Summary
Hudson Golino is an Associate Professor of Quantitative Methods at the University of Virginia with 11 years of experience applying psychometrics, data mining, and machine learning to psychological and educational measurement. He holds a Ph.D. in Neurosciences/Data Mining and multiple certifications in applied measurement, Rasch methods, and statistics in medicine, reflecting a strong interdisciplinary foundation. Hudson’s work spans academic leadership, instrument construction and validation, and applied data science in healthcare settings where he has developed predictive algorithms for ICU outcomes. He has taught and conducted research across Brazil and the U.S., integrating computational approaches into psychology curricula and graduate training. Beyond traditional psychometrics, he runs generativepsychometrics.com and networkpsychometrics.com, signaling an active interest in novel, network-based and generative methods for measurement. Colleagues value him for bridging rigorous methodological research with practical tools for assessment and data-driven clinical decision making.
11 years of coding experience
8 years of employment as a software developer
Certification, Rasch Measurement, Certification, Rasch Measurement at The University of Western Australia
Certification, Introduction to Mathematical Philosophy, Certification, Introduction to Mathematical Philosophy at Ludwig-Maximilians-Universität München
Certification, Applied Measurement, Certification, Applied Measurement at University of Virginia
Doctor of Philosophy (Ph.D.), Neurosciences/Data Mining, Doctor of Philosophy (Ph.D.), Neurosciences/Data Mining at Universidade Federal de Minas Gerais
Certification, Statistics in Medicine, Certification, Statistics in Medicine at Stanford University
English, Portuguese, Spanish