I follow a non-linear path: atypical formal studies, deep autodidactic cycles, and an intentional return to structured informatics education to formalize foundations and accelerate advanced tooling work.

Over the past several years, I have worked at the intersection of healthcare software development and clinical research. My experience includes building registry studies, designing harmonization frameworks across disease areas and study sites, and driving interoperability in complex data environments. Today, in my role as an administration agent at one of Canada’s largest ophthalmology tertiary care centers, I continue to see firsthand how critical standardized, high‑quality datasets are for advancing patient care and research.

With a background spanning healthcare coordination, community advocacy, and research support, I now focus on digital infrastructure, open‑source tooling, and personal knowledge systems. My technical journey began through automation and documentation, evolving into developing GitHub repositories, custom Obsidian workflows, and creative digital tools under the alias PtiCalin. This persona is devoted to building spaces that are gentle, funny, engaging, self‑instructive, deeply structured, scalable, and automated.

Whether I am managing a clinical admission tracker, designing a blockchain tutorial series, or building cozy surrealist vaults, I aim to bring clarity, compassion, and playfulness to everything I create.

• Early Exploration: Built creative systems outside traditional curriculum, fostering curiosity and independence.
• Autodidact Phase: Deep dives into systems thinking, scripting, metadata modeling, and automation using open resources and reverse engineering.
• Project-Centric Growth: Developed vault architectures, plugins, and analysis pipelines with a focus on reproducibility and validation.
• Formal Study (Informatics): Strengthened algorithms, data structures, networking, and design patterns for scalable, maintainable solutions.
• Current Synthesis: Blending academic rigor with experimental prototyping, documenting processes for portable, auditable knowledge.

• Prefer offline-capable, self-owned data stores.
• Model before UI; schemas drive automation.
• Composition: isolate concerns into pluggable units.
• Log decisions, schema shifts, structural refactors.
• Layering: build thin vertical slice → refine → generalize.
• Then abstract: code/prototype before theory summaries.
• Apply concepts from systems design, worldbuilding, and data modeling back into personal knowledge tools.
• Translate tacit shortcuts into explicit documented standards.
• Open-source collaboration: I believe knowledge and tools grow stronger when shared. My approach is rooted in transparency, mentorship, and building together—whether through documentation, code, or community support.

Focused on local-first, modular, metadata-driven workflows. Each category lists current active use plus near-term evolution.