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
To arrange a meeting simply use one of these links to find a time when I am available:
https://calendly.com/neil-bramley/15min (over Teams or Zoom)
https://calendly.com/neil-bramley/15-min-in-person
https://calendly.com/neil-bramley/30min (over Teams or Zoom)
https://calendly.com/neil-bramley/30min-in-person
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
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 a new MSc-level Seminar in Cognitive Modelling and taking two Psychology General Tutorials.
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
-
Jan-Philipp Fränken (expected 2023)
-
Bonan Zhao (expected 2023)
-
Tianwei Gong (expected 2024)
-
Stephanie Droop (expected 2025)
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
Current project grants
EPSRC New Investigator Grant investigating Computational Constructivism: The Algorithmic Basis of Discovery
-
Algorithms of adaptation in inductive inference
In:
Cognitive Psychology
DOI: https://doi.org/10.1016/j.cogpsych.2022.101506
Research output: Contribution to Journal › Article (Accepted/In press) -
Categorizing perceived causal events
Research output: Contribution to Conference › Conference contribution (E-pub ahead of print) -
The Paradox of Time in Dynamic Causal Systems
In:
Entropy
Research output: Contribution to Journal › Article (Accepted/In press) -
Children's active physical learning is as effective and goal-targeted as adults'
In:
Developmental Psychology
Research output: Contribution to Journal › Article (Accepted/In press) -
Children’s failure to control variables may reflect adaptive decision making
In:
Psychonomic Bulletin & Review
Research output: Contribution to Journal › Article (Accepted/In press) -
Powering up causal generalization: A model of human conceptual bootstrapping with adaptor grammars
Research output: › Conference contribution (Accepted/In press) -
Intuitions and Perceptual Constraints on Causal Learning from Dynamics
Research output: › Conference contribution (Accepted/In press) -
Inferring epistemic intention in simulated physical microworlds
Research output: › Conference contribution (Accepted/In press) -
Categorizing perceived causal events
Research output: › Conference contribution (Accepted/In press) -
Redressing the Emperor in Causal Clothing: Commentary on 'The Emperor's New Markov Blankets' by Bruineberg, Dolega, Dewhurst and Baltieri
In:
Behavioral and Brain Sciences
Research output: Contribution to Journal › Comment/debate (Accepted/In press) -
How do people generalize causal relations over objects? A non-parametric Bayesian account
(23 pages)
In:
Computational Brain and Behavior
DOI: https://doi.org/10.1007/s42113-021-00124-z
Research output: Contribution to Journal › Article (E-pub ahead of print) -
Bayesian Optimal Experimental Design for Simulator Models of Cognition
(10 pages)
Research output: Contribution to Workshop › Conference contribution (Accepted/In press) -
Observing effects in various contexts won’t give us general psychological theories
DOI: https://doi.org/10.31234/osf.io/kpycz
Research output: › Other contribution (Published) -
Expectations about future learning influence moment-to-moment feelings of suspense
In:
Cognition and Emotion
DOI: https://doi.org/10.1080/02699931.2021.1932429
Research output: Contribution to Journal › Article (E-pub ahead of print) -
Limits on simulation approaches in intuitive physics
In:
Cognitive Psychology, vol. 127
DOI: https://doi.org/10.1016/j.cogpsych.2021.101396
Research output: Contribution to Journal › Article (Published)