Andrew Pearce is a graduate student at the University of California, San Diego, in the Halıcıoğlu Data Science Institute (HDSI), pursuing a Master of Science in Data Science. His work focuses on the mathematical foundations and applied deployment of machine learning systems in scientific and environmental domains.
Research Interests
Machine Learning
- Representation Learning & Deep Models: Learning structured representations of physical and environmental systems from high-dimensional data.
- Optimization & Learning Theory: Convergence in non-convex optimization and generalization behavior of modern ML systems.
- Mathematical Foundations: Connections between optimization, geometry, and probabilistic modeling.
Applied Data Science
- Statistical Modeling & Inference: Quantifying uncertainty and causal structure in real-world data.
- 3D Computer Vision & Spatial ML: Surface reconstruction and generative modeling from LiDAR and imagery.
- Scientific Machine Learning: Deploying scalable ML systems in environmental domains.