Brandon M. Turner is an Assistant Professor in the Psychology Department at The Ohio State University. He received a B.S. from Missouri State University in mathematics and psychology in 2008, a MAS from The Ohio State University in statistics in 2010, and a Ph.D. from The Ohio State University in 2011. He then spent one year as a postdoctoral researcher at University of California, Irvine, and two years as a postdoctoral fellow at Stanford University. His research interests include dynamic models of cognition and perceptual decision making, efficient methods for performing likelihood-free and likelihood-informed Bayesian inference, and unifying behavioral and neural explanations of cognition. His current focus is on understanding how external factors such as the environment, and internal factors such as working memory interact to shape an observer’s perception of the world, and ultimately how this perception drives their decisions. Vita [@ 8/22/17]
Peter D. Kvam is a postdoctoral researcher in the Psychology Department at The Ohio State University. He received a B.S. in Psychology and B.A. in Mathematics and Sociology from Indiana University in 2012, then an M.A. in 2014 and a Ph.D. in 2017 in Psychology at Michigan State University. He spent a year as a postdoctoral researcher at Indiana University before joining the lab in 2018. His research interests include cognitive models of judgment and decision-making, computational evolution of artificial intelligence, and hierarchical Bayesian methods for connecting behavior across different tasks. He is currently focusing on developing dynamic models of judgments and decisions that feature many alternatives, as well as characterizing decision-makers’ performance across tasks by connecting cognitive models to latent traits such as impulsivity or memory capacity.
James Palestro is a fourth-year doctoral student in the Psychology Department at The Ohio State University. He received a B.A. from Youngstown State University in psychology in 2015, and an M.A. from the Ohio State University in psychology in 2018. His research interests include cognitive modeling, perceptual decision making, and choice confidence. Currently, he is focusing on identifying mechanisms used in perceptual decision making through neuroscientific measures. Vita [@ 1/11/18]
Giwon Bahg is a third-year doctoral student. He received a B.A. in Psychology and Philosophy in 2013, and an M.A. in Psychology in 2015 from Seoul National University. He is interested in computational modeling, Bayesian methods, and temporal dynamics of human cognition, particularly in the context of thinking processes (e.g., categorization, reasoning, decision-making). His current work aims to implement adaptive design optimization for fMRI experiments using a joint modeling approach. He is also investigating dynamics of internal representations in decision-making, as well as its neural and computational bases.
Qingfang Liu is a third-year graduate student. She graduated from Beijing Normal University in China in 2016, with a B.S. in Psychology. Now she is studying for a doctoral degree in Cognitive Psychology and a MAS degree in Statistics. She is interested in perceptual and economical decision-making, computational cognitive models (e.g. sequential sampling models) and Bayesian methods. Her current focus is identifying neural correlates of intertemporal choice and constructing joint models by linking behavioral and neural data. She is also working as a course associate for Data Analysis in Psychology (Psych 2220).
Nate Haines is a third year doctoral student studying clinical psychology at The Ohio State University (OSU). He received his B.A. from OSU in 2015, and his M.A. from OSU in 2017. Nate is interested in the role that emotion plays in how humans process, learn from, and make decisions based on rewards—particularly in the case of drug addiction and other externalizing disorders (e.g., ADHD). Currently, he is focusing on: (1) the role of emotion in learning and valuation, and (2) the relationship between impulsive and anxious personality traits and risky behavior. Nate uses cognitive modeling and machine learning techniques to explore these questions.
Fiona Molloy is first-year graduate student. She graduated from Ohio State in 2018, with a B.S. in Neuroscience. Her research interests include computational modeling and the neural bases of cognitive control and decision-making. Additionally, she is interested in studying the dynamics of these processes in clinical populations, particularly in those struggling with addiction. She is currently working on modeling inhibitory control using neural and behavioral data.
Matthew Galdo is a first-year graduate student. He graduated from Ohio State University in 2018 with a B.S. in Neuroscience. Now, he is working toward a Ph.D. in Cognitive Psychology and a MAS degree in Statistics. His research interests include: the dynamics of decision making, in particular how abnormal patterns of decision behavior (e.g. addiction) and their underlying mechanisms evolve over time; merging cognitive and psychiatric theory; Bayesian statistical methodology; and the link between neural data and cognition. Currently, his main focus is exploring how connectome data can interface with joint models of neural and behavioral data.
Woojong Yi is a first-year doctoral student in the Psychology Department at The Ohio State University. He received a B.A. from The Catholic University of Korea in Psychology in 2010, and an M.A. from Seoul National University in Interdisciplinary program in Cognitive Science (Concentration in Quantitative Psychology) in 2016. He is interested in finding and understanding of processing stages of cognition (e.g., self-control and decision-making), Bayesian statistical methods, computational modeling, joint modeling of behavioral and neural measures, and ultimately, theoretical understanding of cognition. He is currently working on discovering discrete processing stages of self-control using Hidden Markov Models.
Peter Hsu is a fourth-year undergraduate student studying Neuroscience with minors in Computer and Information Science and Cognitive Science. His research interests include computational modeling and brain-machine interface. His current work involves programming experiments in SMILE (State Machine Interface Library for Experiments) to assess the adaptive representation of stimuli in a changing environment.
Corey Keyser is a fourth-year undergraduate student double majoring in Neuroscience and Philosophy with a minor in Computer and Information Science. He is interested in computational modeling with a focus on integrating our understanding of biological processes into our cognitive explanations of processes like decision, desire, and self-control. Currently, his research involves using dynamic sampling to improve cognitive models of evidence accumulation.