I am a Master of Management student at UBC. Previously, I graduated with a Bachelor of Science in Biology and Computer Science (Combined Major) from UBC.
Currently, I am working on humanoid locomotion, training high-level controllers to take robust steps in challenging environments under the supervision of Dr. Michiel Van de Panne at UBC and Nick Ioannidis, a PhD student at SFU.
For my undergraduate thesis, I explored the use of reinforcement learning to model individual human behaviour during epidemics under the supervision of Dr. Daniel Coombs. This work has been accepted to TMLR and you can access the paper.
I am particularly interested in reinforcement learning, vision-action-language models, and computer vision, with the goal of building intelligent systems that seamlessly integrate perception and action.
Research
Exploring the intersection of artificial intelligence, robotics, and human behavior through computational approaches. My research focuses on developing adaptive systems that can learn, reason, and interact effectively in complex environments.
Adaptive Motion Planning for Humanoid Robots
MOCCA Lab, UBC Computer Science · Dr. Michiel Van de Panne
Developing robust control policies for humanoid robots to navigate challenging terrains using deep reinforcement learning techniques.
ContagionRL: A Flexible Platform for Learning in Different Spatial Epidemic Environments
UBC Mathematics & Computer Science · Dr. Daniel Coombs
ContagionRL simulates human behavioral responses during epidemics using reinforcement learning, combining a spatial SIRS disease model with single-agent RL.
Entrepreneurship Education Research
UBC Computer Science and Sauder School of Business · Dr. Angele Beausoleil
An NLP-based system that automatically analyzes and maps entrepreneurship education programs and course syllabi against defined competency frameworks using zero-shot classification.
Monte Carlo Protein Engineering: Conformational Optimization and Systematic Mutagenesis Analysis
UBC Life Sciences Institute (LSI) · Dr. Steven Halem
A Monte Carlo protein optimization system that uses PyRosetta to systematically explore protein conformations and evaluate single amino acid mutations for enhanced stability and functionality.
Featured Projects
A selection of projects combining AI, software engineering, and data-driven systems: from interactive dashboards and research prototypes to robust web and mobile applications.
Protein Mutation Analysis
A systematic protein mutation simulation tool that analyzes single amino acid substitutions across entire protein chains using PyRosetta.
Autonomous Landing with Deep RL
Deep reinforcement learning system that trains an autonomous agent to safely land a spacecraft between the yellow flags.
MuJoCo: Learning to not Fall
Reinforcement learning system teaching humanoid how to not fall and remain standing upright using MuJoCo physics simulation and PPO algorithm.
Monte Carlo Protein Enhancer
PyRosetta-based Monte Carlo simulation tool for optimizing protein conformations to enhance stability and functionality.
Custom Testnet Trading System
A Java-based paper trading platform where users can practice stock trading with virtual money in a simulated market environment using random walk theory for price movements.
Blog
Keeping Things on Track: How PID Controllers Work
Three ideas, three terms, a formula you could write in a single line. How PID controllers solve one of the most universal problems in engineering.
Kelly in the Wild: Against the Ensemble
How Kelly sizing, LMSR pricing and real-time Bayesian updating fit together into a working prediction market architecture.
The Clever Trick at the Heart of RLHF
On why ELO — a 1960s chess rating system — sits at the core of how modern language models are trained.
GitHub Activity
Connect
Feel free to contact me at rdmnr@protonmail.com