Fernando Crema is a Research Assistant and PhD candidate at KU Leuven with 11 years of hands-on experience applying Deep Learning and Automated Machine Learning to clinical and multimodal health data, with a special focus on neuropsychiatric syndromes. He has led data science teams and built scalable anomaly-detection systems using distance-based approaches that exploit triangular inequality for high-throughput network behavior analysis. Prior roles across industry and academia—from Domusware to Predictvia and teaching positions in Venezuela—reflect a strong foundation in probability, graph theory, and practical ML engineering. Fernando blends rigorous research (STADIUS/UZ Leuven) with product-minded deployments, routinely translating advanced methods into deployable solutions. A sabermetrics and baseball enthusiast who once met Trevor Hastie, he brings both statistical curiosity and cross-cultural academic training (summa cum laude in Data Science from Sapienza) to complex healthcare problems.
11 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Engineering Science, Doctor of Philosophy - PhD, Engineering Science at KU Leuven
Internship in the Center for Data Science, Data Science, Internship in the Center for Data Science, Data Science at New York University
Bachelor of Science (BS), Computer Science, 17.01/20, Bachelor of Science (BS), Computer Science, 17.01/20 at Santiago de León de Caracas
Laurea Magistrale in Data Science, 110 e Lode / Summa cum laude, Laurea Magistrale in Data Science, 110 e Lode / Summa cum laude at Sapienza Università di Roma
Professional Courses, Data Science, 10/10, Professional Courses, Data Science, 10/10 at University of Buenos Aires
Licenciado, Computer Science, 18/20 Magna Cum Laude, Licenciado, Computer Science, 18/20 Magna Cum Laude at Universidad Central de Venezuela
Contributions:8 pushes, 1 branch, 1 issue in 3 years 10 months
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