Research
7+
Peer-Reviewed
Publications
7+
Journals
Reviewed
29+
Papers
Reviewed
4
Top-Tier
Venues
Vanier
Scholar
NSERC Canada
Graduate Scholarship
Gold
Medal
Governor General
of Canada · 2025
Research Themes
Five interconnected methodological threads
Thread 01
LLM Behavioral Monitoring in Complex Systems
Detecting reliability degradation, output drift, and failure modes in LLM-powered pipelines operating over interconnected data systems — combining observability instrumentation with behavioral evaluation frameworks to maintain trustworthy AI performance in production.
Thread 02
Deep Learning for Hazard Forecasting
State-of-the-art deep learning architectures applied to geospatial time-series data for province-scale wildfire prediction, urban flood forecasting, and real-time risk assessment — end-to-end pipelines designed for operational deployment in high-stakes environments.
Thread 03
Supervised ML for Complex Prediction
Developing supervised learning frameworks capable of capturing high-dimensional, non-linear interactions in complex systems — where outputs are interdependent and predictive accuracy demands going beyond standard single-output model assumptions.
Thread 04
Graph-Theoretic Risk Modeling
Applying graph-theoretic methods and complex network analysis to model systemic risk and cascading failure propagation in interconnected systems — formalizing how local disruptions escalate into system-wide failures through dependency structures.
Thread 05
Optimization-Augmented Machine Learning
Applying metaheuristic optimization to accelerate and improve model development — replacing exhaustive search strategies with intelligent, convergence-focused approaches that achieve superior hyperparameter configurations at a fraction of the computational cost and time.