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Author Information
Jennifer Trueblood (Vanderbilt)
Dr. Jennifer Trueblood is Associate Professor of psychology and Chancellor Faculty Fellow at Vanderbilt University. She is also Director of Graduate Studies for the Department of Psychology. She is interested in understanding (1) how people make decisions when faced with multiple alternatives, (2) how dynamically changing information affects decision processes, (3) how people reason about complex causal events, and (4) how different perspectives, contexts, and frames can lead to interference effects in decision-making and memory. To address these questions, she develops probabilistic and dynamic models that can explain behavior and uses hierarchical Bayesian methods for data analysis and model-based inference. She is currently an Associate Editor at Cognitive Psychology and Management Science. She is a past president of the Society for Mathematical Psychology and currently helps co-organize the Women of Mathematical Psychology group.
Alex Peysakhovich (Facebook)
Angela Yu (UC San Diego)
Ori Plonsky (Technion - Israel Institute of Technology)
Tal Yarkoni (UT Austin)
Daniel Bjorkegren (Brown University)
More from the Same Authors
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2021 : Representational Denoising to Improve Medical Image Decision Making »
Eeshan Hasan · Jennifer Trueblood · Quentin Eichbaum · Adam Seegmiller · Charles Stratton -
2021 : Integrating Machine Learning and a Cognitive Modeling of Decision Making »
Taher Rahgooy · Jennifer Trueblood · Brent Venable -
2021 Poster: Online Market Equilibrium with Application to Fair Division »
Yuan Gao · Alex Peysakhovich · Christian Kroer -
2019 : Panel Discussion led by Grace Lindsay »
Grace Lindsay · Blake Richards · Doina Precup · Jacqueline Gottlieb · Jeff Clune · Jane Wang · Richard Sutton · Angela Yu · Ida Momennejad -
2019 : Invited Talk #6: Features or Bugs: Synergistic Idiosyncrasies in Human Learning and Decision-Making »
Angela Yu -
2018 Poster: Why so gloomy? A Bayesian explanation of human pessimism bias in the multi-armed bandit task »
Dalin Guo · Angela Yu -
2018 Poster: Demystifying excessively volatile human learning: A Bayesian persistent prior and a neural approximation »
Chaitanya Ryali · Gautam Reddy · Angela Yu -
2018 Poster: Beauty-in-averageness and its contextual modulations: A Bayesian statistical account »
Chaitanya Ryali · Angela Yu -
2017 : Computational modeling of human face processing »
Angela Yu -
2017 : Workshop overview »
Michael Mozer · Angela Yu · Brenden Lake -
2017 Workshop: Cognitively Informed Artificial Intelligence: Insights From Natural Intelligence »
Michael Mozer · Brenden Lake · Angela Yu -
2013 Poster: Forgetful Bayes and myopic planning: Human learning and decision-making in a bandit setting »
Shunan Zhang · Angela Yu -
2013 Poster: Context-sensitive active sensing in humans »
Sheeraz Ahmad · He Huang · Angela Yu -
2012 Poster: Strategic Impatience in Go/NoGo versus Forced-Choice Decision-Making »
Pradeep Shenoy · Angela Yu -
2012 Oral: Strategic Impatience in Go/NoGo versus Forced-Choice Decision-Making »
Pradeep Shenoy · Angela Yu -
2010 Oral: A rational decision making framework for inhibitory control »
Pradeep Shenoy · Rajesh PN Rao · Angela Yu -
2010 Poster: A rational decision making framework for inhibitory control »
Pradeep Shenoy · Rajesh PN Rao · Angela Yu -
2008 Poster: Sequential effects: Superstition or rational behavior? »
Angela Yu · Jonathan D Cohen -
2008 Spotlight: Sequential effects: Superstition or rational behavior? »
Angela Yu · Jonathan D Cohen -
2007 Spotlight: Sequential Hypothesis Testing under Stochastic Deadlines »
Peter Frazier · Angela Yu -
2007 Poster: Sequential Hypothesis Testing under Stochastic Deadlines »
Peter Frazier · Angela Yu -
2006 Poster: Optimal Change-Detection and Spiking Neurons »
Angela Yu