Julian Forsyth
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Researcher, Developer


I’m a Toronto-based researcher and developer with primary research interests in AI Safety and Interpretability, particularly as they apply to Medicine and Robotics. I’m also deeply interested in Computational Neuroscience. I’m excited to be starting my Masters of Science in Applied Computing at the University of Toronto.

In my spare time I try to get outside as much as possible, and watch great and/or terrible movies.

Publications

"Universal Sparse Autoencoders: Interpretable Cross-Model Concept Alignment"

2025 International Conference on Machine Learning (ICML)
Access paper here


"Robot Wheelchair Convoys for Assistive Human Transportation"

Proceedings of the 2024 IEEE International Conference on Smart Mobility
Access paper here

Work

Research Assistant, Computer Vision & Imaging Lab

@ York University, 2024 - present
- Collaborated with an inter-institutional team to conduct cutting-edge research focused on interpretability in deep neural networks
- Designed and implemented an innovative training framework
- Developed statistical and visual tools to communicate our findings and reveal model insights
- Contributed as second author to a paper for ICML 2025 (International Conference on Machine Learning)


Software Engineer & Researcher, Elder Laboratory

NSERC Undergraduate Student Research Award
@ York University, 2023
- Developed motion control and obstacle avoidance protocols for an autonomous wheelchair robot.
- Collaborated with robotics team made up of engineers and developers under Dr. James Elder.


Teaching Assistant

@ York University, 2022 - Present
- Guided students in Java coding, Object-Oriented Programming concepts and data structures.
- Helped students debug their code and work through challenges.

Education

B.A. Honours in Computer Science

@ York University, 2020 - 2024, GPA: 3.9


B.A. in Philosophy

@ Concordia University, 2017 - 2019, GPA: 3.8

Projects

Short Term Load Forecasting with GANs

@ York University, 2024
- Exploring Generative Adversarial Networks as a tool for predicting energy usage on residential power grids. Supervised by Dr. Michael Jenkin.


Syntax Writing Assistance Tool

@ York University, 2023
- Created a tool to improve word choice in text using GPT-2 and BERT.


E-Commerce Platform

@ York University, 2023
- Built a model marketplace with Java Spring, SQL backend, and React frontend, deployed on AWS.