About

I am a senior software engineer and technical lead with a background in building, operating, and modernizing complex analytical systems. My work sits at the intersection of applied machine learning, financial analytics, and large-scale software architecture.

I currently work at Synario, where I focus on evolving a long-lived financial modeling platform while introducing modern architectural patterns and AI-enabled capabilities. Much of my role involves translating ambiguous, research-oriented ideas into systems that can operate reliably in production environments.

Professional Background

Over the course of my career, I have worked across financial analytics, data-intensive platforms, and enterprise-scale systems. This has included leading technical initiatives to modernize legacy codebases, designing microservice layers to decouple monolithic architectures, and introducing new capabilities without disrupting existing users.

A recurring theme in my work is operating under real-world constraints: incomplete data, evolving requirements, and systems that must continue to deliver value while they are being transformed.

Research & Technical Interests

My current technical interests focus on applied machine learning and AI systems, particularly where statistical methods, model-driven reasoning, and production engineering intersect. Areas of active exploration include:

• Anomaly detection and risk analysis in financial data
• AI-assisted analytics and explanation systems
• Model behavior, attribution, and interpretability
• Designing ML pipelines that balance rigor with operational simplicity

Rather than treating research and engineering as separate activities, I am interested in how exploratory modeling, experimentation, and system design inform one another when deployed in real environments.

Writing & Open Work

This site serves as a space to publish technical writing and research notes. The material here reflects work in progress: ideas being tested, patterns being examined, and systems being stress-tested against real constraints.

Selected experiments, prototypes, and supporting code are published on GitHub, where I explore ideas in greater depth through implementation.

Looking Ahead

I am particularly interested in continuing to deepen my work in applied machine learning and AI-driven analytics, with an emphasis on systems that support better decision-making under uncertainty.

This site represents an evolving body of work rather than a static portfolio. The goal is to document thinking over time and to connect with others working at the boundary between research and production systems.