Sep 23–26, 2019
Vlad Eidelman

Vlad Eidelman
Vice President of Research, FiscalNote

Website

Vlad Eidelman is the VP 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 built the first version of the companies patented technology to help organizations predict and act on policy changes. Prior to FiscalNote, he worked as a researcher in a number of academic and industry settings, completing his Ph.D. in CS, as an NSF and NDSEG Fellow, at the University of Maryland and his B.S. in CS and Philosophy at Columbia University. His research focuses 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 ACL, NAACL and 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. In this talk, we show how natural language processing and machine learning can be used to automate the process by analyzing over 10 million publicly released comments. Read more.

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