Mikhail Golovnya, Senior Advisory Data Scientist, Minitab Mikhail Golovnya has been prototyping new machine learning algorithms and modeling automation for the past 25 years. He has been a major contributor to Salford Systems / Minitab on-going search for technological improvements to among the most important algorithms in Machine Learning: CART® Decision Trees, MARS® Non-linear Regression, TreeNet® gradient boosting, and Random Forests®. Mikhail has presented at multiple conferences and seminars, he has also been teaching the mathematical foundations and applications of major predictive learning algorithms, both classical and modern. Having three master’s degrees -- M.S. in rocket science from Kharkov State Polytechnic University (Kharkov, Ukraine), M.S. in Statistical Computing from the University of Central Florida (Orlando, FL), M.A. in Science and Religion from the Biola University (La Mirada, CA) -- he currently serves in the role of Senior Advisory Data Scientist and is leading the next generation of Minitab machine learning product development.
