Archit Datar

Archit Datar is a Senior Data Scientist at Celanese, where they develop hybrid AI/ML data products to enhance innovation in research and development. With a PhD in Computational Materials Discovery from The Ohio State University, Archit has a strong background in advanced molecular simulation and AI algorithms, contributing to multiple high-impact research publications. They have previously held roles at DuPont and Dow, focusing on digital transformation and predictive modeling in the materials industry. Known for their interest in improving machine learning interpretability, Archit has created the ML Uncertainty Python package to quantify uncertainty in ML models.