Abhishek Gupta

Standard Operating Procedure (SOP) Search Simplification: Converted unstructured data to structured format using GPT 3.5 to generate pseudocode and flowcharts (94.7% accuracy). Developed a data model to streamline claims processing, reducing TAT by 20%.

Secured 92.7% in a 1-year orientation course in Electrical Engineering with Specialization in Nuclear Engineering.

Claim Overpayments: Investigated health insurance claims data using fraud detection methods, identifying overpayment of US$ 100K. Warehouse Re-slotting Analysis: Framed an initial stage warehouse re-slotting plan using affinity analysis.

Face Detection: Formulated face Image Quality Metric for key frame selection, improving face recognition accuracy to 89%. Module Inventory Management: Designed an automation application providing role-based authorization and capturing inventory/system configuration data.

Reimbursement Claim Analysis: Performed text mining to identify key reasons of delayed deliveries.

Automated SOP Prioritization: Created Python web scraping script and developed a document prioritization ranking system. Automated low-complexity, high-volume clusters, saving US$ 80K annually. Optimized Appeals Process using GPT 3.5 (96% accuracy) and deployed a gradient boost classification model. Engineered an explainability model and applied a unidirectional stacked RNN model (88% accuracy, 20% improvement). Created Persona: Utilized K-means clustering to segment employees, boosting customer satisfaction by 18%.

Predictive Maintenance: Developed a time series-based regression model to calculate remaining useful life, saving man-hours by 20%. Developed a statistical model for failure rate estimation and designed an automation application to compare predicted failure rates (88% accuracy).