"Machine Learning in Finance"

Gary Kazantsev, Head of Machine Learning

Abstract: Machine learning is changing our world at an accelerating pace. In this talk we will discuss the impact of machine learning and artificial intelligence on finance, from a perspective of a technology company which is a key participant in the financial markets. We will give an overview of the evolution of several flagship Bloomberg ML and AI projects, such as sentiment analysis, question answering, market impact prediction, social media monitoring, topic clustering and time series analysis. We will talk about practical issues in delivering machine learning solutions to problems of finance with an example of how our social topic classification system was built from concepts to actual product. We will also highlight issues which are critical to the industry, such as interpretability, differential privacy and nonstationarity. We will also discuss some possible future directions for the applications of machine learning methods in finance.The talk will end with a Q&A session.

Bio: Gary is the Head of Machine Learning Engineering at Bloomberg, 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 in physics, mathematics, and computer science from Boston University. He is engaged in advisory roles with start ups in FinTech and machine learning space and has worked at a variety of technology and academic organizations over the last 20 years. He is a member of the KDD Data Science + Journalism workshop program committee and a co-organizer of the annual Machine Learning in Finance conference at Columbia University.