Why I Build at the Intersection of AI, Science, and Systems

I’ve always been drawn to difficult problems - especially the ones that sit between disciplines.

My background spans computational science, physics, philosophy, AI engineering, biomedical research, and scientific computing. Over time, I realized something important:

The most meaningful problems rarely fit neatly inside one field.

That’s why I enjoy building at the intersection of:

🧠 AI & intelligent systems 🔬 Science & healthcare ⚙️ Automation & scalable infrastructure 🌐 XR/WebXR & immersive technologies

In recent years, I’ve worked across: • AI/ML systems and agentic workflows • Bioinformatics and computational biology • Scientific imaging and breast cancer detection research • Production-grade APIs and data pipelines • Cloud infrastructure and automation • Open-source XR and WebXR ecosystems

I’m especially interested in projects where rigorous thinking meets real-world impact - whether that means accelerating biomedical discovery, building intelligent research workflows, or creating systems that help people understand complex ideas.

Technology becomes most meaningful when it helps us see, understand, and solve problems more clearly.

Always excited to connect with others building ambitious things at the edge of science, AI, and systems.