In industry-facing contexts, I design and deliver functioning engines and platforms that translate research into deployable systems. My work emphasizes robustness, scalability, and long-horizon usability with real users.
In academic and research-oriented settings, I treat design as system inquiry. I integrate biology, systems science, narrative theory, and computational modeling to study how experience, learning, and decision-making can be represented as systems.
A compact set of visuals to support the narrative: research communication, engine interfaces, and recognitions.
Oneiros Engine is a narrative–cognitive modeling framework that treats dreams, memories, and subjective experience as structured, replayable data. The engine extends game engine logic into the domain of cognition, making internal experience observable through system-level abstractions.
Narrative as data: experiences are captured, encoded, linked, and replayed across time using graph-based structures rather than clinical categories.
Systems biology (state & balance), systems science (feedback & cycles), game engines (state machines & replay), and dream research (symbolic narrative).
A graph structure linking motifs, emotional states, decisions, and contextual evidence. Enables long-horizon replay, comparison, and drift detection across months or years.
Qualitative experience is translated into state–balance–cycle variables (load, capacity, rhythm, recovery) to preserve interpretability without mysticism.
Before Oneiros, I led the design of XDesk / XEST 2.0, a hybrid inquiry-based learning ecosystem integrating software, hardware, hand-drawing, and media capture into a unified educational engine.
XEST 2.0 established the methodological foundation that later evolved into Oneiros Engine: treating learning, narrative, and experience as system-level phenomena rather than isolated events.