Joaquin Bogado is a computer scientist and researcher with 13 years of experience in statistics, machine learning, data analysis and time-series, adept at translating scientific models into production-ready solutions. He has led interdisciplinary work across particle physics, computer networks and information security, combining rigorous research with practical engineering. Currently, he serves as Project Coordinator at Purrfect AI and Generative AI Engineer at VRAIn, while also contributing as an invited researcher at LIFIA and operating an independent consulting practice. In open source, he has enhanced the Rucio project as a back-end developer and technical writer, focusing on CLI documentation, features and tests. He holds a PhD trajectory in computer science, ML and networking from UNLP, complemented by a postgraduate degree in security from CTU Prague. Based in La Plata, Argentina, he looks for challenging opportunities to turn data-driven insights into flexible, auditable solutions.
14 years of coding experience
3 years of employment as a software developer
PhD in Computer Science, Machine Learning/Data Management/Networking, PhD in Computer Science, Machine Learning/Data Management/Networking at Universidad Nacional de La Plata
Postgraduate Degree, Computer and Information Systems Security/Information Assurance, Postgraduate Degree, Computer and Information Systems Security/Information Assurance at Faculty of Electrical Engineering, Czech Technical University in Prague
Licenciatura en Informática, Licenciatura en Informática at Facultad de Informática within Universidad Nacional de La Plata
Contributions:203 commits, 81 PRs, 30 comments in 6 years 10 months
Contributions summary:Joaquin primarily contributed to the project by modifying documentation files and adding new features. They added and updated command-line interface (CLI) documentation, which aligns with technical writing. Additionally, the user appears to have made code changes to the system, adding and modifying functionalities and tests, which suggests some level of backend development.
The Attacker IP Prioritizer(AIP) dynamically generates resource-friendly IPv4 blocklists from Zeek network flows.
Contributions:86 commits, 13 PRs, 97 pushes in 9 months
prioritizerpythonipv4securityaddress
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