Dr. Nan Liu | Intelligent Manufacturing Awards | Best Researcher Award

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Dr. Nan Liu | Intelligent Manufacturing Awards | Best Researcher Award 

Dr. Nan Liu, Hefei University of Technology, China

Dr. Nan Liu is a dedicated researcher and faculty member at Hefei University of Technology, specializing in intelligent manufacturing with a focus on optimizing gear production through AI-driven algorithms. His work aims to enhance processing quality, reduce costs, and advance smart manufacturing technologies. He has led research funded by the National Natural Science Foundation of China (Project No. U22B2084) and authored high-impact publications, including a notable SCI-indexed article on spiral bevel gear grinding force prediction using generalized regression neural networks. Dr. Liu’s contributions lie at the intersection of mechanical engineering and artificial intelligence, positioning him as a rising expert in the field of advanced manufacturing systems.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award – Dr. Nan Liu

Dr. Nan Liu demonstrates strong potential and emerging excellence in the domain of intelligent manufacturing, particularly through the integration of artificial intelligence in gear processing. His current research under the National Natural Science Foundation of China (Project No. U22B2084) exemplifies his capability to address complex engineering problems using AI-driven methodologies.

🎓 Education & Qualifications

  • Ph.D. in Mechanical or Manufacturing-related field (inferred from expertise, institution not specified)

  • Expert in Artificial Intelligence Applications in gear manufacturing and intelligent systems

💼 Work Experience

  • Assistant Professor, Hefei University of Technology

  • Specializes in applying AI algorithms to optimize gear manufacturing processes

  • Focused on improving grinding force prediction, processing quality, and reducing production costs

🏆 Achievements

  • 🔬 Research Grant from National Natural Science Foundation of China (Project No. U22B2084)

  • 📄 Published a high-impact journal article in Engineering Applications of Artificial Intelligence (Elsevier, 2025)

  • 🧠 Developed a Generalized Regression Neural Network model for spiral bevel gear force prediction

  • 🛠️ Contributed to advancing intelligent manufacturing technologies

🥇 Award & Honors

  • 🏅 Award Category Preference: Best Research Scholar Award

  • 📌 Recognized for bridging AI techniques with precision gear manufacturing

Publication Top Notes:

Research on grinding force prediction of spiral bevel gear based on generalized regression neural network and undeformed grinding chips

Research on a nonlinear quasi-zero stiffness vibration isolator with a vibration absorber

Assoc. Prof. Dr. Xiaozhen Lian | Product Design Awards | Best Researcher Award

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Assoc. Prof. Dr. Xiaozhen Lian | Product Design Awards | Best Researcher Award 

Assoc. Prof. Dr. Xiaozhen Lian, Jimei University, China

Dr. Xiaozhen Lian is a dedicated researcher in product innovation design and intelligent manufacturing, with a Ph.D. in Mechanical Design and Theory from Xiamen University (2023). She also holds a Master’s degree in Management Science and Engineering from China University of Mining and Technology and a Bachelor’s degree in Industrial Engineering from Anhui Polytechnic University. Her academic and professional work centers on quality control in manufacturing processes, multi-attribute decision-making, risk prediction, modular product design, and user-centered redesign strategies. Dr. Lian has led and contributed to multiple national research projects, including those funded by the Ministry of Science and Technology and the National Natural Science Foundation of China. She has published extensively in top-tier journals such as Advanced Engineering Informatics, Journal of Engineering Design, and Soft Computing. In addition to her academic achievements, she holds several patents, has reviewed manuscripts for leading SCI and EI journals, and is recognized for her leadership and excellence in student organizations and technical competitions. A passionate long-distance runner and basketball enthusiast, she brings perseverance and teamwork into both her research and life pursuits.

Professional Profile:

SCOPUS

Summary of Suitability – Dr. Lian Xiaozhen for Best Researcher Award

Dr. Lian Xiaozhen is a highly promising and impactful early-career researcher in the field of intelligent manufacturing and product innovative design, with a strong academic foundation and a growing international research presence. With a Ph.D. in Mechanical Design and Theory from Xiamen University (2023), Dr. Lian integrates engineering, data science, and decision theory to advance modern manufacturing systems.

🎓 Education Background

  • 📍 Ph.D. in Mechanical Design and Theory
    Xiamen University, July 2023

  • 📍 Master’s in Management Science and Engineering
    China University of Mining and Technology (CUMT), July 2018

  • 📍 Bachelor’s in Industrial Engineering
    Anhui Polytechnic University (AHPU), July 2015

💼 Work & Research Experience

  • 🔬 Research Interests:

    • Product Innovative Design

    • Intelligent Manufacturing

    • Manufacturing Process Quality Control

    • Product Modular Design Theory

    • MADM, Risk Identification, Fuzzy Theory

  • 📊 Projects Involved:

    • Ministry of Science and Technology of China

    • Natural Science Foundation of China (multiple projects on inverse design, function module partition)

📝 Selected Publications

  • 📘 Advanced Engineering Informatics, 2023

  • 📘 Journal of Engineering Design, 2022

  • 📘 Soft Computing, 2023

  • 📘 Symmetry, 2022

  • 📘 Computer Integrated Manufacturing Systems

  • 📘 Journal of Machine Design

  • 📘 Journal of Shanghai Jiao Tong University

  • 📘 Conference on Frontiers of Design and Manufacturing (Accepted)

🏅 Achievements & Awards

  • 🥇 Postgraduate National Scholarship

  • 🥈 Undergraduate National Inspirational Scholarship

  • 🏆 First-Class Graduate Scholarships at CUMT & AHPU

  • 👏 Outstanding Student & Graduate of CUMT

  • 💡 Founder of IE Association at CUMT

  • 🗣️ 2nd Prize in PPT Speech Contest

  • 🏭 Excellent Intern at Tianma Microelectronics

  • 💬 Best Customer Satisfaction Intern at East China Institute of Optoelectronics

📑 Review & Patent Contributions

  • 🧪 SCI/EI Journal Reviewer (Reviewed >16 manuscripts)

  • 🛠️ 2 Utility Model Patents (1st Author)

  • 🔬 4 Invention Patents (1st Author)

🎖️ Additional Honors & Qualities

  • 👨‍🏫 Class Monitor, Department Director, Academic Secretary

  • 🧠 Strong adaptability, teamwork, and learning ability

  • 🏃‍♂️ Competed in National Half Marathons (2017, 2022)

  • 🧮 Participant in Huawei Cup & Jiangsu Math Modeling Contests

  • 📈 Proven personal growth and responsibility during Ph.D.

Publication Top Notes:

Selection method of design scheme for LCD products based on RA and DFMEA

Best Industrial Sensing Technology

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Introductio Best Industrial Sensing Technology

Welcome to the Best Industrial Sensing Technology Award, recognizing excellence in the development and application of sensor technologies across industries. This prestigious award aims to honor individuals and organizations pushing the boundaries of sensing technology to drive innovation and efficiency in industrial processes.

About the Award:

The Best Industrial Sensing Technology Award is open to individuals and organizations worldwide who have made significant contributions to the field of industrial sensing technology. There are no age limits for eligibility, and both professionals and academics are encouraged to apply. Qualifications should demonstrate a deep understanding of sensing technologies and their applications in industrial settings. Publications related to sensing technology are considered a strong indicator of eligibility.

Requirements:

Applicants are required to submit a detailed description of their work in the field of industrial sensing technology, including relevant publications and qualifications. Evaluation criteria include the originality, impact, and feasibility of the proposed technology, as well as its potential for advancing industrial processes. Submissions should adhere to the submission guidelines outlined below.

Submission Guidelines:

Submissions should include a biography of the applicant, an abstract of the sensing technology project, and supporting files such as publications or patents. The abstract should clearly describe the technology, its application, and its potential impact on industrial processes. Supporting files should provide evidence of the technology’s effectiveness and relevance.

Evaluation Criteria:

Submissions will be evaluated based on the originality, impact, and feasibility of the proposed technology, as well as the applicant’s qualifications and publications in the field of industrial sensing technology. Preference will be given to technologies that have the potential to significantly improve industrial processes and efficiency.

Recognition:

Winners of the Best Industrial Sensing Technology Award will receive a certificate of recognition and will be featured on our website and social media channels. They will also have the opportunity to present their work at an industry conference or seminar.

Community Impact:

The Best Industrial Sensing Technology Award aims to promote innovation and collaboration in the field of industrial sensing technology, ultimately leading to advancements that benefit industries and society as a whole.