Speaker: Chakri Cherukuri

Quantitative Researcher @Bloomberg

Chakri Cherukuri is a senior researcher in the Quantitative Financial Research group at Bloomberg LP. His research interests include quantitative portfolio management, algorithmic trading strategies and applied machine learning. Previously, he built analytical tools for the trading desks at Goldman Sachs and Lehman Brothers. Before that he worked in the Silicon Valley for startups building enterprise software applications. He has extensive experience in numerical computing and software development. He is the core contributor to bqplot, a 2D plotting library for the Jupyter notebook. He holds an undergraduate degree in engineering from Indian Institute of Technology, Madras, an MS in computer science from Arizona State University and another MS in computational finance from Carnegie Mellon University.

Find Chakri Cherukuri at

2019 Tracks

  • Groking Timeseries & Sequential Data

    Techniques, practices, and approaches around time series and sequential data. Expect topics including image recognition, NLP/NLU, preprocess, & crunching of related algorithms.

  • Deep Learning in Practice

    Deep learning use cases around edge computing, deep learning for search, explainability, fairness, and perception.