Aditya Patil

Conference paper applying regression and clustering (K-means) methods to analyze e-commerce user behavior, purchasing trends, and customer segmentation for strategy and marketing insights.

Article describing a hybrid framework for ocular disease diagnosis using advanced methods (listed with co-authors and affiliation to VIIT).

Research article exploring ML techniques for battery performance prediction, remaining useful life (RUL) estimation using a clustering-based approach, and ML-driven materials discovery to improve battery sustainability and reliability.

Study building predictive models for lung cancer outcomes using patient demographics, smoking history, medical and family histories, and other health indicators to predict prognosis.

Analysis of morphology and chemical composition of Sb2(S1-, Tex)3 thin films synthesized via arrested precipitation, using AI-driven methods to identify structural and compositional patterns relevant to optoelectronic applications.

Design and implementation of an academic-support chatbot using a LLaMA-based model, integrating MongoDB and embeddings to retrieve contextually relevant information for student queries.

Paper proposing a cache-based approach to improve scalability and performance in quantum computing systems.

Work applying NLP and predictive modeling to improve sentiment analysis on social media data, focusing on feature engineering and model selection.

Conference/journal article applying clustering and predictive models for customer segmentation and sales prediction in e-commerce and marketing contexts.