Summary
David Porta is an associate professor and data scientist with over 15 years in academia and nine years of professional experience applying theoretical physics and advanced mathematics to real-world data challenges. He blends deep expertise in nonlinear dynamics and statistical physics with practical machine learning, deep learning, and data-mining techniques to build predictive and descriptive models for scientific, industrial, and financial problems. As a researcher and educator he has led multidisciplinary projects, published in high-impact journals, and taught courses from Quantum Mechanics to Data Science, emphasizing problem-solving with computational tools. He has hands-on experience in muon tomography and cosmic-ray simulation for volcanology, and has applied his analytical skills to humanitarian data projects for UNICEF-LACRO. Colocated in Cartagena, Colombia, he combines rigorous theoretical training (PhD in Theoretical and Mathematical Physics) with a demonstrated ability to translate complex analyses into actionable insights and clear reports for stakeholders.
8 years of coding experience
2 years of employment as a software developer
Licenciatura, Theoretical and Mathematical Physics, Licenciatura, Theoretical and Mathematical Physics at Universidad del Zulia
Doctor en Física Fundamental, Theoretical and Mathematical Physics, Doctor en Física Fundamental, Theoretical and Mathematical Physics at Universidad de los Andes (VE)
Spanish, English