Michail J. Beliatis

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About

Michail J. Beliatis is a leading researcher at the intersection of advanced manufacturing, artificial intelligence, and human-robot collaboration. His work focuses on transforming traditional industries through intelligent automation, with key contributions in textile defect detection and additive nano-manufacturing. In his highly cited 2024 study (23 citations), Beliatis developed an enhanced deep convolutional neural network for textile fabric defect detection, integrating safe human-robot collaborative interaction to replace manual, error-prone inspection processes. This work demonstrates how AI-trained automation can revolutionize labor-intensive sectors. Additionally, his 2022 research on robotic 3D printing polymer extruders integrates laser and FTIR characterization for nano-manufacturing, advancing Fused Deposition Modelling (FDM) beyond prototyping into precise nanomaterial deposition and laser nanostructuring. By combining low-cost additive manufacturing with in-situ characterization, Beliatis enables scalable, high-precision production of functional nanomaterials. His interdisciplinary approach—bridging robotics, computer vision, and materials science—positions him as a key innovator in smart manufacturing. With growing citation impact, Beliatis’s work is shaping the future of safe, AI-driven industrial automation and next-generation nano-fabrication technologies.