Arthur Calvi - AI & Remote Sensing Researcher

Current Roles

PhD Student – Remote Sensing (INRIA/CNRS)
Researching forest disturbance detection using satellite imagery and deep learning techniques. Focusing on both abrupt changes (fire, harvesting) and gradual changes (drought, insect attacks).
AI Consultant – DxO Labs
Leading AI initiatives including employee training in LLMs, developing customer support systems using RAG, and creating automated audio dubbing solutions.

Academic Background

PhD in Remote Sensing - INRIA/CNRS (2022-2025)
Research focus: Detection and classification of non-stand-replacing vegetation disturbances to understand and qualify forests' resilience to climate change in Europe. Leveraging satellite imagery and machine learning to study the impact of natural hazards (droughts, fires, insect attacks) and human activities on European forests, which represent a crucial 7% GHG sink in the EU's climate goals.
Master 2 MVA (Mathematics, Vision, Learning) - ENS Paris-Saclay (2021-2022)
Advanced mathematical and experimental training in computer vision, machine learning, and signal processing. Key courses: Convex Optimization, Object Recognition & Computer Vision, Topological Data Analysis, Deep Learning, and Numeric Imaging.
Master 2 Energy - MINES Paris - PSL (2020-2021)
Specialized program focused on decarbonized energy futures, jointly offered by MINES ParisTech, Chimie ParisTech, and ESPCI Paris. Key courses: High-efficiency Industrial Processes, Energy Systems & Building Efficiency, Renewable Energy Technologies, Energy Storage & Grid Systems, Sustainable Mobility Systems.
Master 1 Civil Engineering - Sustainable Envelopes and Buildings (2019-2020)
Comprehensive training in structural engineering and energy management. Key courses: Continuum Mechanics (Solids & Fluids), Structural Analysis, Numerical Methods, Building Thermal Management, Energy Systems & Distribution, Renewable Energy, Materials Science, Construction Methods.
SAPHIRE Program - ENS Paris-Saclay (2018-2019)
Joint program by Electronics/Electrical Engineering, Civil Engineering, and Mechanical Engineering departments. Focus areas: Mathematical Modeling & Simulation, Materials Science, Numerical Methods, Signal Processing, Complex Materials, Dynamic System Control, Eco-design & Construction.

Certifications

C1 Advanced (CAE) – Cambridge Assessment English
Scientific Writing Assessment Program – ENS Paris-Saclay
Neural Networks and Deep Learning – Coursera (deeplearning.ai)
Advanced Training in Energy Efficiency & Deep Learning

Technical Skills

Core Expertise

Remote Sensing
Deep Learning
Machine Learning
Computer Vision
Time Series Analysis
NLP & Generative AI

Technologies

Python (NumPy, PyTorch, Scikit-Learn)
GeoPandas, Rasterio, OpenCV
LangChain, LlamaIndex
Docker, AWS
HTML, SQL, C++

Contact

Interested in research collaboration or AI consulting? Let's connect.