Kevin Frick is a PhD student and graduate teaching assistant at the Toulouse School of Economics who blends rigorous econometric research in labor and education with a strong computational background from a summa-cum-laude MSc in Computer Engineering. He applies empirical industrial-organization tools and machine learning to structural econometrics and policy evaluation, and has collaborated with institutions like J‑PAL Europe and the French Ministry of Labor on NLP-based labor market measurement. With ten years of experience spanning research, teaching, and software engineering, Kevin has practical systems skills—evidenced by contributions to the GemRB open-source engine where he implemented a Theta*-based pathfinder and performance fixes. He brings classroom experience across R, econometrics, and randomized evaluation courses, plus hands-on robotics and SLAM work from an Erasmus traineeship, reflecting a rare mix of theoretical econometrics and production-grade engineering.
10 years of coding experience
2 years of employment as a software developer
Bachelor's degree, Computer Engineering, Summa cum laude, Bachelor's degree, Computer Engineering, Summa cum laude at Alma Mater Studiorum - Università di Bologna
Exchange program, Département d'Économie, Exchange program, Département d'Économie at Ecole normale supérieure
UPC Universitat Politècnica de Catalunya
Master's degree, Computer Engineering, Summa cum laude, Master's degree, Computer Engineering, Summa cum laude at Alma Mater Studiorum – Università di Bologna
Doctor of Philosophy - PhD, Economics, Doctor of Philosophy - PhD, Economics at Toulouse School of Economics
GemRB is a portable open-source implementation of Bioware’s Infinity Engine.
Role in this project:
Back-end Developer
Contributions:2 reviews, 22 commits, 5 PRs in 2 months
Contributions summary:Kevin primarily focused on improving the pathfinding algorithms and related functionalities within the GemRB engine. Their contributions include implementing a new Theta* based pathfinder, addressing actor movement issues, and optimizing pathfinding performance. They fixed memory leaks, corrected edge case behaviors related to pathfinding, and implemented features like adjusting pathfinding to prevent actors from getting stuck. The user also addressed issues around actors blocking searchmap and the overall target reachability.
Contributions:154 pushes, 2 branches in 1 year 3 months
gamegamedevgame-developmentgame-enginebackground
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