PEDRO DOMINGOS is a Professor of Computer Science at the University of Washington, head of machine learning research at D. E. Shaw, and the author of "The Master Algorithm". He is a winner of the SIGKDD Innovation Award, the highest honor in data science. He is a Fellow of the Association for the Advancement of Artificial Intelligence, and has received a Fulbright Scholarship, a Sloan Fellowship, the National Science Foundation’s CAREER Award, and numerous best paper awards. His research spans a wide variety of topics in machine learning, artificial intelligence, and data science, including scaling learning algorithms to big data, maximizing word of mouth in social networks, unifying logic and probability, and deep learning.

FOSTER PROVOST is Professor of Information Systems, Andre Meyer Faculty Fellow, and Director, Fubon Center, Data Analytics & AI, at the Stern School of Business at New York University. He is also Professor of Data Science and former interim Director of the NYU's Center for Data Science. He previously was Editor-in-Chief of the journal Machine Learning, and Prof. Provost's book, Data Science for Business: What you need to know about data mining and data analytic thinking, is a perennial best-seller explaining machine learning to business folk. Foster stands out in data science for having made substantial contributions across research, business thought leadership, and practical applications.