Vlad Eidelman
Vice President, Research, FiscalNote
Vlad Eidelman is the vice president of research at FiscalNote, where he leads AI R&D into advanced methods for analyzing, modeling, and extracting knowledge from unstructured data related to government, policy, and law, and he built the first version of the company’s patented technology to help organizations predict and act on policy changes. Previously, he was a researcher in a number of academic and industry settings, completing his PhD in computer science as an NSF and NDSEG Fellow at the University of Maryland, and his BS in computer science and philosophy at Columbia University. His research focused on machine learning algorithms for a broad range of natural language processing applications, including entity extraction, machine translation, text classification, and information retrieval, especially applied to computational social science. His work has led to 10 patent applications, has been published in conferences like the Association for Computational Linguistics (ACL), North American Chapter of the Association for Computational Linguistics (NAACL), and Empirical Methods in Natural Language Processing (EMNLP), and has been covered by media such as Wired, Vice News, Washington Post and Newsweek.
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