D.E. Shaw Dives Into Machine Learning08.16.2018
The D. E. Shaw group, a global investment and technology development firm and a pioneer in quantitative approaches to trading and investment, today announced the formation of a new, independent machine learning research and development effort.
The new Machine Learning Research Group, which will operate in parallel to the firm’s longstanding machine learning efforts, will be overseen by Dr. Pedro Domingos, who will join the firm as a Managing Director. Dr. Domingos will report to Cedomir Crnkovic, Managing Director, who joined the firm in 1997 and for much of his tenure ran the firm’s futures and currencies systematic trading group.
“Over the past few decades we have developed and deployed increasingly sophisticated machine learning techniques,” said Eric Wepsic, a D. E. Shaw group Managing Director and a member of the firm’s executive committee who oversees the firm’s quantitative trading and investments. “This new, independent venture reflects the importance we attach to gaining fresh perspectives and insights as technology evolves. It also provides us with an opportunity to bring in some of the brightest lights in the field and allow them to set their own research agenda. Pedro is widely recognized as a path-breaking expert on the research frontiers of machine learning, and we are delighted to have him onboard.”
“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.”
Dr. Domingos is a leading authority on machine learning as well as an opinion leader on the issues surrounding it. He is a Professor of Computer Science and Engineering at the University of Washington, as well as the author of The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World, a best-selling book on machine learning. Dr. Domingos has received numerous awards and recognitions, including the SIGKDD Innovation Award, awarded jointly by KDD, the community for data mining, data science, and analytics, and the Association for Computing Machinery recognizing individuals for their outstanding technical contributions to the field of knowledge discovery in data and data mining. He is a member of the editorial board of the journal Machine Learning and a co-founder of the International Machine Learning Society.
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