Vincenzo Coia is a research-focused statistician and senior applied scientist with 11 years’ experience building probabilistic models for water resources, geohazards, and complex environmental systems. He blends statistical theory, machine learning, and physical domain knowledge to support decisions under uncertainty, with particular strength in extreme-event modeling and dependence-aware risk assessment. Vincenzo develops open-source R tools and reproducible workflows that reframe methods to be generalizable across projects, and he has contributed to educational resources like the STAT545 course site. Currently a Research Fellow in Milan working on satellite-informed flood modeling, he continues part-time consulting for industry clients to translate analyses into actionable, decision-ready deliverables. His background spans academia and industry—PhD in Statistics, teaching at UBC, and applied roles at BGC Engineering—giving him a rare mix of pedagogical clarity and field-tested rigor. An understated but consistent theme is his focus on modeling assumptions and how uncertainty propagates under real project constraints, not just algorithmic performance.
11 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Statistics, Doctor of Philosophy (Ph.D.), Statistics at The University of British Columbia
Master of Science (MSc), Mathematical Statistics and Probability, Master of Science (MSc), Mathematical Statistics and Probability at Brock University
Main repository for STAT 545 @ University of British Columbia, a course in data wrangling, exploration, and analysis with R.
Role in this project:
Technical Writer
Contributions:125 commits, 3 PRs, 99 pushes in 2 years 1 month
Contributions summary:Vincenzo's contributions primarily involved modifying HTML files, specifically those related to the course website's content. These changes included updating text, adding links, and adjusting layout elements. The edits focused on the syllabus and lecture notes, ensuring the information was current and accessible to students.
Draw powerful insights using distributions with this R package.
Contributions:2 releases, 14 reviews, 390 commits in 3 years 2 months
r-packagedistributionsdrawrstatsinsights
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