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Vigneashwara Pandiyan is a University Lecturer in the Department of Mechanical and Materials Engineering at the University of Turku, Finland, where he has been serving since 2025. He completed his Ph.D. at Nanyang Technological University (NTU), Singapore, from 2014 to 2018, where he conducted research on modeling and in-situ monitoring of robotic abrasive belt grinding processes. His doctoral work focused on integrating advanced sensor technologies with machine learning to optimize grinding performance and precision manufacturing, in collaboration with the Rolls-Royce@NTU Corporate Laboratory. This research contributed to the understanding and automation of robotic grinding for aerospace components such as fan blades.

In 2019, Dr. Pandiyan worked at A*STAR – Agency for Science, Technology and Research, Singapore, where he contributed to IIoT-based streaming analytics for industrial applications, addressing challenges in both precision manufacturing and fast-moving consumer goods (FMCG) industries. He then joined Empa – Swiss Federal Laboratories for Materials Science and Technology, Switzerland, where he worked from 2020 to 2024. At Empa, his research focused on laser–material interactions in powder bed fusion and directed energy deposition processes, with emphasis on real-time monitoring and control of additive manufacturing systems.

Prior to joining the University of Turku, he served as a Senior Researcher in Additive Manufacturing within the Digital Manufacturing program at the Technology Innovation Institute (TII), Abu Dhabi, from 2024 to 2025. His expertise spans laser–material interactions, metal additive manufacturing, tribology, surface finishing, abrasive cutting, and smart manufacturing. His current research explores the physics of acoustic and optical emissions during material transformations and surface interactions. By analyzing photon and phonon emissions generated during processes such as laser–material interactions and contact-based transformations, he develops sensing and machine learning frameworks for real-time monitoring, anomaly detection, process control, and automation in advanced manufacturing systems.

Dr. Pandiyan has been working with machine learning for nearly a decade and has more than 10 years of experience in process monitoring across subtractive, additive, and other advanced manufacturing processes. His work focuses on integrating advanced sensing, machine learning, and process physics to improve reliability, automation, and qualification in modern manufacturing systems. Alongside his research, he is actively involved in teaching, mentoring, and guiding students in additive manufacturing, process monitoring, tribology, and machine learning-assisted manufacturing.