Kevin Knuth is a Professor of Physics at the University at Albany (SUNY), and is the Editor-in-Chief of the journal Entropy (MDPI). He received his Ph.D. in physics with a minor in mathematics in 1995 at the University of Minnesota where his research in using magnetoencephalography to study the nonlinear dynamics of human auditory cortical function was the one of the first interdisciplinary biophysics efforts at that university that brought together physics, neuroscience, and the mathematical field of nonlinear dynamics.
Knuth is a former NASA research scientist having worked at NASA Ames Research Center in the Intelligent Systems Division designing machine learning systems for astrophysics, Earth science, and climate studies. He has over 30 years of experience in applying Bayesian and maximum entropy methods to the design of machine learning algorithms for data analysis applied to the physical sciences. While at NASA he developed model-based super-resolution imaging techniques for generating three-dimensional models of planetary nebula from Hubble Space Telescope imagery. Knuth wrote the first papers on Bayesian Source Separation and Localization, which is now a field of research. His histogram binning algorithm (optBINS), also known as the Knuth Method, is a standard algorithm in Mathematica. He is a Senior Member of the IEEE, and is a member of the Foundational Questions Institute (FQxI).
His current research interests include the foundations of physics, inference and inquiry, autonomous robotics, the search for and characterization of extrasolar planets, and unidentified aerial phenomena (UAPs/UFOs). His work on the foundations of physics has resulted in the derivation of the laws of physics (such as relativistic quantum mechanics) from algebraic symmetries. His work on inference, inquiry, and autonomous robotics has led him to develop a theory of questions quantified by entropy, which enables machines to solve problems by identifying the best questions to ask / experiments to perform. Knuth and his students have developed the EXONEST software suite for inferring the characteristics of exoplanetary systems from photometric data. His team has found evidence suggesting that the hot Jupiter planet Kepler-91b may have a trojan partner positioned in one of K-91b’s Lagrange points, as well as the discovery of a triple star system consisting of a sun-like G star which is orbited by a pair of co-orbiting red M-dwarf stars, with orbits exhibiting a 10:1 orbital resonance.
Knuth is the lead scientist for UAPx, a contributing member of the Scientific Coalition for UAP Studies, an associate member of IFEX (Interdisciplinary Research Center for Extraterrestrial Studies), an affiliate of the Galileo Project, and he serves on the Board of Advisors for the Society for UAP Studies (SUAPS). Knuth has published over 100 peer-reviewed publications and has been invited to give over 100 presentations in 18 countries.