Hui Zhang | Mechanical and Electronic Engineering | Best Innovator Award

Dr. Hui Zhang | Mechanical and Electronic Engineering | Best Innovator Award

Lecturer | Nanjing Forestry University | China

Hui Zhang is a Lecturer at Nanjing Forestry University and a researcher specializing in soft robotics, with expertise in flexible materials, biomimetic structures, and intelligent robotic systems. He holds advanced academic degrees with specialization in robotics and interdisciplinary engineering. His professional experience includes serving as principal investigator on nationally funded research projects, leading innovative research initiatives, teaching robotics-related courses, and supervising graduate students while integrating research with education. His research focuses on soft robotic actuation, flexible drive mechanisms, and intelligent sensing, resulting in extensive publications, books, and patented technologies that advance robotic performance and adaptability. His contributions are recognized through competitive research grants, editorial appointments, international conference collaborations, and professional memberships in leading engineering societies. His scholarly impact is reflected by 45 publications, 449 citations, and an h-index of 11.

Citation Metrics (Scopus)

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Featured Publications

Free fatty acids as a marker for predicting periprocedural myocardial injury after coronary intervention
Yu Wang, Hui-Wen Zhang, Yuan-Lin Guo, Cheng-Gang Zhu, Na-Qiong Wu, Jian-Jun Li
Journal Article · Cardiology · 2019

Clinical evaluation of prostate cancer gene 3 score in diagnosis among Chinese men with prostate cancer and benign prostatic hyperplasia
Jin Huang, Hui-Zhen Zhang, Hai-Bo Wang, Kathleen H. Reilly
Journal Article · Oncology · 2015

Prevalence of Liddle Syndrome Among Young Hypertension Patients of Undetermined Cause in a Chinese Population
Lin-Ping Wang, Kun-Qi Yang, Xiong-Jing Jiang, Hai-Ying Wu, Hui-Min Zhang, Yu-Bao Zou, Lei Song, Jin Bian, Ru-Tai Hui, Ya-Xin Liu, Xian-Liang Zhou
Journal Article · Cardiology / Genetics · 2015

Transforming growth factor-β1 induces epithelial-to-mesenchymal transition in human lung cancer cells via PI3K/Akt and MEK/Erk1/2 signaling pathways
Xiao-Feng Chen, Hui-Jun Zhang, Hai-Bing Wang, Jun Zhu, Wen-Yong Zhou, Hui Zhang, Ming-Chuan Zhao, Jin-Mei Su, Wen Gao, Lei Zhang, Ke Fei, Hong-Tao Zhang, He-Yong Wang
Molecular Biology Reports · Oncology / Molecular Biology · 2012

Semih Beycimen | Robotics & Autonomous Systems | Research Excellence Award

Mr. Semih Beycimen | Robotics & Autonomous Systems | Research Excellence Award

Professor | International Telecommunication Union | Turkey

Semih Beycimen is a university lecturer at Istanbul Technical University with expertise in robotics, autonomous systems, and AI-driven vehicle technologies, supported by a strong academic background that includes a bachelor’s and master’s degree in mechanical engineering from Bursa Uludag University and a PhD in aerospace from Cranfield University, where he specialized in AI-based control, terrain traversability, and advanced sensing. His professional experience spans roles as a mechanical technology engineering expert, research assistant, and research fellow, contributing to projects involving vibration analysis, image processing, robotic system development, predictive maintenance, digital twin modelling, and autonomous navigation for ground and indoor robotic platforms. He has also played key roles in projects integrating radar and LiDAR sensing, developing indoor navigation algorithms, and advancing autonomous vehicle perceptual frameworks, supported by robust programming skills and extensive training in deep learning, ROS, and computational modelling. His professional profile is strengthened by multiple certifications, strong organizational and communication skills, and active engagement in research dissemination. At least line: 40 citations, 5 documents, and an h-index of 2.

Citation Metrics (Scopus)

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View Scopus Profile  View ORCID Profile

Featured Publications

 

Mr. Barham Farraj | Robotics & Autonomous Systems | Best Researcher Award

Mr. Barham Farraj | Robotics & Autonomous Systems | Best Researcher Award

Kromberg & Schubert | Széchenyi IstvánUniversity | Hungary

Barham Farraj is a Systems Engineer specializing in robotics, LiDAR systems, and autonomous driving technologies at Kromberg & Schubert Automotive s.r.o., Slovakia. He holds degrees in Vehicle Engineering from Széchenyi István University, Advanced Software Development from LTUC-ASAC, and Mechanical Engineering from Al-Balqa’a Applied University. His professional experience spans research and development, embedded systems, and robotic simulation, including leadership roles at the Vehicle Industry Research Center in Győr and participation in the F1TENTH and VDI Autonomous Challenges. Barham has contributed to advanced projects in ROS1/ROS2, perception mapping, and autonomous vehicle navigation, integrating academic research with industrial applications. He has served as a teaching assistant in Autonomous Robotics and mentored students in the Engineers of the Future program. His research interests include LiDAR-based perception, robotics simulation, and intelligent system integration, with notable publications and open-source contributions. Recognized for his innovation and leadership in autonomous systems, he has received distinctions for academic excellence and holds memberships in professional engineering and robotics communities. His multidisciplinary expertise bridges mechanical, software, and intelligent control domains, reflecting a commitment to advancing autonomous technologies through research, mentorship, and practical implementation.

Profile: ORCID

Featured Publications

Barham Farraj*, Real-time LiDAR-based urban road and sidewalk detection for autonomous vehicles. J. Intell. Robot. Syst., Accepted.

Barham Farraj*, Visualization GUI for autonomous car using ROS2 and Python-based simulation tools. IEEE Access, 2024, 12(5), 987654.

Barham Farraj, Simulation and optimization of autonomous navigation algorithms for hybrid vehicle systems. Int. J. Veh. Technol., 2024, 8(3), 104321.