Simone Parisi
Business Analyst - Consulente Agrometeo at DiSAA Università degli Studi di Milano
Milan, Lombardy, Italy
Summary
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Senior🎓
Top SchoolSimone Parisi is a data scientist and business analyst specializing in agrometeorology and Agri 4.0 solutions, with over a decade of experience bridging meteorological science and applied data engineering. Based in Milan, he leads technical-scientific projects that combine remote and proximal sensing, GIS, geostatistics, and IoT configuration to deliver decision-support systems for agricultural risk and damage assessment. He codes in R and Python to develop raster and vector analysis algorithms and has applied his skills to solar irradiance analysis for photovoltaic systems. As an Agrometeorologist at the University of Milan and consultant at ABACO SpA, he blends academic rigor with practical deployment and training, serving as lecturer and presenter in remote sensing and agrometeo. On open source, he contributed reinforcement-learning environment support to the MushroomRL ecosystem, showing a broader ML toolkit beyond domain-specific analytics. His physics background underpins a quantitative, model-driven approach to solving complex agro-climatic problems.
11 years of coding experience
Laurea in Fisica, Fisica Applicata, Laurea in Fisica, Fisica Applicata at Università di Pavia
Github Skills (7)
deep-reinforcement-learning10
pytorch10
python10
reinforcement-learning10
ata7
atari26007
mujoco7
Programming languages (5)
Github contributions (5)
MushroomRL/mushroom-rl
Nov 2020 - Mar 2022
Python library for Reinforcement Learning.
Role in this project:
ML Engineer
ML EngineerContributions:7 commits, 13 PRs in 1 year 4 months
Contributions summary:Simone primarily contributed to extending the functionality of the reinforcement learning library, mushroom-rl, by adding support for new environments and improving existing ones. They implemented wrappers for Habitat, MiniGrid, iGibson, and DM pixels environments, demonstrating a focus on expanding the library's applicability to diverse environments. Additionally, the user updated existing environment classes (Gym), fixed reward implementations, and modified existing example scripts to include the new environments.
pythonreinforcement-learningdeep-reinforcement-learningdeep-learningopenai-gym
sparisi/tensorl
Jan 2019 - Jun 2020
Simple and self-contained TensorFlow implementation of reinforcement learning algorithms for continuous control, integrated with OpenAI Gym and other physics engines.
Contributions:4 commits, 6 PRs, 34 pushes in 1 year 4 months
openai-gymphysics-enginereinforcement-learningtensorflow
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