I am a Data Scientist with a Ph.D. in Physics, specializing in machine learning, data analysis, and scientific computing. My experience spans building robust models for complex, noisy datasets and applying model distillation techniques to compress and accelerate deep learning workflows. I have strong skills in Python, SQL, and modern machine learning frameworks, and am experienced in developing end-to-end machine learning systems with automated workflows, monitoring, and model management to ensure reliable deployment in production environments.
Currently based in Geneva, Switzerland, I am open to remote opportunities. My work includes leading international research teams, applying decision tree-based models for rare event detection, and tailoring machine learning algorithms for low-latency applications including real-time environments and FPGA-based systems. I am passionate about creating data-driven solutions and mentoring students in applied machine learning and data analysis.
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