Tim Pleskac
Professor, Psychological and Brain Sciences
Indiana University Bloomington​
1101 E. 10th St.
Psychology Building 361
Bloomington, IN 47405
Lab
link to come
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What I do
I study how people make judgments and decisions; how these processes shape behavior at the individual, group, and organizational level; and how we can help people make better judgments and decisions. I investigate these questions with computational modeling and methods from the behavioral, cognitive, and neuro- sciences. When I’m not at my desk you can find me running, biking, rowing, or out in the woods. In a parallel world, I own my own bike shop in the Midwest.
2014–
Senior Research Scientist
MAX PLANCK INSTITUTE
I help lead an interdisciplinary research center composed of 30 researchers studying how individuals and groups search for information and make decisions when time and resources are limited. At the Center, I also train researchers in computational modeling and advanced statistics because I believe when used wisely mathematics brings structure to scientists’ thinking.
2007–2014
Associate Professor (2013–14)
Assistant Professor (2007–13)
MICHIGAN STATE UNIVERSITY
As a member of the psychology department, I directed a laboratory focused on developing and testing computational models of judgment and decision making. Key accomplishments include earning an NSF CAREER Award and being named the MSU College of Social Science Outstanding Teacher in 2013.
2006-2007
NIMH Postdoctoral Research Fellow
Cognitive Science Program
INDIANA UNIVERSITY
Bloomington, Indiana
2014–
Senior Research Scientist
2006-2007
NIMH Postdoctoral Research Fellow
Cognitive Science Program
INDIANA UNIVERSITY
Bloomington, Indiana
2023–
Professor (2023– )
INDIANA UNIVERSITY BLOOMINGTON
In August, I joined the Department of Psychological and Brain Sciences.
2018–2023
Professor (2018–23)
Department Chair (2022–23)
I was the Program Director for the Brain, Behavior, & Quantitative Science Graduate Program, & director of the KU Behavioral Science Laboratory. At KU, I established a data science curriculum for undergraduate students.
2014–
Adjunct Researcher (2018– )
Senior Research Scientist (2014 –18)
MAX PLANCK INSTITUTE
I helped lead an interdisciplinary research center–the Center for Adaptive Rationality–composed of 30 researchers studying how individuals and groups search for information and make decisions when time and resources are limited. At the center, I also trained researchers in computational modeling and advanced statistics because I believe when used wisely mathematics brings structure to scientists’ thinking.
2007–2014
Associate Professor (2013–14)
Assistant Professor (2007–13)
As a member of the psychology department, I directed a laboratory focused on developing and testing computational models of judgment and decision making. Key accomplishments include earning an NSF CAREER Award and being named the MSU College of Social Science Outstanding Teacher in 2013.
2000–2004
Psychology, M.S., Ph.D.
UNIVERSITY OF MARYLAND – COLLEGE PARK
Under my adviser Dr. Tom Wallsten, I studied experimental psychology with a particular focus on mathematical models of cognition. My dissertation used mathematical models of risky decision making to develop laboratory-based gambling tasks that could be used to identify and measure differences in people who take real-world risks (e.g., drug use).
1996–2000
Psychology, B.S., cum laude
In addition to a B.S. in Psychology, I minored in Philosophy, Economics, and Political Science. My honors thesis focused on the effect of body temperature on time and visual perception and was done under the advisement of Dr. Mark Blumberg. I also ran on Iowa's cross country and track teams. My senior year I was named co-captain of the cross country team.
COMPUTATIONAL DECISION SCIENCE
Decisions, almost by definition, link our thoughts to our actions. My research uses computational models to characterize this critical link forcing us to specify the mental processes (i.e., memory, learning, or reward evaluation) involved in making a decision, the environments those choices take place in, and the interaction between the person and the environment. By taking this approach, we develop a better understanding of how the mind works and formulate mathematical models to help individuals, groups, and organizations, make better decisions.
DELIBERATION
How do people form a belief or a preference? I have investigated this question from many different angles from perceptual decisions to economic decisions to confidence judgments to probabilistic forecasts. Across these domains, my work has shown a similar deliberation process is at work where samples of information are sequentially sampled about the object or event in question and accumulated over time. Our understanding of this evidence accumulation process is precise enough that in controlled laboratory settings we can predict the choices people will make, the time it will take to make them, and the confidence they will have in them.
CHOICE ENVIRONMENTS
The decisions people make are shaped as much by their own psychological processes as the choice environments they make their decisions in. The question then is what are the critical properties of these choice environments, and how are these structures used to make decisions? In Berlin we have been working to understand how people use the relationship between risks and rewards to make decisions. This has led us to study why the inverse relationship between risks and rewards is so prevalent (it isn't simply due to economic forces), and how people use this relationship to make inferences about the chances of different outcomes.
TRANSLATIONAL MODELING
Often computational models in psychology are used to understand behavior in specific laboratory tasks. I am interested in translating these computational models from the laboratory into tools for identifying and improving problematic decision making. In this area, I have worked to use computational models to identify decision making deficits among real world risk takers like drug users, to identify critical events or shocks that lead students to quit school, and more recently understand a police officer's decision to shoot and the role a suspect's race can play in the decision.
RESEARCH AWARDS
– Jane Beattie Scientific Research Award for Innovative Research, European Association for Decision Making, 2015
– National Science Foundation CAREER Award, 2010
– Hillel Einhorn Young Investigator Award, Society for Judgment and Decision Making, 2008
Book
Hertwig, R., Pleskac, T. J., Pachur, T, & the Center for Adaptive Rationality (2019). Taming Uncertainty. MIT Press: Cambridge, MA. https://mitpress.mit.edu/books/taming-uncertainty
Recent manuscripts and publications
Pleskac, T. J., Kyung, E., Chapman, G. B., & Urminsky, O. (2024). Blinded versus unblinded review: A field study comparing the equity and fairness of review processes (Preprint). https://doi.org/10.31234/osf.io/q2tkw
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​Adaryukov, J. A., Biernat, M., Girard, J. M., Villicana, A. J., & Pleskac, T. J. (2023, August 7). Worth the Weight: An Examination of Unstructured and Structured Data in Graduate Admissions. https://doi.org/10.31234/osf.io/j9yeq
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Tump*, A. N., Deffner, D., Pleskac, T. J., Romanczuk, P., & Kurvers, R. H. (2024). A cognitive computational approach to social and collective1 decision-making. Perspectives on Psychological Science. https://doi.org/ 10.1177/17456916231186964
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Epping, G. P., Kvam, P. D., Pleskac, T. J., & Busemeyer, J. R. (2023). Open system model of choice and response time. Journal of choice modelling, 49, 100453. https://doi.org/10.1016/j.jocm.2023.100453
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Cai, X., & Pleskac, T. J. (2023). When alternative hypotheses shape your beliefs: Context effects in probability judgments. Cognition, 231, 105306. https://doi.org/10.1016/j.cognition.2022.105306
Pleskac, T. J., Yu, S., Grunevski, S., & Liu, T. (2023). Attention biases preferential choice by enhancing an option’s value. Journal of Experimental Psychology: General, 152(4), 993–1010. https://doi.org/10.1037/ xge0001307
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Adaryukov*, J., Grunevski, S., Reed, D. D., & Pleskac†, T. J. (2022). I’m wearing a mask, but are they?: Perceptions of self-other differences in covid-19 health behaviors. PloS one, 17(6), e0269625. https://doi.org/10.1371/journal.pone.0269625
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Lasagna, C. A.*, Pleskac, T. J., Burton, C. Z., McInnis, M. G., Taylor, S. F., & Tso, I. F. (2022). Mathematical Modeling of Risk-Taking in Bipolar Disorder: Evidence of Reduced Behavioral Consistency, With Altered Loss Aversion Specific to Those With History of Substance Use Disorder. Computational Psychiatry, 6(1), 96–116. http://doi.org/10.5334/cpsy.61
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Wu, C. M., Schulz, E., Pleskac, T. J., & Speekenbrink, M. (2022). Time pressure changes how people explore and respond to uncertainty. Scientific reports, 12(1), 4122. https://doi.org/10.1038/s41598-022-07901-1
Ravizza, S. M., Pleskac, T. J., & Liu, T. (2021). Working memory prioritization: Goal-driven attention, physi- cal salience, and implicit learning. Journal of Memory and Language, 121, 104287. https://doi.org/10.1016/ j.jml.2021.1042
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Kvam, P. D., Busemeyer, J. R., & Pleskac, T. J. (2021). Temporal oscillations in preference strength provide evidence for an open system model of constructed preference. Scientific Reports, 11(1), 1–15. https://doi.org/10.1038/s41598-021-87659-0
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Pleskac, T. J., Conradt, L., Lueker, C., & Hertwig, R. (2021) The ecology of competition: A theory of risk-reward environments in adaptive decision making. Psychological Review, 128, 315–335 https://doi.org/10.1037/rev0000261
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​Tump, A. N., Pleskac, T. J., & Kurvers, R. (2020). Wise or mad crowds? The cognitive mechanisms underlying information cascades. Science Advances. https://doi.org/10.31234/osf.io/6vt2p
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Busemeyer, J. R., Kvam, P. D., & Pleskac, T. J. (2020). Comparison of Markov versus quantum dynamical models of human decision making.
WIREsCognitiveScience.
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Leuker, C., Samartzidis, L., Hertwig, R., & Pleskac, T.J. (2020).When money talks: Judging risk and coercion in high-paying clinical trials. PloSone,
15 (1),e0227898. https://doi.org/10.1371/journal.pone.0227898
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Albrecht, R., Hoffmann, J. A., Pleskac, T. J., Rieskamp, J., & von Helversen, B. (2020). Competitive retrieval strategy causes multimodal response distributions in multiple-cue judgments. Journal of Experimental Psychology: Learning, Memory, and Cognition, 46(6), 1064. https://doi.org/10.1037/xlm0000772
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Litvinova,A.,Herzog,S.M.,Kall,A.A.,Pleskac,T.J.,&Hertwig,R.(2020). How the"wisdom of the inner crowd" can boost the accuracy of confidence judgments. Decision, 46(6), 183–211. https://doi.org/10.1037/ dec0000119
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Leuker, C.*, Pachur, T., Hertwig, R., & Pleskac, T. J.† (2020) Do People Exploit Risk–Reward Structures To Simplify Information Processing in Risky Choice? Journal of the Economic Science Association 5(1), 76–94. https://doi.org/10.1007/s40881-019-00073-1
Dai, J.*, Pachur, T., Pleskac, T. J., & Hertwig, R. (2019). What the future holds and when: A description-experience gap in intertemporal choice. Psychological Science, 30(8), 1218–1233. https://doi.org/10.1177/ 0956797619858969
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Leuker, C.*, Pachur, T., Hertwig, R., & Pleskac, T. J. (2019). Too good to be true? Psychological responses to surprising options in risk–reward environments. Journal of Behavioral Decision Making. 32, 346–358. https://doi.org/10.1002/bdm.2116
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Busemeyer, J.R., Kvam, P., & Pleskac, T.J. (2019). Markov versus quantum dynamic models of belief change during evidence monitoring.
ScientificReports, 9 (1),1–10. https://doi.org/10.1038/s41598-019-54383-9
Bhatia, S., & Pleskac, T. J. (2019). Preference accumulation as a process model of desirable ratings. Cognitive Psychology, 109, 47-67. https://doi.org/10.1016/j.cogpsych.2018.12.003
Pleskac, T. J., Yu, S.*, Hopwood, C., & Liu, T. (2019). Mechanisms of deliberation during preferential choice: Perspectives from computational modeling and individual differences. Decision, 6, 77-107. http://dx.doi.org/10.1037/dec0000092
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Schürman, O.*, Frey, R., & Pleskac, T. J.† (2019) Mapping risk perceptions in dynamic risk-taking environments Journal of Behavioral Decision Making, 32, 94-105. https://doi.org/10.1002/bdm.2098
Johnson, D. J.*, Cesario, J., & Pleskac, T. J. (2018). How Prior Information and Police Experience Impacts Decisions to Shoot. Journal of Personality & Social Psychology, 115(4), 601-623. http://dx.doi.org/10.1037/pspa0000130
Hertwig, R., & Pleskac. T. J. 2018). The construct-behavior gap and the description-experience gap: Comment on Regenwetter & Robinson (2017). Psychological Review, 125(5), 844-849. http://dx.doi.org/10.1037/rev0000121
Dai, J.*, Pleskac, T. J., & Pachur T. (2018) Dynamic cognitive models of intertemporal choice. Cognitive Psychology, 104, 29-56. https://doi.org/10.1016/j.cogpsych.2018.03.001
Leuker, C.*, Pachur, T., Hertwig, R., & Pleskac, T. J.† (2018). Exploiting risk-reward structures in decision making under uncertainty. Cognition, 175, 186-200. https://doi.org/10.1016/j.cognition.2018.02.019
Pleskac, T. J., Cesario, J., & Johnson, D.J.* (2018). How race affects evidence accumulation during the decision to shoot. Psychonomic Bulletin & Review. https://doi.org/10.3758/s13423-017-1369-6
Leuker, C.*, Pleskac, T. J., Pachur, T., & Hertwig, R. (2017). How the mind exploits risk-reward structures in decisions under risk. Proceedings of the 39th Annual Conference of the Cognitive Science Society.
Dai, J.*, Pleskac, T. J., & Pachur, T., (2017). A dynamic tradeoff model of intertemporal choice. Proceedings of the 39th Annual Conference of the Cognitive Science Society.
Kvam, P. D.*, & Pleskac, T. J. (2017). A quantum information architecture for cue-based heuristics. Decision, 4, 197–233. http://dx.doi.org/10.1037/dec0000070
Johnson, D.*, Hopwood, C., Cesario, J., & Pleskac, T. J. (2017). Advancing research on cognitive processes in social and personality psychology: A drift diffusion model primer. Social Psychological and Personality Science, 8, 413–423. https://doi.org/10.1177/1948550617703174
Kvam, P. D.*, & Pleskac, T. J. (2016). Strength and weight: The determinants of choice and confidence. Cognition, 152, 170–180. http://dx.doi.org/10.1016/j.cognition.2016.04.008
Uitvlugt, M. G., Pleskac, T. J., & Ravizza, S. M. † (2016). The nature of working memory gating in Parkinson’s Disease: A multi-domain signal detection examination. Cognitive, Affective, and Behavioral Neuroscience, 16, 289–301. http://dx.doi.org/10.3758/s13415-015-0389-9
Pleskac, T. J., (2015). Learning models in decision making. In G. Keren & G. Wu (Eds.), The Wiley Blackwell Handbook of Judgment & Decision Making (pp.629–657). Chichester, United Kingdom: John Wiley & Sons. http://dx.doi.org/10.1002/9781118468333.ch22
Pleskac, T. J., Diederich, A., & Wallsten, T. S. (2015). Models of decision making under risk and uncertainty. In J. R. Busemeyer, J. T. Townsend, Z. J. Wang, & A. Eidels (Eds.), Oxford Handbook of Computational and Mathematical Psychology (pp. 209–231). New York, NY: Oxford University Press. http://dx.doi.org/10.1093/oxfordhb/9780199957996.013.10
Kvam, P. D.*, Pleskac, T. J., Yu, S.,* & Busemeyer, J. R. (2015). Interference effects of choice on confidence: Quantum characteristics of evidence accumulation. Proceedings of the National Academy of Sciences, 112, 10645–10650. http://dx.doi.org/10.1073/pnas.1500688112
Yu, S.*, Pleskac, T. J., & Zeigenfuse, M.* (2015). Dynamics of postdecisional processing of confidence. Journal of Experimental Psychology: General, 144, 489–510. http://dx.doi.org/10.1037/xge0000062
Pleskac, T. J., & Hertwig, R. (2014). Ecologically rational choice and the structure of the environment. Journal of Experimental Psychology: General, 143, 2000–2019. http://dx.doi.org/10.1037/xge0000013
Zeigenfuse, M.*, Pleskac, T. J., & Liu, T. (2014). Rapid decisions from experience. Cognition, 131, 181–194. http://dx.doi.org/10.1016/j.cognition.2013.12.012
Pleskac, T. J., & Wershbale, A.* (2014). Making assessments while taking repeated risks: A pattern of multiple response pathways. Journal of Experimental Psychology: General, 143, 142–162. http://dx.doi.org/10.1037/a0031106
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Order of authorship is in terms of contribution. I typically give students priority in authorship order.
* graduate student or post doc
† alternative ordering with last author being senior author
COURSES
Decision Sciences
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Behavioral Economics
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Negotiation Theory
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Behavioral Game Theory
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Computational Models
of Decision Making
Quantitative Methods
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Data Science (Undergraduate & Graduate)
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Statistics (Undergraduate & Graduate)
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Research Design and Methods
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Bayesian Data Analysis
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Computational Modeling
Cognitive Science
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Cognitive Modeling
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Higher-Order Cognitive Processes
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Current Topics in Cognitive Science
Teaching Awards
– Michigan State University, College of Social Science Alumni Association Outstanding Teaching Award, 2013
– University of Maryland Distinguished Teaching Assistant, 2002