AI & Data Science Activities @EDF

I specialize in Machine/Deep Learning and Statistical Modeling with expertise in various technologies and methodologies. Here's a snapshot of my key skills:

Machine/Deep Learning & Statistical Modeling:

• Anomaly Detection: Proficient in identifying anomalies in thermal sensors within energy storage systems.

• Automated Data Analysis and Natural Language Generation: Skilled in automating data analysis processes and generating natural language output.

• Recommendation Model: Developed models to identify and recommend similar territories for enhanced decision-making.

• AI Drift Controller (NLP Use Case): Implemented AI drift controllers, particularly in the context of Natural Language Processing (NLP) # Python, Sklearn, PyTorch, TensorFlow, MLFlow, Git, AutoML

Multi-Agent Based Modeling:

• Simulation: Experienced in simulating human and electric vehicle charging behaviors.

• Optimization: Skilled in optimizing electricity production scheduling for improved efficiency. # GAML, GAMA Java.

Reinforcement Learning:

• Automated Data Cleaning Pipeline: Developed automated data cleaning pipelines for image detection and sentiment analysis using # DDQN and QLearning

Symbolic AI:

• Reasoning System: Proficient in developing reasoning systems incorporating ontology and knowledge graph.

# RDF, OWL, SparQL, GraphDB

Design of Storage and Processing of Massive Data:

• Batch and Stream Processing: Designed systems for the storage and processing of massive data, utilizing

# PySpark, Hive, Nifi, Kafka, Hadoop

Leadership and Collaboration:

• Mentorship: Actively engaged in mentoring juniors, interns, and contractors.

• Collaboration: Fostered collaborations with academic institutions to promote knowledge exchange

• Project Initiation: Involvement in setting up the Data Cloud project, multi-modal knowledge extraction for graph enhancement, knowledge enhanced Multi-Agent System for electricity production scheduling etc.