Sep 23–26, 2019
Vlad Eidelman

Vlad Eidelman
Vice President, Research, FiscalNote

Website

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.

Sessions

4:35pm5:15pm Wednesday, September 25, 2019
Location: 1E 12/13
Vlad Eidelman (FiscalNote)
While regulations affect your life every day, and millions of public comments are submitted to regulatory agencies in response to their proposals, analyzing the comments has traditionally been reserved for legal experts. Vlad Eidelman outlines how natural language processing (NLP) and machine learning can be used to automate the process by analyzing over 10 million publicly released comments. Read more.

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