Alex Gray

Alexander Gray, Ph.D.

Chief Executive Officer & Co-Founder

Alexander Gray serves as CEO of Skytree, after having recently served as a tenured Associate Professor in the College of Computing at Georgia Institute of Technology. A theme of his work, over more than two decades, has been the goal of speeding up and scaling up all of the major practical methods of machine learning in order to help realize the widespread use of massive datasets in science and industry.  This early focus on the computational aspects of machine learning, beginning in 1993 with work on massive scientific datasets on supercomputers at NASA’s Jet Propulsion Lab, long preceded the recognition in recent years of the importance of “big data”.  His work has resulted in a number of current state-of-the-art algorithms for several key problems, both in terms of mathematical complexity and real-world speed (a relatively rare combination), state-of-the-art industrial-strength software in use for critical applications in Fortune 500 companies and science institutions, and high-profile applications in astronomy and other sciences.  His current efforts lie in the formalization and automation of “data science” (including data preparation, exploratory data analysis, model validation, and deployment), toward mass enabling of high-quality/high-importance applications of machine learning.  He has won or been nominated for a number of best paper awards in statistics and data mining and is a recipient of the National Science Foundation CAREER Award and a National Academy of Sciences Kavli Scholar.  He is a frequent advisor on the topic of Big Data, including serving on the National Academy of Sciences Committee on the Analysis of Massive Data (2010), and the topic of Data Science, including serving in the National Science Foundation Workshop on the Theoretical Foundations of Data Science (2016) and on the Advisory Board of the Statistical and Applied Mathematical Sciences Institute (2016).  He holds B.S. degrees in Applied Mathematics and Computer Science from the University of California, Berkeley and a PhD in Computer Science from Carnegie Mellon University.