Aarnav Sabale

• Researching novel object detection techniques leveraging metadata storage to prevent re-classification, enhancing AI-driven autonomy for the visually impaired

• Developing AI recognition systems for assistive canes with real-time communication using LIME xAI

• Designed containerized AI Assistant trained on Rasa with intent-based NLU for daily task management

• Leading development of leasing optimization tool for 1,700-unit apartment portfolio using smart pricing algorithms and credit-based systems

• Developed product fulfillment backend and optimized inventory using ML and historical data, reducing waste and improving stock accuracy

• Conducted comprehensive strategy analysis addressing supply chain limitations with innovative solutions

• Applied AI skills in Python, Node.JS, and TensorFlow to programmatically classify unstructured conversational training data

• Integrated cutting-edge NLP Transformer models, improving conversation effectiveness to 96% through optimized training parameters

• Contributed to IEEE Xplore publication on NLP Model Integration for Mental Health Applications

• Refactored MATLAB cardiac MRI pipeline into Python framework with 50% complexity reduction

• Implemented Fourier-Feature MLP with PyTorch GPU optimization for real-time 4D displacement inference

• Achieved superior precision vs. CNNs and splines, with seamless mixed-signal circuit analytics integration

Machine learning cane with xAI communication system enabling real-time object recognition and navigation assistance for visually impaired individuals. Features LIME explainable AI for transparent decision-making.

Comprehensive database solution for TGCS tracking application processes and IQ test results. Streamlined data management with improved efficiency and advanced reporting capabilities.

Developed Amazon Rekognition system for dining hall optimization and AI drone delivery platform for campus logistics. Integrated computer vision with practical applications.