Akram Zaytar is a Senior Research Scientist at Microsoft AI for Good Lab with 11 years of experience applying GeoAI, deep learning, and probabilistic ML to climate and geospatial problems. He previously led research at IBM on scalable climate informatics, building hazard impact estimators, seasonal crop maps, and post-processing models for sub-seasonal forecasts. His work bridges academic rigor (PhD in AI and Climate Science) with production-facing solutions—weakly supervised fraud detection and edge-enabled farm twinning—demonstrating both methodological breadth and applied impact. Based in Tangier, he combines expertise in computer vision, explainable ML, and Bayesian methods to turn satellite imagery and forecasts into actionable risk insights. An interest in interpretable features for extremes and operational forecast calibration sets him apart from typical ML practitioners.
11 years of coding experience
1 year of employment as a software developer
Master's degree, Computer Systems and Networking, Master's degree, Computer Systems and Networking at Faculty of Science and Technology Tangier
Bachelor in Applied Mathematics and Computer Science, Mathematics and Computer Science, Bachelor in Applied Mathematics and Computer Science, Mathematics and Computer Science at Université Abdelmalek Essaâdi
English, Arabic, French
Stackoverflow
Stats
23reputation
3kreached
1answer
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Github Skills (74)
github10
deep-learning10
fastai10
lstm10
git10
sgd10
artificial-intelligence10
tensorflow10
backpropagation10
machine-learning10
keras10
scikit-learn10
python9
federated-learning9
jupyter-notebook9
Programming languages (5)
TypeScriptJupyter NotebookVim ScriptRich Text FormatPython
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