Paul Siegel
About Paul Siegel
Paul Siegel is a Senior Machine Learning Engineer at Turing Labs Inc. in Boston, Massachusetts, where he focuses on using large language models for Bayesian optimization. He has held various roles in data science and product management, including positions at Brandwatch and Columbia University.
Work at Turing Labs Inc.
Paul Siegel has been employed at Turing Labs Inc. as a Senior Machine Learning Engineer since 2023. He is based in Boston, Massachusetts. In his current role, he focuses on utilizing large language models to develop causal structures for Bayesian optimization. This work contributes to advancements in machine learning applications within the organization.
Previous Experience at Brandwatch
Before joining Turing Labs Inc., Paul Siegel worked at Brandwatch for a total of seven years. He served as Product Director from 2021 to 2022 and as Principal Data Scientist from 2015 to 2021. During his tenure, he led a team of 35 professionals, including data scientists, engineers, product designers, and UX researchers, in the AI division. His projects at Brandwatch included influence and reach analysis in online social networks, entity linking and categorization in short-form text, audience classification, and trend detection.
Academic Background
Paul Siegel holds a Doctor of Philosophy (PhD) in Mathematics from Penn State University, where he studied from 2007 to 2012. He also earned a Bachelor of Science (B.S.) in Mathematics from the University of Michigan, completing his studies there from 2003 to 2007. His academic background provides a strong foundation for his work in machine learning and data science.
Experience at Columbia University
Paul Siegel served as an Assistant Professor of Mathematics at Columbia University in the City of New York from 2012 to 2015. In this role, he contributed to the academic community and engaged in research and teaching, further enhancing his expertise in mathematics.