MSc Student — UBC Okanagan
I study reinforcement learning systems that are reliable, data-efficient, and grounded in real-world engineering needs.
About
I'm a graduate student researching how to make reinforcement learning agents explore responsibly and communicate what they know. I care about simple baselines, clean code, and making research artifacts easy to reproduce.
Interests
Selected work
Exploring ways to surface what agents know and how they explore, as part of the UBC Digital Transparency Cluster.
Applying U-Net variants and streaming inference to detect veins in NIR imagery for biomedical applications.
Prototyped compact convolutional networks with natural-gradient updates, aiming for lower power and parameter budgets.
Contact
Whether it's research discussions, collaborations, or sharing ideas on RL, feel free to reach out.