PROVEN INTERFACE ENGINEERING
WPUX Case Study: Engineering Model Explainability Layers and Automated UI Pipelines for Enterprise Predictive Inference Engines
This project highlights the cross-functional orchestration of a model explainability layer and frontend application architecture for an enterprise predictive calculation engine. To resolve development bottlenecks, a quantitative mapping ledger was engineered to align frontend interactive elements directly with four core relational tables within a cloud data warehouse. Additionally, an automated compilation pipeline was invented to translate high-fidelity design system components directly into functional programming layout scripts to accelerate engineering velocity.
WPUX Case Study: Quantifying Subconscious Cognitive Friction via Biometric Eye-Tracking
This pilot study details how an AI-powered webcam eye-tracking suite was leveraged to subconsciously evaluate user comprehension of a complex enterprise process diagram. Biometric gaze tracking across 5 participants revealed that while the primary top flow successfully guided users, a peripheral legend introduced severe cognitive friction and scored a highly negative K-coefficient of -0.48. The research demonstrates how advanced gaze-analytics move design teams past self-reported surveys to quantify abstract confusion, expose fragile information architectures, and mitigate deployment risks before software launch.
WPUX: Case Study: Transforming an Enterprise Performance Platform
This case study details a mixed-methods UX evaluation of a legacy enterprise Performance Development Plan (PDP) system that scored a poor 37.35 on the System Usability Scale. Through 26 semi-structured interviews and survey data, critical heuristic failures were uncovered, including severe navigation chaos and a 65% data loss rate due to silent timeouts. To bridge this usability-value gap, a behavioral-driven Tri-Pillar Framework was engineered to seamlessly integrate formal objectives, token-based peer recognition, and automated work artifact evidence collection.