My work explores how the visual design of symbols (e.g., !@#$%$) and logos influences what we remember, and the practical applications of those insights in the realm of advertising. Through research experiments and exploration of big data, I hope to reveal data-driven design principles that let us engineer more effective symbols and logos.
Interests
- Symbolic cognition in the mind and brain
- Improving memory for symbols and brand logos
- Memory enhancement techniques
Education
PhD in Cognitive Neuroscience, 2023
University of Waterloo
MA in Cognitive Neuroscience, 2019
University of Waterloo
Honours BA in Psychology, 2017
University of Waterloo
Skills
Technical
Python
Data Science
SQL
Hobbies
Hiking
Cats
Photography
Experience
Postdoctoral Scholar
University of Chicago
Responsibilities include:
- Analysing
- Modelling
- Deploying
- Exploring what makes symbols and logos highly memorable.
Course Instructor
University of Waterloo
Responsibilities include:
- Analysing
- Modelling
- Deploying
- Taught Brain Physiology, as well as Research Methods in Memory.
Database Coordinator
Waterloo Research in Aging Participants
Responsibilities include:
- Analysing
- Modelling
- Deploying
- Managed a database of 400+ older adult participants.
Accomplishments
Neural Networks and Deep Learning
Formulated informed blockchain models, hypotheses, and use cases.
See certificate
Object-Oriented Programming in R
Recent Publications
(2024).
Reading text aloud benefits memory but not comprehension.
Memory & Cognition.
(2024).
Release from response interference in color-word contingency learning.
Acta Psychologica.
(2023).
Face processing in ADHD: A review of the N170 event-related potential.
Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale.
(2023).
Memory for symbolic images: Findings from sports team logos..
Journal of Applied Research in Memory and Cognition.
(2023).
On Memory for Everyday Symbols.
Doctoral Dissertation.
