iCubed Seminar: Daniel Preotiuc-Pietro, Bloomberg

Dec 1, 2021

Dec 1, 2021

5:30 pm To 6:30 pm

Online: EDT (USA)


Event Description

iCubed (Institute, Industry, Innovation) seminars invite DSI Industry Affiliates to give technical talks on work going on in their domain.

Join DSI’s iCubed Seminar Series to learn about real-world uses of data science and opportunities with DSI Industry Affiliates.

Guest Speaker: Daniel Preoțiuc-Pietro, Senior Research Scientist, Bloomberg

Moderated By: Jessica Rodriguez, Industry Engagement and Outreach Officer, The Data Science Institute

Applied Named Entity Recognition @ Bloomberg

Bloomberg deals with a wealth of heterogeneous data, including (but not limited to): reports from financial analysts, earnings releases, company filings, news stories, web scrapes, social media posts, ticker symbols, and pricing information of a wide variety of securities. With 80% of financial data in unstructured formats, the ability to quickly identify named entities automatically is essential to understanding this content.

We will briefly introduce Bloomberg’s products that use this technology and present the unique challenges related to Bloomberg’s data and business. We will then present four of our recent publications that aim to tackle the following challenges: heterogeneity of content, temporal data drift, ensuring high precision in tagging or tagging entities as they are typed.

Bio: Daniel Preoțiuc-Pietro is a Senior Research Scientist at Bloomberg, where he leads the core NLP group that powers models for processing news, social media and financial documents. His research interests are focused on understanding the social and temporal aspects of text, especially from social media, with applications in domains such as Social Psychology, Law, Political Science and Journalism. Several of his research studies were featured in popular press including the Washington Post, BBC, New Scientist, Scientific American or FiveThirtyEight. He is a co-organizer of the Natural Legal Language Processing workshop series since its inception. Prior to joining Bloomberg LP, Daniel was a postdoctoral researcher at the University of Pennsylvania with the interdisciplinary World Well Being Project and obtained his PhD in Natural Language Processing and Machine Learning at the University of Sheffield, UK.


Data Science Institute, Columbia University

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