Spacekime theory was developed by two data scientists:
- Dr. Ivo Dinov is the University of Michigan's SOCR Director, as well as a professor of Health Behavior and Biological Sciences, and Computational Medicine and Bioinformatics. SOCR stands for: Statistics Online Computational Resource designs. Dr. Dinov is an expert in "mathematical modeling, statistical analysis, computational processing, scientific visualization of large datasets (Big Data) and predictive health analytics." His research has focused on mathematical modeling, statistical inference, and biomedical computing.
- His colleague, Dr. Milen Velchev Velev, is an associate professor at the Prof. Dr. A. Zlatarov University in Bulgaria. He studies relativistic mechanics in multiple time dimensions, and his interests include "applied mathematics, special and general relativity, quantum mechanics, cosmology, philosophy of science, the nature of space and time, chaos theory, mathematical economics, and micro-and-macroeconomics."
Drs. Dinov and Velev began developing spacekime theory around four or five years ago, while working with big data in the healthcare field. "We started looking at data that intrinsically has a temporal dimension to it," Dr. Dinov told me during a video chat. "It's called longitudinal or time varying data, longitudinal time variance—it has many, many names. This is data that varies with time. In biomedicine, this is the de facto, standard data. All big health data is characterized by space, time, phenotypes, genotypes, clinical assessments, and so forth."
Also, watch for Drs. Dinov and Velev's book on spacekime theory this August, "Data Science: Time Complexity, Inferential Uncertainty, and Spacekime Analytics (De Gruyter Stem)."