Lucas Cavalcante

Lucas Cavalcante is an experienced data scientist and machine learning scientist with a strong background in physics and computational methods. Currently employed at NOETIK, Lucas previously held the position of Machine Learning Scientist at Herophilus, where contributions included developing deep learning models for drug screening assays. As a postdoctoral scholar at the University of California, Davis, Lucas focused on automating spectroscopy simulations using density functional theory and maintained open-source software for research applications. Lucas's academic journey includes a PhD in Condensed Matter and Materials Physics from the Federal University of Ceara, complemented by a guest PhD at DTU - Technical University of Denmark, where advancements in simulation software for 2D materials were achieved. Throughout various research roles, Lucas has demonstrated expertise in simulation techniques, software development, and teaching scientific methodologies.