International Conference on Machine Learning, Artificial Intelligence and Data Science

Manish Kumar Gupta

Biography

Manish Kumar Gupta is an Assistant Professor in the Department of Computer Science & Engineering at Madan Mohan Malaviya University of Technology (MMMUT), Gorakhpur, India. He earned his B.Tech., M.Tech., and Ph.D. in Computer Science & Engineering from a state government university, India. 

With over 15 years of teaching and research experience, Dr. Gupta has held academic positions at leading institutions including Amity University, Sarvottam Institute of Technology, and Buddha Institute of Technology, where he also served as Head of Department (CSE). His research interests span Big Data, Blockchain, Programming for Problem-Solving, Design & Analysis of Algorithms, and Mathematical Computation.

He has authored and co-authored numerous research papers in international journals, conference proceedings (Scopus-indexed), and book chapters with reputed publishers like Springer and Taylor & Francis. In addition, he holds patents in areas including IoT-based health management and robotics. He has actively participated in various FDPs, workshops, and international conferences, and serves on editorial and review committees of scientific journals.

Mr. Gupta is a member of professional societies such as the International Association of Engineers (IAENG) and The Institute of Research, Engineers, and Doctors, and IEEE. Beyond academia, he is passionate about fostering innovation and developing secure, scalable solutions for data-intensive systems.

Research Interest

His research interests span Big Data, Blockchain, Programming for Problem-Solving, Design & Analysis of Algorithms, and Mathematical Computation.

Abstract

Big Data: Concepts, Challenges, and Applications in the Digital Era: Big Data refers to extremely large, complex, and high-velocity datasets that cannot be efficiently processed using traditional data management techniques. With the rapid growth of digital technologies, social media, cloud computing, and the Internet of Things (IoT), the volume, variety, velocity, and veracity of data have increased exponentially, creating both opportunities and challenges for organizations and researchers. Big Data analytics enables the extraction of meaningful patterns, trends, and insights that can drive innovation, optimize business processes, improve decision-making, and support evidence-based policymaking. However, managing Big Data involves addressing significant issues such as data storage, processing frameworks, scalability, privacy, and security. Emerging technologies like Hadoop, Spark, and machine learning algorithms have become essential tools for handling Big Data efficiently. This presentation provides an overview of Big Data concepts, its key characteristics, technological enablers, challenges, and diverse applications across domains such as healthcare, finance, e-commerce, and smart cities.