Qian Likun is an emerging researcher in the field of automation and control systems, currently pursuing his undergraduate degree at China University of Geosciences (Wuhan). With a solid foundation in electronic technologies, embedded systems, and automation instrumentation, Qian has displayed strong technical proficiency and innovative thinking across various academic and practical projects. He has independently designed and developed motion controllers, control platforms, and monitoring systems, showcasing his ability to integrate software and hardware seamlessly. His projects range from motion trajectory control to subsurface conductor detection and RGBD salient object detection using convolutional neural networks. In addition to his technical skills, Qian has demonstrated outstanding leadership capabilities by serving as the class monitor and contributing to his college’s new media promotion initiatives. He has actively led his classmates to achieve multiple awards at the college level, earning personal recognition as an excellent Communist Youth League cadre. His work ethic, problem-solving ability, and teamwork have set him apart as a student leader and aspiring researcher. With his growing expertise in control systems, programming, and intelligent instrumentation, Qian Likun is positioning himself as a promising researcher with the potential to make significant contributions to the field of automation and intelligent systems in the near future.
Professional Profile
Education
Qian Likun is currently enrolled at China University of Geosciences (Wuhan), where he has been studying Automation since September 2018. His undergraduate education has provided him with comprehensive knowledge of automation systems, control theory, embedded technologies, and sensor applications. Throughout his studies, he has maintained a GPA of 3.01 and successfully completed a diverse range of technical courses such as analog electronic technology, digital logic circuit design, digital signal processing, system analysis, embedded programming, and object-oriented software development. These courses have helped him build a solid theoretical foundation and practical skill set. Qian’s education has also included specialized training in big data processing technologies for manufacturing and advanced system control strategies. His participation in several project-based learning modules has further enhanced his engineering abilities and problem-solving skills. His academic journey reflects not only his dedication to learning but also his ability to apply knowledge effectively to real-world scenarios. Qian has also achieved English proficiency certifications, having passed CET-4 and CET-6, and earned a Computer Level 2 certification in C++, which complements his automation expertise with solid programming capabilities. His educational background has fully equipped him to contribute meaningfully to complex research in automation and intelligent control systems.
Professional Experience
Although Qian Likun is in the early stages of his professional journey, he has accumulated substantial project-based experience that closely mirrors industry applications. He has led and contributed to multiple innovative projects during his time at China University of Geosciences. Notably, Qian successfully designed and implemented a cascade control system for a water tank and pipeline pressure monitoring, using PID control and Ethernet communication to achieve multi-machine interaction with an impressive 85% control precision. He independently built an integrated motion control experimental platform capable of simple three-dimensional relief processing and developed a modular CNC control interface. His hands-on experience also includes controlling servo motors via 51 microcontrollers, designing circuits for microvoltage signal acquisition, and applying LABVIEW software for upper computer visualization. Additionally, he utilized C++ and QT to create a multifunctional human-machine interaction calculator capable of performing both basic arithmetic and complex trigonometric operations. His graduation project focuses on RGBD salient object detection using convolutional neural networks and bifurcation backbone strategies. Qian’s practical experience demonstrates his ability to handle multidisciplinary engineering tasks, from hardware design to embedded system development and intelligent control applications, making him a well-rounded and capable early-career researcher.
Research Interest
Qian Likun’s research interests are centered on automation systems, intelligent instrumentation, embedded control, and intelligent perception technologies. He is particularly fascinated by the integration of sensor technologies with embedded systems to achieve precise control in real-time industrial environments. His work has also ventured into the field of intelligent detection, including subsurface conductor identification and salient object detection using RGBD imaging and convolutional neural networks. Qian is deeply interested in the development of intelligent monitoring systems that leverage human-machine interfaces (HMI) and multi-device communication through Ethernet networks. His passion lies in designing practical control systems that are both accurate and efficient, particularly in complex industrial processes. Furthermore, his recent exploration of deep learning methodologies, especially in salient object detection using bottom-up feature extraction and bifurcation backbone strategies, reflects his growing interest in artificial intelligence and machine vision applications. He is motivated to pursue research that blends traditional control theories with modern computational intelligence techniques to solve real-world challenges. Qian aspires to further investigate advanced control algorithms, embedded smart devices, and data-driven decision-making systems in future academic or industry research, aiming to contribute to the advancement of intelligent automation and control engineering.
Research Skills
Qian Likun possesses a diverse and practical set of research skills that span programming, circuit design, motion control, system modeling, and embedded development. He is proficient in programming languages such as C++ and MATLAB, which he has used to design embedded software, motion control systems, and data visualization interfaces. His expertise in control systems includes practical application of PID control algorithms, system modeling, and real-time control implementations. Qian has hands-on skills in building experimental platforms for motion processing, servo motor control using 51 microcontrollers, and data acquisition through differential amplification circuits. He has also demonstrated the ability to develop multi-functional human-machine interaction interfaces using QT and C++ for embedded applications. His hardware knowledge extends to sensor integration, analog and digital circuit design, and microcontroller programming. Additionally, Qian is familiar with machine learning techniques, particularly convolutional neural networks, which he applied in his graduation project for salient object detection. His skill set is further strengthened by his capability to design networked systems that enable multi-device communication using Ethernet protocols. Qian’s combination of software development, hardware control, signal processing, and intelligent algorithm application makes him a versatile researcher capable of addressing complex automation challenges.
Awards and Honors
Throughout his academic journey, Qian Likun has received multiple recognitions for both his leadership and academic contributions. He has served as the class monitor at China University of Geosciences (Wuhan), successfully leading his class to receive the “Excellent Class” award at the college level on several occasions. His dedication and organizational skills were further acknowledged when he was honored with the title of “Outstanding Communist Youth League Cadre” at the university level. Qian also played an active role in the university’s New Media Promotion Department, where he contributed to the management and content creation for the Automation College’s official WeChat platform. These leadership roles have allowed him to develop strong communication, teamwork, and project management skills in parallel with his technical education. His certification achievements include passing the Computer Level 2 examination in C++ and successfully completing both the College English Test (CET-4 and CET-6), demonstrating his competency in programming and his readiness for international collaboration. These awards and recognitions highlight his well-rounded profile, balancing academic performance, research activities, and social engagement, which together showcase his suitability as a dedicated and promising young researcher.
Conclusion
Qian Likun is a highly motivated, technically skilled, and leadership-oriented young researcher with a growing background in automation and intelligent control systems. His solid foundation in embedded technologies, motion control, signal acquisition, and human-machine interface design, combined with his demonstrated ability to lead project teams and manage complex system integrations, positions him as a promising talent in the engineering field. While he is still at the beginning of his research journey, his proactive engagement in hands-on projects and his exploration of cutting-edge technologies like convolutional neural networks reflect his potential for impactful future research contributions. Qian has demonstrated excellent leadership skills, receiving recognition for both academic performance and community engagement. However, to elevate his research profile to the next level, he would benefit from increasing his involvement in peer-reviewed research publications, enhancing his academic output, and expanding his international collaborations. With continued dedication, academic refinement, and professional development, Qian Likun has the potential to grow into a highly capable and innovative researcher who can contribute significantly to the advancement of automation, intelligent systems, and interdisciplinary engineering solutions.
Publications Top Notes
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Title: Design of audio to image cross-modal learning and generation based on single-layer CoPt spin-orbit torque devices
Authors: Likun Qian, Liu Yang, Chao Zuo, Ying Tao, Wendi Li, Fang Jin, Huihui Li, Kaifeng Dong
Year: 2025
Journal: Journal of Magnetism and Magnetic Materials
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Title: Design of spike-timing-dependent plasticity synapses based on CoPt-SOT device and its application in all-spin spiking neural network
Authors: Liu Yang, Shuguang Zhang, Likun Qian, Ying Tao, Fang Jin, Huihui Li, Zhe Guo, Rujun Tang, Kaifeng Dong
Year: 2025
Journal: Applied Physics Letters