In 2018, Comet.ml hosted a series of meetups through NYC Artificial Intelligence & Machine Learning, aiming to unite data scientists from academia and industry to discuss the latest machine learning developments. Key speakers included Melanie Weber, a Columbia PhD candidate, who developed geometric tools for analyzing complex networks, and Clare Gollnick of Terbium Labs, who addressed the reproducibility crisis in data science. Precision Health AI presented their oncology data management pipeline, while Columbia PhD Yixin Wang introduced the "deconfounder" algorithm for causal inference. These events highlighted advancements in network analysis, machine learning reproducibility, and oncology data management, showcasing Comet.ml's commitment to fostering innovation and collaboration in data science.