Advances in NLP: Finance Perspective


October 6th at 12:25 PM ET – 12:45 PM ET

Register – Free

In this talk we will discuss the latest developments in NLP research viewed through the lens of the finance industry. We will talk about a range of applications of NLP in finance – signal construction from unstructured data, information extraction, question answering, etc. – and review advances in the state of the art for key NLP tasks involved in those applications – relation extraction, paraphrase generation, table extraction, summarization and representation learning. This talk will cover a selection of recent papers from EMNLP 2021, AAAI 2022, ACL 2022 and NAACL 2022 published by or in collaboration with the Bloomberg AI Engineering group. Finally, we will look at the further directions for research and applications of NLP in finance. The talk will conclude with a Q&A session.

About the speaker

Gary Kazantsev

Head of Quant Technology Strategy at Bloomberg

Gary is the Head of Quant Technology Strategy in the Office of the CTO at Bloomberg. Prior to taking on this role, he created and headed the company’s Machine Learning Engineering group, leading projects at the intersection of computational linguistics, machine learning and finance, such as sentiment analysis of financial news, market impact indicators, statistical text classification, social media analytics, question answering, and predictive modeling of financial markets.

Prior to joining Bloomberg in 2007, Gary had earned degrees with distinction in physics, mathematics, and computer science from Boston University.

He is engaged in advisory roles with FinTech and Machine Learning startups and has worked at a variety of technology and academic organizations over the last 20 years. In addition to speaking regularly at industry and academic events around the globe, he is a member of the KDD Data Science + Journalism workshop program committee and the advisory board for the AI & Data Science in Trading conference series. He is also an adjunct professor at Columbia University, and a co-organizer of the annual Machine Learning in Finance conference at Columbia University.



Sessions: October 4 – 6
Trainings: October 11 – 14


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