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Pedro Domingos Will Lead New D.E. Shaw Machine Learning Group

New York-based investment corporate D. E. Shaw Group yesterday announced that esteemed University of Washington Professor of Computer Science Pedro Domingos will join the firm as a Managing Director and lead its new Machine Learning Research Group.

New York-based investment corporate D. E. Shaw Group yesterday announced that esteemed University of Washington Professor of Computer Science Pedro Domingos will join the firm as a Managing Director and lead its new Machine Learning Research Group.

The Group will operate independently and in parallel to the firm’s machine learning efforts. Dr. Domingos will report to Cedomir Crnkovic, Managing Director, who runs the D. E. Shaw’s Futures and Currencies Systematic Trading Group.

Founded in 1988, D. E. Shaw has earned a reputation as a driving innovative force in hedge funds. Founder David Shaw pioneered the use of high-speed quantitative trading, a set of strategies to identify trading opportunities by using mathematical computations and number crunching. Many of the world’s top mathematicians, computer scientists and engineers are involved with D. E. Shaw and its research lab.

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D. E. Shaw Founder David Shaw, an American investor, computer scientist, and hedge fund manager.

Dr. Domingos is a renowned machine learning and data science expert. He co-authored the influential paper Markov Logic Network, which introduced a novel approach to combining logic and probabilistic graphical models in a single representation. His 2015 book The Master Algorithm is a bestseller Bill Gates recommends as one of two books everyone should read to understand AI. The book was also spotted on Chinese President Xi Jinping’s bookshelf during his last New Year’s address.

Financial companies are increasingly turning to AI as they discover the tremendous potential of leveraging machine learning in massive financial data. Deep Neural Networks can be used for example to predict price movements with short-term data, and these predictions can be transferred into trading strategies and then trading algorithms.

In a recent Barclay Hedge Fund poll, more than half the hedge fund managers and commodity trading advisers surveyed said they use AI or Machine Learning to inform investment decisions.

“Financial data sets are among the most challenging and fascinating ones for machine learning,” said Dr. Domingos. “It’s exciting to join the D. E. Shaw group, a pioneer of quantitative investing, to work on new avenues for attacking that challenge.”

Financial companies are now aggressively poaching AI experts from tech companies and universities. Earlier this year, J.P. Morgan hired Dr. Manuela Veloso from Carnegie Mellon University to lead the firm’s Artificial Intelligence Research. Goldman Sachs meanwhile lured machine learning expert Charles Elkan from Amazon.

Read Synced’s previous coverage on Dr. Domingo and AI in finance.


Journalist: Tony Peng | Editor: Michael Sarazen

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