Sunil Gautam

Papers

Total Citations

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About

Sunil Gautam’s research lies at the intersection of big data analytics and machine learning, with a focus on translating complex algorithms into real-world applications. His most-cited work, “Application of Big Data and Machine Learning” (2020), explores how machines are trained on historical data to build predictive logic, with particular emphasis on speech recognition and computer vision. While this paper has garnered 3 citations—a modest count reflecting an early-stage contribution—it signals Gautam’s engagement with foundational challenges in the field. His research underscores the transformative potential of machine learning in automating decision-making and pattern recognition across industries. As a researcher, Gautam contributes to the growing body of work that bridges theoretical ML advancements with practical, data-driven solutions. His efforts are particularly relevant for students and practitioners seeking to understand how big data and algorithmic training converge to power modern intelligent systems. With continued development, Gautam’s work holds promise for deeper impact in areas where machine learning meets everyday technology.