Breck Baldwin serves as an Associate Research Scientist at Columbia University in the City of New York, where he leverages his extensive expertise in verifiable AI, bias in AI, and computational linguistics to drive innovative research projects. With a strong foundation in natural language processing...
Breck Baldwin serves as an Associate Research Scientist at Columbia University in the City of New York, where he leverages his extensive expertise in verifiable AI, bias in AI, and computational linguistics to drive innovative research projects. With a strong foundation in natural language processing (NLP) and machine learning, Breck is particularly focused on the intersection of these fields and their applications in addressing real-world challenges. His current work centers around the development of CoDatMo (Co)vid (Dat)a (Mo)deling, a pioneering platform designed to facilitate reproducible Bayesian models for COVID-19 modeling. This project is a collaborative effort with the University of Liverpool, aiming to enhance the accuracy and reliability of pandemic-related data analysis.
In his role, Breck is not only responsible for project management and grant writing but also plays a vital role in fundraising efforts to secure resources for ongoing research initiatives. His proficiency in Bayesian statistics and tools like Stan allows him to contribute meaningfully to the Stan project, ensuring that the methodologies employed are both robust and transparent. Breck’s diverse skill set, which includes text mining, information extraction, and data mining, enables him to extract valuable insights from complex datasets, further enriching the research landscape at Columbia University. As he continues to explore the nuances of AI and its implications for society, Breck remains committed to fostering an environment of ethical AI development and promoting best practices in computational research.
