Genfeng Liu | Engineering | Best Researcher Award

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Dr. Genfeng Liu | Engineering | Best Researcher Award

Research Scholar at Henan University of Technology, China

Genfeng Liu is a highly qualified candidate for the Best Researcher Award, with a strong background in control science and engineering, specializing in data-driven control, adaptive control, and fault-tolerant systems. His research spans intelligent transportation, multiagent systems, and nonlinear systems, contributing to high-impact IEEE journals such as IEEE Transactions on Cybernetics (IF: 19.118) and IEEE Transactions on Neural Networks and Learning Systems (IF: 14.255). As a reviewer for leading journals, he holds strong academic credibility. His work on model-free adaptive control and cybersecurity applications demonstrates real-world relevance. To enhance his profile, he could expand international collaborations, increase industry applications, and lead large-scale research projects. While his contributions are highly significant, further engagement in technology transfer and interdisciplinary research would strengthen his impact. Overall, his extensive publication record and research influence make him a strong contender for the award, with potential for even greater contributions in the future.

Professional Profile

Education

Genfeng Liu received his Ph.D. in Control Science and Engineering from Beijing Jiaotong University, China, in 2021. His doctoral research focused on advanced control methodologies, including data-driven control, iterative learning control, and fault-tolerant control, which have significant applications in intelligent transportation and nonlinear systems. Throughout his academic journey, he developed expertise in adaptive control and multiagent systems, contributing to cutting-edge research in automation and cybernetics. His education provided a strong foundation in both theoretical and applied control engineering, enabling him to publish in prestigious IEEE journals. Additionally, his academic background equipped him with the analytical and problem-solving skills necessary to address complex challenges in system automation and intelligent control. His commitment to continuous learning and research excellence is evident in his contributions to high-impact scientific literature and his role as a reviewer for renowned international journals, solidifying his reputation as an expert in his field.

Professional Experience

Genfeng Liu is currently a Lecturer at the College of Electrical Engineering, Henan University of Technology, Zhengzhou, China. His professional experience revolves around advanced control engineering, with a focus on data-driven control, adaptive control, and fault-tolerant systems. As a researcher, he has made significant contributions to intelligent transportation systems, multiagent systems, and nonlinear control, publishing extensively in high-impact IEEE journals. Beyond his research, he actively participates in academic peer review for prestigious journals such as IEEE Transactions on Cybernetics and IEEE Transactions on Intelligent Vehicles, reinforcing his role as a respected scholar in the field. His expertise extends to supervising students and collaborating on interdisciplinary projects, bridging the gap between theoretical advancements and practical applications. His ongoing work in model-free adaptive control and cybersecurity-related control mechanisms further strengthens his impact in academia and industry, positioning him as a leader in modern control systems and intelligent automation research.

Research Interest

Genfeng Liu’s research interests lie in advanced control engineering, with a strong focus on data-driven control, adaptive control, and fault-tolerant control. His work explores iterative learning control and model-free adaptive control techniques, particularly in applications related to intelligent transportation systems, nonlinear systems, and multiagent systems. He is also interested in cybersecurity aspects of control systems, such as defense mechanisms against false data injection attacks. His research aims to enhance the efficiency, safety, and reliability of automation in modern transportation and industrial systems. By integrating artificial intelligence with control theory, he seeks to develop innovative solutions for complex, real-world engineering challenges. His studies have been published in top-tier journals, reflecting his commitment to advancing theoretical and applied knowledge in control science. Additionally, his expertise in intelligent transportation and system optimization continues to drive impactful contributions to the fields of automation, cybernetics, and industrial informatics.

Award and Honor

Genfeng Liu has received several accolades and recognition for his outstanding contributions to the field of control science and engineering. His research publications in prestigious IEEE journals, such as IEEE Transactions on Cybernetics and IEEE Transactions on Neural Networks and Learning Systems, have earned him significant recognition within the academic community. As an active reviewer for renowned international journals, he has been acknowledged for his critical evaluations and contributions to the peer-review process. His innovative work in data-driven control, adaptive control, and fault-tolerant systems has positioned him as a leading researcher in intelligent transportation and nonlinear systems. Additionally, his participation in high-profile conferences and collaborations with esteemed researchers further highlight his impact in the field. While his research achievements are commendable, pursuing national and international research grants and awards would further enhance his recognition and establish him as a distinguished leader in control engineering and automation.

Research Skill

Genfeng Liu possesses strong research skills in advanced control engineering, specializing in data-driven control, adaptive control, and fault-tolerant control. He is proficient in developing and implementing iterative learning control and model-free adaptive control strategies for complex nonlinear and multiagent systems. His expertise extends to intelligent transportation systems, where he applies innovative control techniques to enhance automation and safety. He is highly skilled in mathematical modeling, algorithm development, and system optimization, enabling him to solve real-world engineering challenges effectively. His ability to conduct in-depth theoretical analysis and translate findings into practical applications is evident in his numerous high-impact publications in top-tier IEEE journals. Additionally, his experience as a reviewer for prestigious academic journals demonstrates his critical thinking and analytical skills. His research capabilities, combined with his ability to collaborate on interdisciplinary projects, make him a valuable contributor to the fields of cybernetics, automation, and industrial informatics.

Conclusion

Genfeng Liu is a highly suitable candidate for the Best Researcher Award due to his exceptional research output, high-impact publications, and contributions to control engineering and intelligent transportation systems. To further strengthen his candidacy, increasing international collaborations, practical industry applications, and leadership roles in large-scale projects would make his research even more impactful.

Publications Top Noted

  • Title: Improved Model-Free Adaptive Predictive Control for Nonlinear Systems with Quantization Under Denial of Service Attacks
    Authors: Genfeng Liu, Jinbao Zhu, Yule Wang, Yangyang Wang
    Year: 2025
    Citation: DOI: 10.3390/sym17030471

  • Title: Adaptive Iterative Learning Fault-Tolerant Control for State Constrained Nonlinear Systems With Randomly Varying Iteration Lengths
    Authors: Genfeng Liu, Zhongsheng Hou
    Year: 2024
    Citation: DOI: 10.1109/TNNLS.2022.3185080

  • Title: Cooperative Adaptive Iterative Learning Fault-Tolerant Control Scheme for Multiple Subway Trains
    Authors: Genfeng Liu, Zhongsheng Hou
    Year: 2022
    Citation: DOI: 10.1109/TCYB.2020.2986006

  • Title: RBFNN-Based Adaptive Iterative Learning Fault-Tolerant Control for Subway Trains With Actuator Faults and Speed Constraint
    Authors: Genfeng Liu, Zhongsheng Hou
    Year: 2021
    Citation: DOI: 10.1109/TSMC.2019.2957299

  • Title: Adaptive Iterative Learning Control for Subway Trains Using Multiple-Point-Mass Dynamic Model Under Speed Constraint
    Authors: Genfeng Liu, Zhongsheng Hou
    Year: 2021
    Citation: DOI: 10.1109/TITS.2020.2970000

  • Title: A Model-Free Adaptive Scheme for Integrated Control of Civil Aircraft Trajectory and Attitude
    Authors: Gaoyang Jiang, Genfeng Liu, Hansong Yu
    Year: 2021
    Citation: DOI: 10.3390/sym13020347

  • Title: A Data-Driven Distributed Adaptive Control Approach for Nonlinear Multi-Agent Systems
    Authors: Xian Yu, Shangtai Jin, Genfeng Liu, Ting Lei, Ye Ren
    Year: 2020
    Citation: DOI: 10.1109/ACCESS.2020.3038629

  • Title: Model-Free Adaptive Direct Torque Control for the Speed Regulation of Asynchronous Motors
    Authors: Ziwei Zhang, Shangtai Jin, Genfeng Liu, Zhongsheng Hou, Jianmin Zheng
    Year: 2020
    Citation: DOI: 10.3390/pr8030333

Anuj Kumar | Engineering | Best Researcher Award

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Mr. Anuj Kumar | Engineering | Best Researcher Award

Assistant Professor at Management Education & Research Institute, Janakpuri, India

Anuj Kumar is an accomplished academic and researcher in Computer Science & Engineering, currently pursuing a Ph.D. in Image Processing at AKTU, Lucknow. With over a decade of teaching experience at institutions like Guru Gobind Singh Indraprastha University and IIMT College of Engineering, he has significantly contributed to education and research. His expertise spans artificial intelligence, computer graphics, and data structures, complemented by proficiency in programming languages such as Python, C++, and MATLAB. He has published research papers in Scopus-indexed journals, IEEE Explorer, and Elsevier, along with a book chapter on distributed artificial intelligence. Recognized for his contributions, he was awarded at the Smart India Hackathon 2018 and qualified GATE 2012 with an 85.04 percentile. Anuj is actively involved in academic leadership, faculty development, and university assessments. With a commitment to innovation and interdisciplinary research, he aspires to advance computational methodologies and industrial applications in artificial intelligence and image processing.

Professional Profile 

Education

Anuj Kumar has a strong academic background in Computer Science & Engineering. He is currently pursuing a Ph.D. in Image Processing from Dr. A.P.J. Abdul Kalam Technical University (AKTU), Lucknow, Uttar Pradesh, demonstrating his commitment to advanced research. He earned his M.Tech in Computer Science & Engineering from Guru Gobind Singh Indraprastha University, Delhi, in 2014, securing a first division. His undergraduate studies include a B.Tech in Computer Science & Engineering from the Institution of Electronics & Telecommunication Engineers (IETE), Delhi, in 2011, also with first-division honors. Additionally, he holds a Three-Year Diploma in Computer Science & Engineering from IETE, Delhi (2006). His early education was completed under the U.P. Board, where he finished 10th grade (2000) and 12th grade (2003) in the second division. His educational journey, enriched with technical certifications like MCAD (Microsoft Certified Application Developer) in 2006, has laid a strong foundation for his expertise in computing and research.

Professional Experience

Anuj Kumar has extensive academic experience as an Assistant Professor in Computer Science & Engineering, with a teaching career spanning over a decade across prestigious institutions. Since July 2023, he has been serving at MERI College of Engineering and Technology, Haryana. Prior to this, he worked at IIMT College of Engineering, Greater Noida (2022–2023) and Greater Noida Institute of Technology, GGSIPU (2018–2022), where he contributed to curriculum development and research initiatives. He also held academic positions at USIC&T, Guru Gobind Singh Indraprastha University (2017–2018) and Ram-Eesh Institute of Engineering & Technology (2017). Earlier in his career, he served at Baba Saheb Ambedkar Institute of Technology & Management (2014–2016) and The Institution of Electronics & Telecommunication Engineers, Delhi (2011–2012). His vast experience includes mentoring students, conducting faculty development programs, and leading academic audits, showcasing his commitment to education, research, and institutional development.

Research Interest

Anuj Kumar’s research interests lie at the intersection of computer vision, image processing, artificial intelligence, and computational methods. Currently pursuing a Ph.D. in Image Processing, he focuses on developing advanced techniques for image enhancement, noise removal, and forgery detection using deep learning algorithms. His expertise extends to computer graphics, formal language automata, database management systems (DBMS), data structures, and discrete mathematics, which serve as the foundation for his research innovations. He has actively contributed to AI-driven industrial systems, biodiversity assessment using hyperspectral imaging, and disruptive innovations in tech-business analytics. His work has been published in Scopus-indexed journals, IEEE conference proceedings, and reputed international journals, reflecting the impact of his research. Additionally, he explores the applications of distributed artificial intelligence (DAI) for document retrieval, emphasizing intelligent data processing techniques. His dedication to cutting-edge research strengthens his role as a mentor and academician in the field of computer science and engineering.

Award and Honor

Anuj Kumar has been recognized for his academic excellence and research contributions through various awards and honors. He was awarded in the Smart India Hackathon 2018, a prestigious national-level competition promoting innovation and problem-solving skills. Demonstrating strong technical acumen, he qualified GATE 2012 with an impressive 85.04 percentile and a score of 302, showcasing his expertise in computer science and engineering. His achievements extend beyond academics, as he was the runner-up in the 100m race at IETE, New Delhi, in 2005, highlighting his diverse talents. Additionally, he has played a significant role in academia as a convener of the Joint Assessment Committee (JAC) for academic audits, deputy center superintendent for examinations, and university representative in various assessment programs. His dedication to research and education is further reflected in his memberships on editorial boards and professional organizations, solidifying his reputation as a distinguished academic and researcher.

Research Skill

Anuj Kumar possesses a strong research skillset that spans multiple domains within computer science and engineering, particularly in image processing, artificial intelligence, and computational methods. His expertise in deep learning, fuzzy techniques, and hyperspectral imaging enables him to develop innovative solutions for image enhancement, noise removal, and forgery detection. He is proficient in Python, MATLAB, C++, and various database management systems (DBMS), which support his research in data analysis, automation, and intelligent computing. His ability to critically analyze complex problems, design experiments, and implement advanced algorithms has led to multiple Scopus-indexed publications, IEEE conference presentations, and book chapters. Additionally, his role in academic audits, faculty development programs, and technical training workshops demonstrates his leadership in research and education. His strong analytical thinking, problem-solving capabilities, and hands-on approach to emerging technologies make him a highly skilled researcher in the field of computer vision and artificial intelligence.

Conclusion

Anuj Kumar has a strong academic foundation, technical expertise, and a growing research portfolio in computer science and engineering. His contributions to image processing, artificial intelligence, and industrial automation position him as a promising candidate for the Best Researcher Award. However, enhancing high-impact publications, research collaborations, and funding contributions would further strengthen his profile for this recognition.

Publications Top Noted

  • P., Jaidka, Preeti, P., Upadhyay, Prashant, A., Kumar, Aman, A.S., Kumar, Anuj Shiva, S.P., Yadav, Satya Prakash (2024). Transforming Coconut Farming with Deep Learning Disease Detection. Evergreen. Citations: 0

  • D., Sharma, Deepak, A.S., Kumar, Anuj Shiva, N., Tyagi, Nitin, S.S., Chavan, Sunil S., S.M.P., Gangadharan, Syam Machinathu Parambil (2024). Towards intelligent industrial systems: A comprehensive survey of sensor fusion techniques in IIoT. Measurement: Sensors. Citations: 3

  • S., Singh, Sandeep, B.K., Singh, B. K., A.S., Kumar, Anuj Shiva (2024). Multi-organ segmentation of organ-at-risk (OAR’s) of head and neck site using ensemble learning technique. Radiography. Citations: 3

  • R., Naz, Rahat, A.S., Kumar, Anuj Shiva (2024). Surveying Quantum-Proof Blockchain Security: The Era of Exotic Signatures. Conference Paper. Citations: 1