Research Projects

My research portfolio is a testament to the intersection of Applied AI, Transport Analytics, and Impact-Driven Engineering. While my blog documents my learning journey, these projects showcase the rigorous execution and system design required to turn concepts into reality.

“Research is to see what everybody else has seen, and to think what nobody else has thought.” - Albert Szent-Györgyi

From Conceptualization to Execution

In my writing, I often explore the “why” and “how” of emerging technologies. In these projects, I transition to the “what”-the actual systems, pipelines, and models that deliver measurable outcomes.

• Engineering Decision Making: Moving beyond isolated experiments to build Reproducible Workflows and production-ready codebases.
• Technical Rigor: Balancing model accuracy with real-world interpretability and operational constraints.
• Holistic System Design: Ensuring that every component-from data validation to stakeholder dashboards-is part of a cohesive, maintainable system.

Core Research Themes

1. Intelligent Transport Systems (ITS)

I have spent significant time developing end-to-end data processing pipelines for large-scale mobility datasets. This work involves everything from demand forecasting to anomaly detection in complex urban environments.

2. Applied Machine Learning

Moving beyond prototypes, my focus is on Deployment-Oriented Thinking. This includes building robust training infrastructures, maintaining scientific rigor, and ensuring models can thrive in production environments.

Bridging the Divide

A recurring theme across my work is the ability to communicate complex research clearly to mixed technical audiences. I believe that Scientific Rigor and Practical Delivery are not mutually exclusive but are two halves of the same coin.

• Blog: The conceptual laboratory for ideas and learning.
• Resume: The strategic summary of roles and achievements.
• Projects: The physical evidence of systems built, deployed, and proven.

This integrated approach ensures that every line of code I write is informed by deep research and every research thought I have is grounded in engineering reality.