificial Intelligence, it is common to observe high volume and pace of both scientific and non-scientific publications. It is overwhelming and I am often asked how to do.
It is in this context that I present a list of books that I find particularly noteworthy, along with some comments, for those readers who are eager to engage in the exciting AI adventure.
✒️ 📚 Books
🗞️ Peer-reviewed Publications
Optimal transport-based machine learning to match specific patterns: application to the detection of molecular regulation patterns in omics data
Journal of the Royal Statistical Society (RSS), 2024
Thi Thanh Yen Nguyen, Warith Harchaoui, Lucile Mégret, Cloe Mendoza, Olivier Bouaziz, Christian Neri and Antoine Chambaz
We have created methods for geometrically connecting two piles of points, which is useful when these points are supposed to match. Our application example concerns the study of messenger RNA in genetics to understand Huntington's disease.
🗞️ 🧬 Paper
Generalised Mutual Information for Discriminative Clustering
Neural Information Processing Systems (NEURIPS), 2023
Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Warith Harchaoui, Mickaël Leclercq, Arnaud Droit and Frederic Precioso
Clustering is the process of making groups among objects: similar within a group, dissimilar between two groups. The human mind naturally likes to form groups when it comes to customers, genes, fruits, animals and so on. The GEMINI project exploits artificial neural networks in a novel way for this large-scale task.
La conférence NEURIPS est la meilleure du monde (ou 2ème meilleure) en intelligence artificielle d'après Google Scholar.
🗞️ ♊️ Paper
Learning Representations using Neural Networks and Optimal Transport 🇫🇷🇬🇧
Ph.D. in Applied Mathematics, 2020
Warith Harchaoui
(supervised by Pr. Charles Bouveyron and Dr. Stéphane Raux)
From 2016 to 2020, this Ph.D. work focused on three key areas:
- Clustering: grouping large-scale data in number and dimension ;
- Importance of data features: identifying representative and discriminating features in data without the need for manual labels ;
- Confidence level estimation in automated decisions: creating statistical methods to assess the reliability of automated decisions, which is crucial in industry, security and healthcare.
🗞️ 🎓 Ph.D. Defense