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About

Xiaoqin Zhang is a multidisciplinary researcher whose work spans advanced manufacturing, materials science, and intelligent computer vision systems. With a growing body of highly cited publications, Zhang has made significant contributions to the field of 3D printing, particularly in developing high-performance photocuring elastomers and novel processing strategies for poly(dimethylsiloxane). Their 2019 paper on 3D-printed photocuring elastomers with exceptional mechanical strength and resilience has garnered 66 citations, reflecting its broad impact on additive manufacturing applications, while a subsequent two-stage curing approach for PDMS attracted 54 citations for enabling precision-fabricated, high-performance structures. Beyond materials, Zhang has demonstrated impressive versatility in artificial intelligence and robotics. Their work on bioinspired deep active learning for remote sensing scene classification (49 citations) bridges cognitive science and computer vision, while contributions to adversarial robustness in video object segmentation and 3D object detection underline a commitment to reliable, real-world AI systems. Zhang also explores human-robot collaborative logistics and electromagnetic actuators for bionic robots, showcasing an applied engineering dimension to their research portfolio. Together, these contributions — spanning over 240 citations — position Zhang as an innovative researcher at the exciting intersection of smart manufacturing, robotics, and deep learning.