Max Robotics — Global Service Robot Directory + US Certification

About

Ahmed Yaseer is a researcher whose work sits at the intersection of advanced manufacturing, robotics, and machine learning, with a particular focus on Wire Arc Additive Manufacturing (WAAM). His most influential contribution, "Machine Learning Based Layer Roughness Modeling in Robotic Additive Manufacturing" (2021), has garnered 87 citations, establishing him as a notable voice in the application of artificial intelligence to manufacturing process optimization. Yaseer has made significant strides in addressing one of WAAM's most persistent challenges — surface roughness control — developing predictive models that reduce reliance on costly post-fabrication machining. His work spans surface roughness characterization, path planning strategies for robotic deposition systems, and the use of multilayer perceptron neural networks to forecast layer quality during manufacturing. Beyond metal fabrication, Yaseer has demonstrated a broader curiosity, contributing a well-cited review on sensors and machine learning in precision livestock farming, reflecting his interest in applying intelligent systems across diverse domains. His body of work collectively underscores a commitment to making complex manufacturing and agricultural processes smarter, more efficient, and more autonomous — research increasingly vital in today's era of industrial digitalization.