Sean Riley


About

Not a lot to say here, really. Everything you need to know about anything can be found in hockey clichés... Get pucks in. Get pucks deep. Go to the hard areas and keep your stick on the ice.

Academics

    • Ph.D. in Cognitive Science, Carleton University (expected 2025)
    • Title: Visual Mental Imagery & Subjective Experiences: A Computational Perspective
    • Advisor: Jim Davies

    • B.A. in Psychology, University Of British Columbia

Research Interests

Subjective Experiences

The hard problem of consciousness is haunting. Somehow, syntactic operations over symbols makes manifest the subjective character of my existential dread as I ruminate on how syntactic operations over symbols makes manifest...

...The problem mocks my conceit like history does the present.

My current research has involved investigations into the symbols and operations that may be involved in subjective experience. Whatever computational machinery makes qualia possible, it's likely primitive to human-level intelligence. Understanding this machinery can give us valuable insights into how to build general intelligence in-silico.

There's also a more immediate aspect to this as well. People are largely driven by their subjective experiences, and modelling these experiences in specific domains can help us build useful technologies, such as rhetorical force detectors.

Paper

Visual Mental Imagery

The fact we can "see" things inside our mind is wild. Right now, you can close your eyes and visualize Nietzsche's moustache in a street brawl with Socrates' beard. That's absurd. How does the brain do this? What computations are involved and over what representations? Are visual mental images built of perceptual content, or experiential content? Does this change the underlying computations? If so, how? And what even is vividness? It seems to be cut from the same cloth as pornography: we can't define it, but we know it when we see it.

My current work has explored a novel conception of vividness built on the idea that visual imagery involves representations that carry experiential content, and that when we visualize this street brawl, we are visualizing the experience of seeing it.

Paper

Corporate Compliance

Most business owners want to be compliant with relevant legislation. How can we help them, particularly when it comes to privacy? Homomorphic encryption is an exciting avenue that has the potential to break down data silos and help businesses utilize their data while still remaining compliant with privacy laws.

Current Projects

VMI: A spiking neural network model of visual mental imagery & subjective experiences

- Developed a novel model of vividness

- Developed a novel model of qualia

- Built spiking neural network

- Managed experiments & data

Tech Stack: Python, Git

Target Thesis Defense: Spring, 2025

Parabasis: A content advisory system for the internet

- Developed novel ML algorithms for rhetoric detection and theme detection

- Built advisory system

- Built backend api, datalayer, and web server

- Built website frontend

- Deployed and maintained all cloud infrastructure

Tech Stack: Go, Python, Flutter/Dart, Git, Docker, AWS

Status: public beta

Requires: bug fixes and UI update

Target Release: Summer, 2025

Verb Phrase: A social media app that only kinda sucks

- Designed app

- Built backend api, datalayer, and web server

- Built app client (Android, iOS, macOS, Windows)

- Built website frontend

- Deployed and maintained all cloud infrastructure

Tech Stack: Go, Python, Flutter/Dart, Git, Docker, AWS

Status: internal beta

Requires: bug fixes and UI update

Target Release: Summer, 2025

Homomorphic Encryption: Fancy ciphers!

- Developed novel use-cases for homomorphic encryption in the payments space

- Developed prototype for established payroll company

Tech Stack: C++, JS, HTML/CSS, Git, Docker

Status: internal prototype

Target Release: TBD

Publications

Riley, S.N. & Davies, J. (2023). Vividness as the similarity between generated imagery and an internal model. Brain & Cognition, 169, 105988.

Riley, S.N., Savelson, Z. & Singh, R. (2023). Cognitive primitives and bayesian number word learning. In Proceedings of the Annual Meeting of the Cognitive Science Society, (Vol. 45), pp. 2924-2930.

Riley, S.N. & Davies, J. (2020). A spiking neural network model of spatial and visual mental imagery. Cognitive Neurodynamics, 14(2), 239-251.

Riley, S.N. (2017). Investigating the multivariate nature of NHL player performance with structural equation modelling. PLoS One, 12(9), e0184346.

Porter, S., ten Brinke, L., Riley, S.N. & Baker, A. (2014). Prime time news: The influence of primed positive and negative emotion on susceptibility to false memories. Cognition & Emotion, 28(8), 1422-1434.

Riley, S.N. & Gabora, L. (2012). Evidence that threatening situations enhance creativity. In Proceedings of the Annual Meeting of the Cognitive Science Society, (Vol. 34), pp. 2234-2239.