Delanoe Pirard

AI Engineer specialized in applied research, I design and develop advanced AI systems for scientific, industrial, and highly constrained environments. My work focuses on deep learning, computer vision, reinforcement learning, physical simulation, and statistical modeling.

I have solid experience in creating algorithms capable of solving complex problems: behavior optimization, task planning, visual recognition, biological structure analysis, and information extraction from heterogeneous data. I rely on advanced simulation environments (IsaacSim), modern cloud platforms, and the NVIDIA ecosystem to achieve reliable and reproducible performance.

My background in bioinformatics led me to develop models for predicting protein characteristics, drawing inspiration from natural language processing techniques. I contributed to work in digital pathology, where I designed and validated models capable of identifying histological structures and detecting malignant patterns in medical images. These experiences familiarized me with experimental methodologies, statistical validation, and the rigor required for research projects.

Before specializing in AI, I worked for several years as a full-stack developer, creating complete web applications, robust backend infrastructures, and industry-oriented connected solutions. This versatility allows me to understand the entire technical chain today, from the design of a learning model to its integration into an operational system.

I am involved in R&D missions, advanced prototyping, algorithmic problem-solving, and the development of reliable, measurable AI solutions adapted to real-world constraints.