Neil Bramley

Lecturer

  • Psychology Department
  • School of Philosophy, Psychology and Language Sciences
  • College of Arts, Humanities & Social Sciences

Contact details

Address

Street

Room S2, Psychology Building

City
7 George Square, Edinburgh
Post code
EH8 9JZ

Availability

Biography

Background

I am interested in higher level cognition, particularly how people represent the world and think about its alternatives, plus how they use these abilities to plan, imagine, explain, blame and solve problems. I generally use interactive online experiments and games combined with computational modelling to investigate these issues.

CV

PDF icon 92393.pdf

Qualifications

PhD Experimental Psychology; MRes Computer Science; MSc Cognitive & Decision Sciences; MA (Hons) Philosophy

Responsibilities & affiliations

Marketing Officer for Psychology Department

Undergraduate teaching

I teach PSYL10160 Causal Cognition (http://www.drps.ed.ac.uk/21-22/dpt/cxpsyl10160.htm).

 

 

Postgraduate teaching

In 2022/2023 I will be teaching on PPLS MSc Univariate Statistics (USMR, PSYL11099) and on a new MSc level Informatics Seminar in Cognitive Modelling.

I also do a module on Online Experimentation in the Psychological Research Skills Module.

Open to PhD supervision enquiries?

Yes

Areas of interest for supervision

I am keen to supervise MSc and PhD students interested in cognitive science related topics

Current PhD students supervised

PhD primary

PhD secondary

  • Simon Valentin (expected 2024)
  • Ella Markham (expected 2026)
  • Fahd Yasin (expected 2025)

PhD tertiary

  • Yuan Meng (Berkeley, graduated 2022)
  • Victor Btesh (UCL, expected 2025)
  • Susanne Haridi (Mac Planck Institute for Biological Cybernetics, Tübingen, expected 2025)

Research summary

Computational cognitive science. The goal of my research is to better understand the algorithms, processes and representations that underpin human intelligence. I generally approach this by developing computational theories of human learning representation and control, designing challenging and interactive tasks that distill elements of the challenges faced by natural cognition (see Demos) and having people and my models attempt to solve them. By comparing the behaviour of models to that of people, I try to gain insight into the mechanisms that people use to to solve problems and adapt their behaviour. As well as helping to understand human intelligence, insights from my research inform the development of artificial systems capable of learning and behaving in more flexible and human-like ways.

Causal cognition, active learning, hypothesis generation, control, judgment and decision making, resource rationality, game theory, optimal teaching, iterated learning, rational analysis, philosophy of mind, philosophy of science (see Research)

Research activities

View all 34 activities on Research Explorer

Current project grants

EPSRC New Investigator Grant investigating Computational Constructivism: The Algorithmic Basis of Discovery

View all 40 publications on Research Explorer

This article was published on