Projects per year
Personal profile
Biography
Dr. Patrick Nalepka received his PhD in Experimental Psychology from the University of Cincinnati within the Center for Cognition, Action and Perception. During graduate study, Dr. Nalepka's research focused on investigating the perceptual-motor processes that underlie the emergence of stable coordinative patterns in complex and dynamic multiagent task contexts, as well as the role constraints play in how such patterns materialize. Since joining Macquarie, his focus has been on investigating the effects embodied artificial-agents (e.g., virtual avatars, robots) have in mixed human-artificial agent teams for coordination, and how such artificial systems should be used to enhance human skill acquisition in perceptual-motor tasks undergoing continual perturbations. Dr. Nalepka's research utilizes nonlinear time-series analyses, dynamical modeling, reinforcement and machine learning, and virtual reality technology.
Research interests
Multiagent Interaction; Coordination Dynamics; Ecological Psychology; Human-Machine Interaction; Complex Adaptive Systems
Research engagement
International Research Collaborators
University of Cincinnati
Cincinnati Children's Hospital Medical Center
Teaching
(2016) Sensation & Perception (University of Cincinnati, Instructor)
Community engagement
Media Mentions of Research
(2016) Research on goal-directed multiagent "shepherding" referenced on the Brain Science podcast, Ep. 123
(2015) Research referenced on WCPO Cincinnati titled “Checkups: Concussions, teens and cars – when is it safe to drive again?"
(2015) Research referenced on WCPO Cincinnati titled “Studying effects of concussions on teen drivers.”
Education/Academic qualification
Psychology, PhD, University of Cincinnati
27 Aug 2013 → 31 Jan 2018
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Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Visual search dynamics and image complexity in radiology
Nalepka, P., Carrigan, A. & Di Ieva, A.
8/06/19 → 21/12/19
Project: Research
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MQRSG: Targeting body size misperception and attentional bias to reduce body dissatisfaction in young people
Stephen, I., Stevenson, D., Brooks, K., Nalepka, P., Richardson, M., Mond, J., Hay, P. J. & Fardouly, J.
1/01/19 → 31/12/21
Project: Other
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Audio-Video Observation, Recording, Analysis and Conferencing Infrastructure
Richardson, M., Wuthrich, V., Kallen, R., Norberg, M., Reichle, E., Wiggins, M., Sutton, J., Nalepka, P., Rigoli, L., Douglas, H., Pini, S., Mingon, M., Falkland, E., Wolters, N., Kwok, C. & Auletta, F.
1/01/19 → 31/12/19
Project: Other
Research Outputs
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Herd those sheep: emergent multiagent coordination and behavioral-mode switching
Nalepka, P., Kallen, R. W., Chemero, A., Saltzman, E. & Richardson, M. J., 1 May 2017, In: Psychological Science. 28, 5, p. 630-650 21 p.Research output: Contribution to journal › Article › peer-review
37 Citations (Scopus) -
A comparison of dynamical perceptual-motor primitives and deep reinforcement learning for human-artificial agent training systems
Rigoli, L., Patil, G., Nalepka, P., Kallen, R. W., Hosking, S., Best, C. & Richardson, M. J., Jun 2022, In: Journal of Cognitive Engineering and Decision Making. 16, 2, p. 79–100 22 p.Research output: Contribution to journal › Article › peer-review
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Dynamical perceptual-motor primitives for better deep reinforcement learning agents
Patil, G., Nalepka, P., Rigoli, L., Kallen, R. W. & Richardson, M. J., 2021, Advances in practical applications of agents, multi-agent systems, and social good: the PAAMS collection : 19th international conference, PAAMS 2021, Salamanca, Spain, October 6-8, 2021 : proceedings. Dignum, F., Corchado, J. M. & De La Prieta, F. (eds.). Cham, Switzerland: Springer, Springer Nature, p. 176–187 12 p. (Lecture notes in artificial intelligence; no. 12946).Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
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Gaze facilitates responsivity during hand coordinated joint attention
Caruana, N., Inkley, C., Nalepka, P., Kaplan, D. M. & Richardson, M. J., 26 Oct 2021, In: Scientific Reports. 11, 1, p. 1-11 11 p., 21037.Research output: Contribution to journal › Article › peer-review
Open AccessFile2 Downloads (Pure) -
How to train your Artificial Agents to be more human-like?
Patil, G., Nalepka, P., Kallen, R. W. & Richardson, M. J., 2021, p. 40. 1 p.Research output: Contribution to conference › Abstract