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Manikya Alister
PhD Candidate The University of Melbourne
I’m a PhD candidate in computational cognitive science at the Complex Human Data Hub within the Melbourne School of Psychological Sciences. I also work casually as a freelance data scientist and academic tutor (TA).

About Me

I build experiments and develop computational models to explain and predict how people learn and make decisions.

I’m due to finish my PhD mid-late 2025 and am looking for a postdoc. If your lab is hiring or you know of a position or fellowship that I would be a good fit for, please get in touch.

Academic Research

I have research and teaching experience across several areas including psychology, neuroscience, and statistics (check out the “CV” tab to see more detail).

I have broad interests, but most of my current research is focused on understanding how we learn and reason from social information, particularly in online contexts like on social media. Some questions I am currently focusing on include:

  • What kinds of assumptions do we make about the people that we learn from and why?
  • Under what circumstances are we more or less persuaded by social testimony?
  • What happens to our cognitive mechanisms over time as we learn to trust/distrust someone?
  • How do people integrate information from multiple sources to decide what to believe?

I have also published in other areas such as perceptual decision-making, social cognition, goal prioritisation, and meta-science. In 2020 I graduated with a Bachelor of Psychological Science (Honours) from the University of Queensland (UQ). In my Honours year I won the McElwain prize for the best Honours thesis in Psychology and also graduated top of my cohort, winning the Australian Psychological Society Prize for UQ and a University Medal.

Data Science

I have experience building powerful, interactive data capabilities. I have worked with the Good Data Institute to consolidate their internal database of volunteers and automate their intake processes. I also designed and deployed a web-based dashboard using R shiny that informs and visualizes several aspects of their organisation including the diversity and equity of their volunteers and project impact (see this blog post I wrote about the project). I also worked with the University of Adelaide and the Defense Science and Technologies Group to build a software prototype that leverages state of the art NLP techniques like BERTopics and other transformer based tools, and powerful data visualization libraries such as JavaScript’s D3, to analyse how narratives emerge and spread across social media.

Skills

  • Research design
  • Data analysis
  • Statistical & computational modelling
  • Software and data engineering
  • Data visualisation
  • Bayesian inference
  • Public speaking
Publications
Alister, M., Ransom, K.J., Connor-Desai, S., Soh, E.V., Hayes, B., Perfors, A. (2025). How convincing is a crowd? Quantifying the persuasiveness of a consensus across individuals and claim types. Provisionally accepted at Psychological Science.
Alister, M., Perfors, A. (accepted). Stochastic search algorithms can tell us who to trust (and why). Proceedings of the Annual Meeting of the Cognitive Science Society, 46(46).
Alister, M., Ransom, K.J., Lua, A., Perfors, A. (accepted). The impact of engagement and partisan influence campaigns in an isolated social media environment. Proceedings of the Annual Meeting of the Cognitive Science Society, 46(46).
Alister, M., Ransom, K.J., Connor-Desai, S., Soh, E.V., Hayes, B., Perfors, A. (2024). Sensitivity to Online Consensus Effects Within Individuals and Claim Types. Proceedings of the Annual Meeting of the Cognitive Science Society, 46(46). Link.
Alister, M., Herbert, S., Sewell, D.K., Neal, A., Ballard, T.J. (2024). The Impact of Cognitive Resource Constraints on Goal Prioritization. Cognitive Psychology, 148. Link.
Alister, M., Ransom, K.J., Perfors, A. (2023). Inferring the truth from deception: What can people learn from helpful and unhelpful information providers? Proceedings of the Annual Meeting of the Cognitive Science Society, 45(45). Link.
Alister, M., McKay, K.T., Sewell, D.K., Evans, N.J. (2023). Uncovering the Cognitive Mechanisms Underlying the Gaze Cueing Effect. Quarterly Journal of Experimental Psychology, 803–827. Link.
McKay, K.T., Grainger, S.A., Alister, M., Henry, J.D. (2023). Enhancing ecological validity of gaze-cueing stimuli is associated with increased gaze following for older but not younger adults. Psychology and Aging, 38(6), 562–572. Link.
Grainger, S.A., Henry, J.D., Alister, M., Bourdaniotis, X.E., Mead, J., Bailey, T.G., Coombes, J.S., Vear, N. (2023). Cardiorespiratory fitness and muscular strength do not predict social cognitive capacity in older age. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 1824–1833. Link.
Alister, M., Ransom, K.J., Perfors, A. (2022). Source independence affects argument persuasiveness when the relevance is clear. Proceedings of the Annual Meeting of the Cognitive Science Society, 44(44).

Under Review

Alister, M., Ransom, K. J., Perfors, A. (2023). When a helpful bias is unhelpful: Limitations in reasoning about random and deliberately misleading evidence. Preprint.
Alister, M., Evans, N. J. ParAcT-DDM: A diffusion-based framework for modelling systematic, time-varying cognitive processes. In revision at Psychological Review. Preprint.

Non-academic publications and articles featuring my research

Alister, M. (2022). How does an organisation of data professionals leverage its own data? Good Data Institute. Link.
Wilcox, C. (2023). The life academic: Getting your priorities straight, with a little help from science. Science Advisor. Link.

CV