Helmi Ayari | Data processing | Research Excellence Award

Published on by Research Data Analysis

Mr. Helmi Ayari | Data processing | Research Excellence Award

Université Ibn khaldoun | Tunisia

Helmi Ayari is a doctoral researcher in Artificial Intelligence at the École Polytechnique de Tunisie, focusing on machine learning, deep learning, and intelligent imaging systems, with a research track record that includes 3 published documents, an h-index of 1, and citations from 33 documents. He holds a Master of Research in Intelligent Systems for Imaging and Computer Vision and a fundamental Bachelor’s degree in Computer Science. His work includes contributions to medical image analysis, explainable AI, and optimization techniques, with notable publications such as a comparative study of classical versus deep learning-based computer-aided diagnosis systems published in Knowledge and Information Systems (Q2), and a study integrating genetic algorithms with ensemble learning for enhanced credit scoring presented at the International Conference on Business Information Systems (Class B). Professionally, he has served as a Maître Assistant and teaching assistant, delivering courses in machine learning, deep learning, Python, R, computer architecture, and automata theory, while supervising Master’s research, coordinating academic programs, and contributing to hackathons and university events. His research interests span AI-driven decision systems, interpretable machine learning, evolutionary optimization, and applied deep learning. Recognized for both academic and pedagogical engagement, he continues advancing impactful AI research and education.

Profile : Scopus

Featured Publications

Computer-Aided Diagnosis Systems: A Comparative Study of Classical Machine Learning Versus Deep Learning-Based Approaches. Knowledge and Information Systems, published May 23, 2023. https://doi.org/10.1007/s10115-023-01894-7

Integrating Genetic Algorithms and Ensemble Learning for Improved and Transparent Credit Scoring. International Conference on Business Information Systems, June 25, 2025. (Class B)

Hui Zhang |  Biosensing and Bioimaging | Best Researcher Award

Published on by Research Data Analysis

Dr. Hui Zhang |  Biosensing and Bioimaging | Best Researcher Award

Nanjing Forestry University | China

Dr Hui Zhang holds a Bachelor in Mechanical Manufacturing & Automation from Southeast University (2004-2008), a Master in Mechanical Design & Theory from Jiangnan University (2009-2012), and a Doctorate in Mechatronic Engineering from Southeast University (2013-2018) with a joint PhD period at the National University of Singapore (2014-2016). He is currently Assistant Professor (Lecturer) at Nanjing Forestry University (from December 2024), following his previous role as Assistant Researcher at Southeast University (May 2018-Nov 2024). His research centres on mechatronic engineering, with a strong emphasis on dielectric elastomer actuators, tunable lenses, soft electroactive materials, additive manufacturing of functional structures, and AI-augmented sensing and diagnostics. He has published extensively in SCI journals on topics including biomimetic human-eye adaptive lenses, 3D printed dielectric elastomers, tunable imaging systems, and machine-learning enabled defect detection. His current h-index is 11 with 45 papers and 418 citations. He has also contributed to monographs and conference proceedings in advanced manufacturing and smart devices. His work has been recognised for innovation in soft robotics and functional materials, and he continues to push the frontier of coupling mechanical design, materials science and intelligent systems in mechatronics.

Profile : Scopus

Featured Publications

Zhang, H.*, Zhu, J., Wen, H., Xia, Z., and Zhang, Z. (2023). “Biomimetic human eyes in adaptive lenses with conductive gels” in Journal of the Mechanical Behavior of Biomedical Materials, 139:105689. This work presents adaptive biomimetic lenses using conductive gels for vision systems inspired by the human eye, emphasizing improved optical tuning performance.

Zhang, H., Wen, H., Zhu, J., Xia, Z., and Zhang, Z.* (2023). “3D printing dielectric elastomers for advanced functional structures: A mini-review” in Journal of Applied Polymer Science, e55015. This review highlights emerging advances in 3D-printed dielectric elastomers with potential for flexible electronics and smart soft devices.

Zhang, H., Xia, Z., Zhang, Z., and Zhu, J. (2022). “Miniature and tunable high voltage-driven soft electroactive biconvex lenses for optical visual identification” in Journal of Micromechanics and Microengineering, 32(6):064004. The study develops compact electroactive soft lenses enabling tunable optical focusing for miniature imaging and identification applications.

Zhang, H.*, Dai, M., Xia, Z., and Zhang, Z. (2021). “Computational analyses for tunable solid lenses coupling polyacrylamide hydrogel electrodes” in Bulletin of Materials Science, 44(2):78. A computational approach is introduced to analyze hydrogel-based tunable solid lenses that enhance precision in optical deformation control.

Zhang, H.*, Li, Z., Xie, Y., Xia, Z., and Zhang, Z. (2021). “Focus-tunable imaging analyses of the liquid lens based on dielectric elastomer actuator” in Bulletin of Materials Science, 44(2):148. This research demonstrates a liquid-based dielectric elastomer lens with adjustable focusing capability to support compact imaging technologies.