Software

Software Engineer (ML & Computer Vision)

• Led the design and evaluation of Siamese neural network architectures (VGG16, ResNet50, ResNet152, ViT-Base, and ViT-Large) utilizing Contrastive Loss for non-invasive biometric livestock identification.
• Integrated Explainable AI (Grad-CAM) to visually map and validate that neural activation focus was anchored on anatomical muzzle groove ridges instead of background noise.
• Engineered on-device image processing pipelines for real-time camera frames, including auto-cropping, blur-filtering, and illumination normalization.
• Optimized deep learning model inference (onnx runtime / tflite integration) for resource-constrained edge devices, achieving low-latency offline verification.
• Coordinated large-scale multi-environment field data collection across Nepalese farms, capturing muzzle characteristics under variant ambient lighting, postures, and post-mortem intervals.

Junior Software Engineer

• Developed and integrated on-device image analysis components, including computer vision modules for localized skin feature classification.
• Optimized client-side networking layers, caching strategies, and local database transactions to ensure efficient retrieval of image metadata.
• Designed responsive interface architectures to handle high-resolution image rendering pipelines across various hardware form factors.

Medease — Healthcare Management & Booking System

An integrated healthcare management application featuring real-time appointment booking, consultation chat, video consulting, and a built-in medical products e-commerce system.

Systems focus: Real-time communication protocols (WebRTC), secure chat and video streaming architectures, and e-commerce transaction handling.

Lunar Calibration for Light Pollution Measurement

A collaborative Android application developed with students from MIT and NYU that detects and measures light pollution from lunar photographs. The app handles camera-based image capture, analysis, and all computation entirely on-device.

Systems focus: On-device image processing, camera frame analysis, and performance-optimized computation without network dependency.