I am an AI/ML Engineer and researcher fueled by a passion for machine learning, deep learning, computer vision, natural language processing, and generative artificial intelligence. I strive to develop intelligent, data-driven systems that tackle real-world challenges, such as image segmentation, crowd anomaly detection, predictive analytics, and document intelligence. My research is dedicated to advancing robust and imbalance-aware image segmentation, enhancing computer vision for video understanding, pioneering machine learning-based risk prediction, and exploring retrieval-augmented generation (RAG) for knowledge-intensive applications. I am particularly focused on improving model reliability, evaluation, and practical deployment, emphasising the transformation of experimental findings into scalable AI solutions. Holding a B.Tech in Computer Science and Engineering from KIIT University, I am committed to making a meaningful contribution to reproducible, reliable, and impactful AI systems through research, experimentation, and engineering.
I am an AI/ML Engineer and researcher fueled by a passion for machine learning, deep learning, computer vision, natural language processing, and generative artificial intelligence. I strive to develop intelligent, data-driven systems that tackle real-world challenges, such as image segmentation, crowd anomaly detection, predictive analytics, and document intelligence. My research is dedicated to advancing robust and imbalance-aware image segmentation, enhancing computer vision for video understanding, pioneering machine learning-based risk prediction, and exploring retrieval-augmented generation (RAG) for knowledge-intensive applications. I am particularly focused on improving model reliability, evaluation, and practical deployment, emphasising the transformation of experimental findings into scalable AI solutions. Holding a B.Tech in Computer Science and Engineering from KIIT University, I am committed to making a meaningful contribution to reproducible, reliable, and impactful AI systems through research, experimentation, and engineering.