The International Conference on Machine Learning, Artificial Intelligence, and Data Science (ICMLAIDS 2026), scheduled for March 20–21, 2026, in Florida, will bring together researchers, engineers, and industry professionals to explore practical applications of AI and data science in engineering systems. At the forefront of these discussions is Harshitkumar Ghelani, an electronics engineer specializing in PCB manufacturing and production engineering, who will be a featured speaker at the event. Recognized for his pioneering work at the intersection of applied research and manufacturing practice, Ghelani was selected for his expertise in integrating AI and data science into production workflows, demonstrating how analytical technologies can drive tangible improvements in engineering systems.
According to conference organizers, the 2026 program will focus on practical applications of machine learning and data science across manufacturing, production engineering, quality assurance, and reliability management. The agenda reflects growing industry interest in solutions that can be implemented within existing processes while maintaining system stability, compliance, and performance.
In outlining the direction of the event, Isaac Johns, Program Coordinator for ICMLAIDS 2026, said, "The conference is designed to connect research with real-world implementation. This year's discussions will emphasize how data-driven methods are being applied within operational engineering environments, rather than remaining purely theoretical."
Focus on Implementation and Industry-Relevant Use Cases
Conference materials indicate that ICMLAIDS 2026 will feature technical presentations, applied case studies, and panel discussions addressing topics such as predictive analytics in manufacturing, integration of machine learning models into quality systems, process monitoring using real-time data, and analytical approaches to failure analysis and root cause investigation.
Organizers noted that the program emphasizes interdisciplinary participation, reflecting the reality that effective implementation of artificial intelligence in engineering systems often requires collaboration between engineers, data scientists, and operations teams. Sessions are structured to encourage discussion of both opportunities and constraints, including scalability, validation, and long-term reliability.
Speaker Participation and Industry Perspective
The conference speaker lineup includes contributors from academic institutions, research organizations, and industrial environments, selected based on relevance to the conference themes. Among the invited participants is Harshitkumar Ghelani, who has been recognized by multiple professional and academic organizations for his pioneering work. Ghelani is a Royal Fellow of the International Organization for Academic and Scientific Development, a Senior Member of IEEE, a Fellow of IETE, and an international scientific research organization, and his research on additive manufacturing in electronics won the Best Paper Award from the World Journal of Advanced Engineering Technology and Sciences. He was specifically selected to present at ICMLAIDS 2026 due to his expertise in applying AI and data science within manufacturing workflows, bridging the gap between research and practical engineering solutions.
We spoke with Ghelani ahead of the event, who shared that his perspective draws on both manufacturing practice and applied research. He highlighted that at ICMLAIDS 2026, he plans to discuss the practical integration of machine learning and data science in production workflows, including challenges related to process monitoring, predictive quality control, and reliability optimization. He emphasized that the conference will provide a platform for examining real-world applications of AI in engineering systems, facilitating dialogue between researchers and practitioners on how analytical tools can improve operational efficiency and decision-making across manufacturing environments.
Discussing the conference focus, Ghelani said, "As engineering systems generate increasing volumes of process and quality data, the challenge is not collecting information but applying analytical tools in ways that support reliability and informed decision-making." He added, "Conferences that emphasize implementation allow engineers to examine what is feasible within production environments, rather than viewing artificial intelligence only through a theoretical lens."
Research Dissemination and Knowledge Exchange
In addition to technical sessions, ICMLAIDS 2026 will provide participants with opportunities to publish full-length research articles in associated academic journals. According to the organizing committee, accepted publications will be indexed and assigned digital object identifiers (DOIs), supporting broader dissemination and long-term accessibility of presented work.
Conference representatives stated that the publication component is intended to support both academic researchers and industry practitioners documenting applied solutions, implementation outcomes, and system-level insights.
Broader Context and Industry Impact
Industry observers note that conferences emphasizing applied artificial intelligence and data science play an increasingly important role as organizations seek to translate research advances into operational improvements. In manufacturing and engineering contexts, adoption is often influenced by factors such as process compatibility, regulatory requirements, and system reliability.
Organizers of ICMLAIDS 2026 stated that the conference aims to contribute to informed discussion on these issues by convening participants with experience across research and operational environments, supporting responsible and practical innovation.
Join the Conversation