I am a graduate student in Statistics at ETH Zurich, working on problems in Data Science, Machine Learning, and Artificial Intelligence. Most of my repositories are private, but feel free to contact me if you would like to discuss any of the work below.

Meta Learning and Hierarchical Models

• My thesis evolves around the topic of meta learning and hierarchical models. In particular, we try to understand and develop models to deal with grouped data structures.

Neural Network Verification

• Verifying robustness of neural networks using DeepPoly, a deterministic convex relaxation-based approach for ReLU and ReLU6-based architectures.

Continual Learning

• Analyzing which parameters cause catastrophic forgetting in continual learning frameworks.

Quantitative Finance

• Building predictive signals for liquid assets from illiquid asset performance.

Healthcare Operations

• Emergency department staffing optimization app for planning requirements and analyzing patient flow characteristics.

Computer Vision

• Conditional Generative Adversarial Network for generating synthetic training examples for image classification.

Quantitative Finance

• Linear state-space models for dynamic cointegration-optimal index tracking.
• Backtesting statistical arbitrage strategies based on enhanced index tracking methodology.

Feel free to reach out if any of these projects are of interest.