Wei Ji Ma (Dutch: Whee Ky; Chinese: 马伟基) is a professor at New York University in the Department of Psychology and the Center for Neural Science. Ma focuses on the areas of perception, decision-making, and memory. He holds a PhD in theoretical physics from University of Groningen in the Netherlands. Ma is the 2021 recipient of the Jeffrey L. Elman Prize for Scientific Achievement and Community Building from the Cognitive Science Society. Biography Ma grew up in Groningen, the Netherlands. He received a Bachelor of Science and Master of Science in physics in 1996 and a Bachelor of Science and Master of Science in mathematics in 1997, both from the University of Groningen. He continued at the University of Groningen, where he received a PhD in theoretical physics in 2000. He transitioned into computational neuroscience as a post-doctoral fellow under Christof Koch at the California Institute of Technology from 2002 to 2004, and subsequently as a post-doctoral fellow under Alexandre Pouget at the University of Rochester until 2008. He received his first faculty position in the Department of Neuroscience at Baylor College of Medicine in 2008 and remained there until 2013, when he took an associate professor position at New York University, where he has a dual appointment in the Center for Neural Science and the Department of Psychology. Research Ma researches how the human brain represents and processes uncertainty. A large portion of his academic work is devoted to the construction of Bayesian inference models which describe how an observer arrives at beliefs about things in the world from noisy information. This modeling spans the range of describing the behavior of an observer, for example how an observer might infer two sensory inputs arise from a common source, to the activity of a population of neurons implementing the Bayesian operations. A complementary line of inquiry is studying encoding strategies in working memory, specifically highlighting the relationships between the role of noisy representations of objects in the brain and the number that can be recalled correctly. Broadly, his modeling focuses can be described as examining encoding models, decision rules, and probabilistic computations. In recent years, his work has focused on planning and thinking ahead in complex decision problems. Representative publications Ma, W. J. (2012). Organizing probabilistic models of perception. Trends in Cognitive Sciences, 16(10), 511-518. Ma, W.J., Beck, J.M., Latham, P.E., & Pouget, A. (2006). Bayesian inference with probabilistic population