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Dan Navarro

Title Associate Professor
Phone +61 8 8303 5265
Office 5 09 Hughes Building

Like any cognitive scientist, my primary interest is learning how the mind works. In my case that translates into a mix of traditional experimental psychology and computational modelling work, with a little philosophy and machine learning on the side. I'm interested in lots of different topics in cognitive science, but the main ones would be:

Concept learning: How do people acquire rich knowledge of the world?

One of the major themes in my research is how people learn concepts and categories. My interest in this problem stems from the fact that I rely heavily on mathematical and computational models of cognition. Very frequently when I encounter a new learning or inference problem in everyday life or in the psychological literature, it turns out on close inspection to be very deeply related to an underlying categorisation problem. In that sense, the problem of assigning "things" to "kinds" is one of the most fundamental tasks facing an intelligent agent. Within this area I've been interested in several topics. I'm interested in discovering what kind of mental representations support the inferences we make (e.g., 1, 2, 3, 4, 5, 6) as well as the biases and assumptions underpin human learning (e.g., 1, 2) and reasoning (e.g., 1, 2, 3) by both adults and children. I'm interested in how the structure of the input shapes what people learn (e.g., 1, 2)

Decision making: How does knowledge translate into action?

Acquiring knowledge is only one half of the problem facing humans and other intelligent agents. The other half is using knowledge as a guide to action. For that reason, a second stream of work focuses on how people make decisions. My main area of interest in this field is understanding how people learn to make good choices in an uncertain and complex world (e.g., 1, 2, 3), and from that perspective I've tended to look mostly at "higher order" deliberative decisions. However, I've maintained an interest in the literature on simple choice problems, and some of my work has been in this area (e.g., 1, 2, 3)

Psychological methods: How do we learn about the mind?

A third area of research that I've been involved relates to psychological methodology and statistical inference. There's little point in doing empirical work or building computational models if you lack the tools to properly assess your hypotheses. With that in mind, my work in this areas has focused on using Bayesian and information theoretic tools to draw better inferences from data (e.g. 1, 2, 3, 4), with particular reference to inferring latent mental representations from empirical data (e.g, 1, 2, 3, 4). In recent work I've become interested in the potential that big data has in psychology (e.g., 1) and in making use of online data collection tools (e.g., 1, 2, 3). Over the last few years I've become quite enthusiastic about using R as a tool for teaching statistics to undergrad psychology students, and wrote my own textbook with that in mind (1)

Applications: What can we use this research for?

Most of my work is basic science, but I dabble in applied work every now and again. I've looked at the role that psychological theory can play in understanding cognitive biases in gambling (e.g., 1, 2), in improving information retrieval and data visualisation (e.g., 1, 2, 3) and others. Some of this work involved only academic collaborators, but in other instances it's involved working with industry partners in areas as diverse as petroleum, telecommunications and defence.

Here's the complete list of my refereed publications, with links to the full version of papers included where possible (our copyright notes page covers the legal details).


  • A Hendrickson, A Perfors and DJ Navarro (submitted). Categorization and generalization: A curious discrepancy with increasing sample size. Manuscript submitted for publication
  • L Kennedy, DJ Navarro, A Perfors and N Briggs (submitted). On the use of clinical scales in non-clinical populations: A discussion of the analysis of skewed responses. Manuscript submitted for publication
  • L Kennedy, DJ Navarro, A Perfors and N Briggs (submitted). Not every credible interval is credible: On the importance of robust methods in Bayesian data analysis. Manuscript submitted for publication
  • A Perfors, DJ Navarro, C Donkin and T Benders (submitted). Poor statistical inference or good social reasoning? On the pragmatics of the Monty Hall dilemma. Manuscript submitted for publication

In Press









Here's a list of classes that I have taught over the last few years. The link to the Computational Cognitive Science class is worth checking out: we've placed a lot of content there.

Cognitive Modelling

Statistics Classes

  • Doing Research in Psychology II, 2014 (Statistics)
  • Doing Research in Psychology II, 2012 (Statistics)
  • Doing Research in Psychology II, 2011 (Statistics)

Cognitive Psychology

  • Perception & Cognition III, 2010 (Categorisation)
  • Perception & Cognition III, 2009 (Categorisation)
  • Cognition III, 2008
  • Cognition III, 2007
  • Decision-Making in Real Environments VII, 2006
  • Perception & Cognition III, 2006 (Cognition)
  • Psychology II, 2006 (Language).
  • Perception & Cognition III, 2005 (Cognition)

Below is a partial list of the code associated with some of my papers. I'm in the process of switching to git, so all the newer stuff will appear as a git repository on my bitbucket page.


  • Bayesian generalisation [code]
  • Bayesian additive clustering [code]
  • Dirichlet process mixture model [code]
  • Clustering using NML [code]
  • Wiener first passage time densities [code]
  • Geometric complexity for categorisation models [code]

Employment History

  • Future Fellow and Associate Professor (Level D), University of Adelaide (2013-present)
  • Future Fellow and Senior Lecturer (Level C), University of Adelaide (2012)
  • Australian Research Fellow and Senior Lecturer (Level C), University of Adelaide (2009-2012)
  • Australian Research Fellow and Lecturer (Level B), University of Adelaide (2007-2009)
  • Lecturer Level B in Psychology, University of Adelaide (2006)
  • Australian Postdoctoral Fellow, University of Adelaide (2004-2006)
  • Postdoctoral Researcher, Ohio State University (2002-2004)


  • Ph.D. in Psychology, University of Adelaide (1999-2003)
  • Honours First Class in Psychology, University of Adelaide (1998)
  • Bachelor of Social Science, University of Adelaide (1994-1997)

Publications / Citations

See here and here

National Competitive Grants

  • Navarro, DJ & Lee, MD (2015-2018). Learning and choosing in a complex world. ARC Discovery Project DP150104206. Value: $330,000
  • Navarro, DJ (2012-2016). How is information represented in the mind? Learning structured mental representations from data. ARC Future Fellowship FT110100431. Value: $608,000
  • Navarro, DJ, Perfors, AF & Tenenbaum, J (2011-2014). How are beliefs altered by data? Robust Bayesian models for human inductive inference. ARC Discovery Project DP110104949. Value: $445,000.
  • Navarro, DJ (2007-2011). Hierarchical Bayesian models for human conceptual learning. ARC Discovery Project DP0773794. Value: $510,000.
  • Navarro, DJ, Lee, MD & Maio Mackay, M (2005-2007). Psychological user profiling in the telecommunications industry. ARC Linkage Project LP0562206. Value: $449,000.
  • Lee, MD & Navarro, DJ (2004-2006). Extending cognitive models to account for individual differences. ARC Discovery Project DP0451793. Value: $230,000.

Research Contracts, Consultancies and Small Grants

  • Navarro, DJ (2015). Introduction to R. Consultancy with DSTO Value: $6000.
  • Ma-Wyatt, A, Burns, N, Dunn, J & Navarro, DJ (2014). Equipment grant. School of Psychology RIBG Large Grant Scheme. Value: $27,000.
  • Navarro, DJ (2013). Introduction to R. Consultancy with CSIRO Value: $2500.
  • Navarro, DJ (2007). Decision-making experiments in an oil & gas context. Research agreement with the Australian School of Petroleum, University of Adelaide; original funds from Exxon & Santos. Value: $35,000.
  • Navarro, DJ (2007). Review of the social network analysis literature. Research contract with Defense Research and Development Canada. Value: $22,000.
  • Navarro, DJ (2005). Human similarity judgments on email. Research contract with Australian Defence Science and Technology Organisation. Value: $33,000.


  • Executive Dean's Teaching and Learning Prize (2013). Awarded by the Faculty of Health Sciences at the University of Adelaide.
  • William K Estes New Investigator Award (2007). Awarded by the international Society for Mathematical Psychology to early career researchers
  • Frank Dalziel Prize (2003). Awarded to Ph.D. thesis "Representing Stimulus Similarity", for best contribution to experimental or behavioural psychology at the University of Adelaide.
  • Australian Psychological Society Prize (1998). Best psychology Honours thesis at the University of Adelaide, "Parallel Forms of the Trailmaking Test and Their Relationship to the Perception of Optimal Structure".

Conferences/Workshops Organised

  • Australasian Experimental Psychology Conference. April 2013
  • Australian Mathematical Psychology Conference. February 2012
  • Leuven Workshop on Natural Language Concepts. June 2008
  • Adelaide Mental Life 2. June 2005
  • Adelaide Mental Life 1. December 2004
  • Hoosier Mental Life. June 2004
  • OSU Workshop on Model Selection in the Real World. June 2004

Talks, Invited or Otherwise

I don't keep track of these at the moment.

Teaching Record

  • 2014: Doing Research in Psychology II.
  • 2014: Computational Cognitive Science III.
  • 2014: Honours Research Methods (One Seminar).
  • 2012: Doing Research in Psychology II (SELT broad approval rate: 97%)
  • 2012: Computational Cognitive Science III (SELT data unavailable)
  • 2011: Doing Research in Psychology II (SELT broad approval rate: 96%)
  • 2011: Computational Cognitive Science III (SELT data unavailable)
  • 2010: Perception & Cognition III (SELT broad approval rate: 100%)
  • 2010: Computational Cognitive Science III (SELT data unavailable)
  • 2009: Perception & Cognition III (SELT broad approval rate: 100%)
  • 2008: Cognition III (SELT broad approval rate: 93%)
  • 2007: Cognition III (SELT broad approval rate: 95%)
  • 2006: Psychology II, Language lectures. (SELT broad approval rate: 89%)
  • 2006: Decision Making in Real Environments VII. (SELT broad approval rate: 100%)
  • 2006: Perception & Cognition III. (SELT broad approval rate: 92%)
  • 2005: Perception & Cognition III. (SELT broad approval rate: 100%)

Ph.D. Theses Supervised

  • Gokaydin, D. (2015). The structure of sequential effects.
  • Ejova,A. (2013). The illusion of control: Influencing factors and underlying psychological processes
  • Stephens, R. (2013). The selection and integration of information to guide induction reasoning
  • Maurits, L (2012). Representation, information theory and basic word order.
  • Pattinson, M (2012). An examination of information system risk perception using the repertory grid technique
  • Stone, B (2010). The development and assessment of the semantic fields model of visual salience.
  • Gilliland, V (2010). Decision making in civil disputes: The effect of role and frame.

Masters Theses Supervised

  • Dobson-Keeffe, N (2007). Evaluation of virtual advisor effectiveness in short story narration
  • Dunn, M (2011). Designing visualisations for military commanders
  • Wong, M (2011). Heuristical approaches for a tableau-based intelligent agent

Honours Theses Supervised

  • Wong, W. K. (2012). Category learning in a dynamic environment
  • Nettle, F (2011). What makes a good decision maker? Individual difference correlates of confidence and accuracy in a decision making task with varied stimuli distribution.
  • Mackrill, K (2010). The limit of selective attention in categorisation: A local or global phenomenon?
  • Sim, XW (2009). Label, behaviour and causal relation: The role of category indicators on inductive generalization and classification,
  • Colebatch, N (2009). Confirmation pays off: positive evidence is most useful for learning number rules.
  • De Vel, M (2009). The effect of domain type on the simplicity bias in categorisation.
  • Anderson, L (2009). Opening new doors: Measuring desire for flexibility with alternate option choices.
  • Chen, X (2009). People's perceived value of options in a dynamically changing environment.
  • Langsford, S (2008). Gesture as a window into cognitive metaphor: Gesturing about time in Chinese and English.
  • Monaghan, S (2008). The framing effect under time pressure and its relationship to the overconfidence bias.
  • Doust, C (2007). How delay and temporal distribution influence the perceived present value of sequences of future benefits.
  • Gold, J (2007). Perception of randomness: The role of representativeness and availability in mental simulations and probability judgements.
  • Bruza, B (2007). A test of the decision-by-sampling account of decision making biases: Relating memory, intelligence and personality to framing and overconfidence.
  • Stephens, R (2006). On the psychological distinction between category labels and other category features.
  • Walwyn, A (2006). Investigating the roles of visual perception and intelligence in relation to the Travelling Salesperson Problem.

Former Postdoctoral Researchers

  • Wouter Voorspoels
  • Sean Tauber
  • Simon De Deyne
  • Kieran O'Doherty

Current Lab Members

See here.

Editorial Service

  • Behavior Research Methods (Associate Editor, 2014-present).
  • Cognitive Science (Associate Editor, 2011-2013)
  • Journal of Mathematical Psychology (Consulting Editor, 2010-present).
  • Cognitive Science (Board of reviewers 2009-2010)
  • Acta Psychologica (Guest editor, 2010)
  • Proceedings of the Annual Conference of the Cognitive Science Society (2010-2012 Program Committee)
  • Proceedings of the European Conference on Cognitive Science (2006, 2011 Program Committee)

Committees / Working Parties

  • School committee: Chair of research committee, 2015
  • School committee: Executive advisory committee, 2015
  • Faculty committee: Research committee, 2015
  • University researcher profiles reference group, 2014, 2015
  • School working party: Masters application process, 2014
  • School committee: Infrastructure committee 2014
  • School committee: Research committee. 2006, 2007, 2008, 2014
  • School working party: The psychology server. 2013.
  • Faculty working party: Postdoctoral recruitment. 2012.
  • School working party: Computing & statistics. 2010.
  • School working party: Perception, cognition & neuropsychology curriculum. 2008
  • Faculty committee: Research career development. 2006
  • School committee: Occupational health & safety committee. 2007, 2008

Miscellaneous Administration

  • (Joint) Head of Brain and Cognition Research Group. 2014, 2015
  • Research management system, academic co-ordinator. 2010, 2011, 2012, 2013, 2014, 2015
  • School of psychology research report. 2008.
  • School of psychology seminar series organiser. 2006.
School of Psychology,
North Terrace Campus,
University of Adelaide

T: +61 8 8313 5744