Maedeh Azadi Moghadam | Artificial Intelligence | Best Researcher Award

Dr. Maedeh Azadi Moghadam | Artificial Intelligence | Best Researcher Award

Biomedical Engineer | Semnan University | Iran

Dr. Maedeh Azadi Moghadam is an emerging researcher whose work advances the fields of biomedical engineering, neurotechnology, and human–machine interaction, with a particular focus on developing more reliable and human-centered brain–computer interface (BCI) systems. Her research interests span neural signal processing, SSVEP-based BCI optimization, cognitive fatigue detection, biomarker-based performance measurement, and the integration of physiological signals into more adaptive computational models. She is especially interested in understanding how fatigue and cognitive variability influence BCI accuracy, and her work aims to design intelligent systems capable of adjusting in real time to user states, ultimately improving usability for rehabilitation, assistive technologies, and next-generation neuroengineering applications. Dr. Moghadam’s research skills include biosignal analysis, EEG processing, feature extraction, algorithmic modeling, quantitative measurement techniques, and scientific writing, demonstrating her multidisciplinary strengths across engineering and neuroscience. According to Scopus, she has 3 indexed documents, 2 citations, and an h-index of 1, reflecting growing visibility and early academic impact in her domain. Although no formal awards or honors are listed for her in the available Scopus record, her contributions to innovative metrics—such as a continuous fatigue index for SSVEP-based BCI performance—highlight her potential for future recognition in neurotechnology and biomedical measurement science. Her publications demonstrate a commitment to improving the efficiency, accuracy, and adaptability of neuroengineering systems, particularly those intended for people with motor impairments or communication limitations. In conclusion, Dr. Maedeh Azadi Moghadam represents a promising researcher whose interdisciplinary work is helping shape the future of intelligent BCIs, cognitive state monitoring, and biomedical signal-driven technologies. Her expanding scientific contributions, combined with her advancing research skill set, position her for continued impact in the global scientific community and future leadership in neurotechnology innovation.

Profiles: Scopus | Google Scholar | LinkedIn

Featured Publications

Azadi Moghadam, M., & Maleki, A. (2023). Fatigue factors and fatigue indices in SSVEP-based brain–computer interfaces: A systematic review and meta-analysis. Frontiers in Human Neuroscience, 17, 1248474. Citations: 33

Maleki, A., & Azadimoghadam, M. (2022). Fatigue assessment using frequency features in SSVEP-based brain–computer interfaces. Iranian Journal of Biomedical Engineering, 16(3), 229–240.
Citations: 4

Moghadam, M. A., & Maleki, A. (2023). Fatigue detection in SSVEP-based BCIs using biomarkers: A comparative study. 2023 31st International Conference on Electrical Engineering (ICEE), 496–500. Citations: 2

Azadi Moghadam, M., & Maleki, A. (2024). Comparative study of frequency recognition techniques for steady-state visual evoked potentials according to the frequency harmonics and stimulus number. Journal of Biomedical Physics and Engineering. Citations: 1

Moghadam, M. A., & Maleki, A. (2025). A continuous fatigue index based on biomarkers for SSVEP-based brain–computer interfaces. Measurement, 118598.

The Dr. Maedeh Azadi moghadam’s research advances global innovation in neurotechnology by improving the accuracy, stability, and human-centered design of brain–computer interface systems through biomarker-driven fatigue detection and advanced signal analysis. By enhancing the reliability of assistive technologies and cognitive monitoring tools, the nominee’s work contributes meaningful benefits to science, healthcare, and industry, ultimately supporting more accessible, intelligent, and high-performing human–machine interaction solutions for society.

 

Jiafa Mao | Computer Science | Best Researcher Award

Prof. Jiafa Mao | Computer Science | Best Researcher Award

Professor at Zhejiang University College of Computer Science and Technology | China 

Prof. Jiafa Mao is an accomplished scholar and doctoral supervisor at the School of Computer Science and Technology, Zhejiang University of Technology, renowned for his expertise in information security, pattern recognition, computer vision, intelligent systems, and multimedia processing. He earned his Ph.D. in Pattern Recognition and Intelligent Systems from East China University of Science and Technology, followed by postdoctoral research at the Beijing University of Posts and Telecommunications. He has served as a professor, leading impactful research that bridges theory with real-world applications. Prof. Mao has directed and participated in numerous national and provincial-level projects, including the National 973 Program and NSFC initiatives, reflecting his strong research leadership. With over 60 publications in prestigious journals such as Pattern Recognition and IEEE Transactions, he has established an international academic footprint. A dedicated reviewer and active member of ACM, CCF, and CSIG, he continues to advance innovation and mentor future researchers.

Professional Profile

Scopus Profile 

Education

Prof. Jiafa Mao has built a strong academic foundation rooted in advanced computing sciences. He earned his Ph.D. in Pattern Recognition and Intelligent Systems from East China University of Science and Technology, where he focused on computational intelligence and system-level problem-solving. His doctoral journey equipped him with a deep understanding of information security, intelligent algorithms, and multimedia systems. To further enhance his research capabilities, he pursued postdoctoral studies at the Beijing University of Posts and Telecommunications. During this period, he engaged in cutting-edge investigations in computer science and technology, contributing to high-level research projects and collaborations with academic and industrial partners. This combined academic trajectory not only refined his expertise in areas such as pattern recognition and computer vision but also prepared him to become a future leader in the field, capable of addressing both theoretical challenges and practical applications.

Experience

Prof. Jiafa Mao has accumulated extensive academic and research experience, particularly in higher education and large-scale projects. He has served as a Professor and Doctoral Supervisor at the School of Computer Science and Technology, Zhejiang University of Technology. In this role, he has guided doctoral and postgraduate students, fostered innovation, and promoted high-quality research in areas like multimedia fingerprinting and intelligent systems. His professional journey also includes a productive postdoctoral tenure at the Beijing University of Posts and Telecommunications, where he sharpened his expertise in information security and data protection. Beyond academic teaching, he has led or participated in more than six national projects, including the National 973 Program and the National Natural Science Foundation of China, along with multiple ministerial, provincial, and industry-sponsored projects. His career reflects a balance of teaching, research, and leadership, demonstrating both scholarly excellence and real-world impact.

Research Interest

Prof. Jiafa Mao’s research interests span a wide spectrum of computer science disciplines, with a strong emphasis on information security and pattern recognition. He has extensively explored multimedia fingerprinting, information hiding, and intelligent systems, advancing methods that secure digital content in increasingly complex environments. His contributions to computer vision and image processing have supported applications ranging from identity verification to data protection, reinforcing the relevance of his work in both academic and industrial contexts. He is also engaged in the study of intelligent algorithms that integrate machine learning with evolving computational models, addressing challenges in automation and system reliability. Prof. Mao’s research aligns with pressing societal and technological needs, particularly in safeguarding information systems and advancing AI-driven solutions. With over 60 publications in top-tier journals and conferences, his studies not only enrich theoretical frameworks but also offer practical tools that address real-world challenges in computing and communication technologies.

Awards and Honors

Prof. Jiafa Mao’s career is distinguished by his strong record of scholarly recognition and professional service. His work has been featured in internationally respected journals such as Pattern Recognition, IEEE Transactions on Evolutionary Computation, and IEEE Transactions on Industrial Informatics, showcasing the global reach and quality of his contributions. He has served as a peer reviewer for numerous top journals and conferences, including IEEE Transactions on Cybernetics and the IEEE International Workshop on Information Forensics and Security, highlighting his trusted expertise within the academic community. His leadership in major projects funded by the National 973 Program and the National Natural Science Foundation of China reflects not only research excellence but also national recognition of his capabilities. Furthermore, his professional memberships in ACM, CCF, and CSIG demonstrate his active involvement in advancing the computing profession. These honors, alongside his extensive publication record, affirm his status as a highly respected researcher and academic leader.

Publication Top Notes

Title: Point-level feature learning based on vision transformer for occluded person re-identification
Year: 2024
Citation: 8

Title: Multi-granularity feature intersection learning for visible-infrared person re-identification
Year: 2025

Title: Basic theories and methods of target’s height and distance measurement based on monocular vision
Year: 2025
Citation: 1

Title: The 3D tooth model segmentation method based on GAC+PointMLP network
Year: 2025

Title: Feature optimization-guided high-precision and real-time metal surface defect detection network
Year: 2024
Citation: 3

Title: Workflows scheduling powered by execution time prediction model
Year: 2024
Citation: 1

Title: HashNeck is a Boosting Tool for Deep Learning to Hashing
Year: 2024

Conclusion

Prof. Jiafa Mao represents a distinguished scholar whose academic journey, research expertise, and leadership contributions firmly position him as a leading figure in the field of computer science. His work in information security, pattern recognition, multimedia fingerprinting, and intelligent systems has advanced both theoretical understanding and practical applications. With a Ph.D. in Pattern Recognition and Intelligent Systems and a successful postdoctoral tenure, he has established a strong foundation in computational intelligence and security-driven technologies. His role as a professor and doctoral supervisor has allowed him to mentor future researchers, while his involvement in national and industry-driven projects has enhanced his reputation as a solution-oriented innovator. Prof. Mao’s extensive publications, active peer-reviewing, and professional memberships in organizations like ACM and CCF underscore his global recognition and professional influence. With a balance of academic excellence and societal impact, he is a highly deserving candidate for prestigious recognitions such as the Best Researcher Award.