Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA
Chakri Cherukuri

Chakri Cherukuri
Senior Quantitative Researcher, Bloomberg LP

Website

Chakri Cherukuri is a senior researcher in the Quantitative Financial Research Group at Bloomberg LP in NYC. His research interests include quantitative portfolio management, algorithmic trading strategies, and applied machine learning. He has extensive experience in scientific computing and software development. Previously, he built analytical tools for the trading desks at Goldman Sachs and Lehman Brothers. He holds an undergraduate degree in mechanical engineering from the Indian Institute of Technology (IIT) Madras, India, and an MS in computational finance from Carnegie Mellon University.

Sessions

11:50am–12:30pm Wednesday, March 27, 2019
Applied machine learning in finance
Data Science, Machine Learning & AI
 Location: 2009
Secondary topics:  Financial Services, Text and Language processing and analysis
Chakri Cherukuri (Bloomberg LP)
Average rating: ****.
(4.33, 3 ratings)
Quantitative finance is a rich field in finance where advanced mathematical and statistical techniques are employed by both sell-side and buy-side institutions. Chakri Cherukuri explains how machine learning and deep learning techniques are being used in quantitative finance and details how these models work under the hood. Read more.