The De Gruyter STEM series published a new textbook authored by Ivo D. Dinov and his colleague Milen V. Velev. The “Data Science – Time Complexity, Inferential Uncertainty, and Spacekime Analytics” book represents years of significant effort to develop a novel mathematical foundation of data science.
By introducing complex time (kime), this work unifies artificial intelligence (AI), data science, and quantum mechanics into a new data analytics framework where longitudinal data (e.g., time-series) are represented as manifolds (e.g., kime-surfaces). The textbook is freely available (hardcover copy and EBook format) at the University of Michigan Library, and will serve as core and supplementary material for several graduate level courses in Health Sciences, Bioinformatics, Mathematical Physics, and Engineering. The supporting textbook website includes a number of demonstrations, applications, and an open-source TCIU R package.