Mr. Iat Chong CHAN
Machine Learning Team, London, United Kingdom
The Bloomberg Terminal brings together real-time data on every market, breaking news, in-depth research, powerful analytics in one fully integrated solution. In the News product, we provide, our award-winning news coverage ensures our clients could get the information they need. While at the same time, putting a lot of effort into trying to avoid overloading them with excessive information.
In this talk, we will have a general overview of how AI (Artificial intelligence) techniques are being utilised in Bloomberg to allow our clients obtaining the information needed efficiently. Then, we will focus on a particular application, which was designed to refine information from a massive amount of news stories. We will also discuss the AI algorithms that underpin it.
There is no pre-requisite for most part of this talk. 30% of the talk requires basic understanding of statistics and probabilities.
Iat Chong Chan (https://www.linkedin.com/in/iatchongchan) is a research scientist/software developer in Bloomberg Machine Learning Team. His interests mostly lie in the intersection of Computational Linguistics, Machine Learning, and High Performance Computing. He has been working on a scalable infrastructure to infer topics of social contents ingested to Bloomberg by statistical models, and a multi-documents summarisation system to extract the most important information from a text collection. Iat Chong also leads the NLP guild inside Bloomberg, to advocate the use of ML/NLP techniques for new business problems. Before he joined the company, he was a MSc student in Dept. of Computer Science at University of Oxford, supervised by Prof. Stephen Pulman, and worked on building a better input method on small hand-held devices by a novel Bayesian Network with Variational Inference.