Codes by Shrey
Health + AI Education Experiences Expression

health-humans-ai

Human factors research for clinical AI, health products, and embodied performance systems.

I am applying for roles where UX research, human factors, clinical AI evaluation, and health-product strategy meet. My edge is translating observed behavior into product decisions for systems that affect safety, trust, comprehension, and daily health behavior.

Education

MS Human Factors Information Design. BS Biomedical Engineering.

Research

Moderated usability, mixed methods, task analysis, trust evaluation.

Clinical AI

LLM evaluation, clinical roleplay, patient-centered communication.

Health Product

Wearables, biomechanics, movement coaching, digital health behavior.

Positioning

I study how people understand, trust, and behave within health-adjacent systems.

I work with product and engineering teams to turn those insights into clearer interactions and better decision support.

I build for n = 1, then engineer for safety and scale.

Proof From Work

mpathicClinical AI evaluator reviewing conversational outputs for quality, safety, empathy, scope control, and user comprehension. NBME Clinical RoleplayLead product engineer for an AI clinical communication simulator with text / voice interaction, transcript review, and formative feedback. NATHAN SportsUX researcher for moderated mobile usability studies across discovery, conversion friction, trust signals, and retention levers. Movement CoachingBiomechanics, behavior change, swim instruction, and clinic-based movement education translated into product requirements. HapTrekWearable haptic navigation prototype using Arduino, accelerometer logic, vibration feedback, and field-testing requirements. Glenoid Implant PatentBiomedical device invention with biomechanics, medical-device constraints, stress testing, and patient-outcome context.

Research Methods I Bring

Behavioral Research

Moderated usability testing, think-aloud studies, survey design, journey mapping, personas, and task analysis.

AI Trust Evaluation

Mixed-methods research on OpenEvidence, Consensus, and Perplexity for trust calibration, comprehension, source use, and overreliance.

Product Translation

Research synthesis, information architecture, prioritization, Figma, UserTesting, Jira, React, TypeScript, and AI prototyping.

Why This Lane Fits

The local library points toward the same market that the portfolio already proves: clinical AI needs human-in-the-loop evaluation, health products need trust and behavior research, and wearables need human factors that connect data to action.

That is the role I am positioning for: a researcher-builder who can work across humans, health, and AI without losing the safety boundary or the product decision.

Primary sources used: local LinkedIn saved-post map, latest UXR resume, and the existing git-gud portfolio case studies.