Luca Anzalone
Field Manager at Open Fiber
Palermo, Sicily, Italy
Summary
👤
Senior🎓
Top SchoolLuca Anzalone is a Field Manager and licensed architect based in Palermo with nine years of experience bridging architectural design, telecoms engineering and field operations. Trained with a summa-cum-laude Master’s in Architecture and a BIM Management diploma, he combines 2D/3D design skills (AutoCAD, Revit, 3ds Max) with hands-on delivery of fiber-optic networks, backhaul design, permits and electromagnetic impact assessments. At Open Fiber he leads field activities for large infrastructure deployments, after technical roles designing telecom networks and energy acquisitions. Unusually for an architect, he contributes to ML-focused open-source work—implementing a CARLA simulator environment for reinforcement learning—illustrating a practical cross-disciplinary interest in data-driven systems. He holds VAT registration and a strong track record of turning complex regulatory and engineering constraints into executable site programs.
9 years of coding experience
Laurea Magistrale LM in Architettura e dell'Ingegneria edile, Architettura, 110 e lode, Laurea Magistrale LM in Architettura e dell'Ingegneria edile, Architettura, 110 e lode at Università degli Studi di Palermo
Italian, English, French
Stackoverflow
719reputation
18kreached
41answers
2questions
Github Skills (23)
simulation10
environmental10
dev-environment10
python10
simulator10
simulations10
reinforcement-learning10
enviroment10
tensorflow10
deep-reinforcement-learning10
environ10
carla10
numpy9
machine-learning9
pygame9
Programming languages (7)
Github contributions (5)
tensorforce/tensorforce
Apr 2020 - Apr 2020
Tensorforce: a TensorFlow library for applied reinforcement learning
Role in this project:
ML Engineer
ML EngineerContributions:5 commits, 1 PR, 34 comments in 8 days
Contributions summary:Luca contributed to the development of a CARLA environment wrapper for reinforcement learning applications. They implemented the `CARLAEnvironment` class, which provides an interface for interacting with the CARLA simulator. The user also made several improvements, including fixing import issues, adding dependencies, and updating examples, demonstrating a focus on environment setup and integration. Their work involved defining states, actions, reward functions, and sensor specifications to facilitate reinforcement learning experiments within the CARLA simulator.
tensorflow-librarytensorforcereinforcement-learningdeep-reinforcement-learningmachine-learning
Luca96/reinforce-lib
May 2020 - Oct 2022
Contributions:74 commits, 4 pushes in 2 years 4 months
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