Developed a portable AI-powered ECG monitoring system, integrating custom PCB hardware with a mobile application for USB-based signal acquisition and waveform visualization. Implemented a Pan-Tompkins signal-processing pipeline using 5-15 Hz bandpass filtering, differentiation, squaring, moving-window integration, and adaptive thresholding to reduce noise and detect R-peaks and QRS complexes. Integrated a remotely hosted CNN-LSTM model for automated ECG classification, combining waveform feature extraction with temporal sequence modeling and delivering results in under five minutes, including electrode placement, signal acquisition, and inference.

Developed an AI/ML-based GIS application leveraging UNET architecture to predict flood inundation extent based on satellite image data, achieving a dice coefficient of over 88% when compared to HECRAS and reducing inference time by 95%. Successfully implemented the application using a Django backend, Next.js frontend, and Google Maps GIS, enabling image generation with a rapid response time of 10 milliseconds. Received a Rs.10 lakh grant from the Ministry of Education's Institution's Innovation Council (IIC) under the Yukti Innovation Challenge to support further development and real-world application of the project.

Developed full-stack features for Intelligent Payment Automation, an enterprise accounts-payable platform integrating Oracle NetSuite with BILL and processing $200+ million in monthly transaction value. Optimized SuiteQL queries across four transaction types through streamlined joins, parameterized filtering, and paginated retrieval, resolving query timeouts on datasets exceeding 1 million records. Developed SuiteScript RESTlet APIs for vendor retrieval and payment submission, implementing bounded retries, payment-state reconciliation after timeouts, and chained execution to resume processing within platform resource limits. Built reusable UIF components for searchable payment grids, dynamic filtering, and pagination, incorporating concurrent data loading and isolated error handling. Engineered 1,400+ automated API and UI regression tests and integrated test suites into TeamCity CI pipelines, validating critical payment workflows, detecting integration failures early, and accelerating release validation.

CGPA: 8.72

Percentage: 93.6%

CGPA: 9.4