Guest Researcher at Max Planck Institute for Dynamics and Selforganization
Göttingen, Lower Saxony, Germany
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Summary
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Abdullah Makkeh is a computer scientist and mathematician with a decade of experience translating information theory and high-performance computing into practical, interpretable AI systems. As a Guest Researcher and former Senior Scientist in Göttingen, he has led interdisciplinary teams to improve pattern-recognition models, develop autonomous learning paradigms, and publish in top venues such as PNAS and NeurIPS. His technical toolkit centers on Python and PyTorch, and he has advanced novel metrics for disentanglement, stopping criteria for LLMs, and autonomy evaluation in reinforcement settings. Abdullah’s work bridges theory and open-source practice—he has developed analysis tools for time series and neural data and fostered collaborations with industry partners like Honda Research Institute Europe. Fluent in English and German, he combines project leadership with hands-on research, having supervised students from BSc to PhD level. An underappreciated strength is his focus on measurable, performance-driven gains (e.g., a documented 10% boost in pattern recognition models) that make research directly actionable.
10 years of coding experience
7 years of employment as a software developer
MSc Mathematics, MSc Mathematics at Lebanese University - Faculty of Sciences
PhD Mathematics and Computer Science, PhD Mathematics and Computer Science at University of Tartu
A differentiable measure of shared mutual information via overlapping exclusions in event (measure) spaces for discrete and continuous variables
Contributions:5 PRs, 31 pushes, 2 branches in 3 years 11 months
differentiablecontinuousdiscretespacesmeasure
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Abdullah Makkeh - Guest Researcher at Max Planck Institute for Dynamics and Selforganization