Arindam Biswas is an AI researcher with a strong background in theoretical mathematics and machine learning theory. His work focuses on the foundations of artificial intelligence, including large language models, fine-tuning, sparsification, and multi-agent systems. He combines rigorous mathematical reasoning with applied AI research to design more efficient, reliable, and theoretically grounded intelligent systems.

Thierry Mefenza is an expert data scientist with a strong academic and research background. He completed his PhD at ENS and holds a Master’s degree in Data Science. As a former teacher-researcher, he combines scientific rigor, statistical modeling, and applied machine learning expertise to design robust data-driven solutions for complex business and industrial challenges.

Yassine Naji is an AI researcher whose work focuses on computer vision, video analysis, and anomaly detection. He explores how AI can be used to identify complex patterns in visual data and build robust systems for real-world monitoring and decision-support applications. His interests also include agentic AI pipelines, combining perception, reasoning, and action to create more autonomous and adaptable intelligent systems.

Nicolas Urbani is an AI researcher with a strong interest in software development, system integration, and production-ready AI architectures. His work focuses on building robust agentic pipelines, from low-level orchestration to real-world deployment, using frameworks such as LangGraph. He combines deep learning expertise with a practical engineering mindset to turn AI concepts into reliable, maintainable systems.

Gaël Marec is an AI researcher with expertise in multimodal AI, knowledge graphs, and computer vision. His research explores how structured representations and language models can improve the understanding of complex visual and textual data. At Polynom Research, he focuses on bridging academic research and real-world applications by building AI prototypes that are explainable, reliable, and aligned with business needs.

Raphaël Mouravieff is an AI researcher specializing in large-scale database analysis and data-driven decision-making. In addition to his PhD research in Artificial Intelligence, he holds a Master’s degree in Economics, giving him a strong interdisciplinary perspective on complex data systems. His work focuses on using AI to extract insights from massive datasets, with a particular interest in applications in the medical and biochemical fields.

Sinitandjon Yaya Yeo is a PhD student at the intersection of academic research and applied AI, working between Polynom and Sorbonne University. A graduate of École Polytechnique, he is conducting research on multi-agent systems under the co-supervision of Arindam Biswas. His work explores how autonomous AI agents can collaborate, reason, and coordinate actions to solve complex tasks in practical environments.