Looking for information about me ? Here is what you need to know :
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My background : I am a statistician and machine learning professional by education, with a background in mathematics and research.
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My passion : solving data science problems from theory to practice - and vice versa ! - using technologies such as Python, TensorFlow, Keras, R, Shiny, SQL, AWS, Docker, Kubernetes etc., in fields such as the manufacturing industry, energy, the medical sector, agronomy, etc. I am used to develop new statistical & machine learning methods, or to apply state of the art techniques from statistics, machine and deep learning (e.g. Bayesian & Frequentist approaches, Kernel methods, Ensemble methods, Deep-NN, Conv-NN, etc.).
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What I have achieved so far :
- I developed the Maintenance Factory SaaS suite, for one of my companies named CYM, which performs real-time analyses using machine, sensor or telemetric data and aims at reducing costs and increasing production within the manufacturing intelligence and predictive maintenance framework.
- I developed the Deep vision for Diabetic Retinopathy Detection (3DR) SaaS approach, based on deep convolutional neural networks, which allows automated referable diabetic retinopathy detection. This approach has been benchmarked with another approach cleared by the FDA in the USA and allows ; 1) fast, 2) massive and 3) regular screening and follow-up of patients. The 3DR SaaS is currently used by the University Health Centre of Dakar
- I developed the CRAN package KRMM for solving "Reproducing Kernel Hilbert Space" (RKHS) regression, used by teams of INRA and CIRAD for genomic prediction and analyses, which competes with current implementations of SVM, random forests and neural networks within the omic framework.
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What I am doing currently : I lead an amazing team of data scientists at OKP4 where we develop many AI based services, for a decentralized protocol, which will allow data sharing and new knowledge creation
