I'm a full-stack engineer supporting health and wellness research, with interests spanning human performance, cognition, and computational modelling. In my professional work, I help research teams navigate IRB processes and data-sharing agreements, query operational and electronic health record data, and apply predictive modeling and causal inference to research questions. My broader interests include computational approaches to understanding affective, cognitive, and sensorimotor processes.
Please check out my Resume if you want to see my professional background, or view my projects involving cognition and machine learning: Affective Computing, Musical Computing, and Sensorimotor Computing, or simply hit the play button for a concise summary:
The little-mouse icon on the opens Pythia, this site's resident assistant — a small language model that runs at the edge (a local Ollama behind the hardware bridge) or from an AWS-hosted endpoint. She was chosen as a tribute to the many small intelligences that are sacrificed for scientific discovery. She serves four primary functions — or to see her in action:
Question answering about the pages and projects here — what the SEED model ablation found, how the guitar transcriber works, what the drone sim optimizes — from any page.
On the Affective Computing page she runs the SEED protocol end to end: checks your sensors, starts and paces the trials, collects self-reports, and archives the recording.
Practice another language with Pythia. Tutor Mode supports English, Spanish, and Mandarin, answering questions about the project side-by-side with English, providing pinyin for Mandarin, offering gentle corrections, and speaking with language-specific voices.
Reactive, personalized software requires constant iteration, revision, and maintenance. LLMs have accelerated many aspects of software engineering and design, and this site would have been considerably more difficult to build and maintain without them.
Much of the content and styling here emerged through repeated cycles of human and machine judgment, generation, and refinement. Perfection should not be expected, and neither should infallibility from Pythia. There is an ancient irony in consulting an Oracle: even prescient answers can mislead when the question, assumptions, or interpretation are wrong [Herodotus].