Weiyang Chen | image processing | Best Researcher Award

Dr. Weiyang Chen | image processing | Best Researcher Award

Qufu Normal University | China

Publication Profile

Scopus

๐ŸŽ“ EARLY ACADEMIC PURSUITS

Dr. Weiyang Chen began his academic journey with a strong foundation in science and technology, culminating in a Ph.D. from the Chinese Academy of Sciences in 2015. His early academic work laid the groundwork for his future focus on image processing, data analysis, and bioinformatics.

๐Ÿ’ผ PROFESSIONAL ENDEAVORS

Currently an Associate Professor at the School of Cyber Science and Engineering, Qufu Normal University, Dr. Chen has significantly contributed to both teaching and research. He has participated in 5 consultancy or industry-sponsored projects and holds key roles, such as Deputy Secretary General of the Cloud Computing and Big Data Committee and Bentham Ambassador.

๐Ÿ”ฌ CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Chenโ€™s research spans bioinformatics, video and image processing, and algorithm development. He has authored over 50 publications, holds 12 patents, and developed several software applications. He has completed or is currently conducting 8 research projects, reflecting his leadership and innovation.

๐ŸŒ IMPACT AND INFLUENCE

His research has been featured in international media including TIME, The Guardian, NewScientist, Science News, and Daily Mail. With an h-index of 16 on ResearchGate, his work has a strong academic footprint and public engagement.

๐Ÿ“š ACADEMIC CITES AND RECOGNITION

Dr. Chen has published 38 articles in SCI and Scopus-indexed journals. He has served on 6 academic conference committees and contributes to scientific discourse through his profiles at ResearchGate and his university homepage.

๐Ÿค COLLABORATIONS AND NETWORKS

He collaborates with distinguished scholars like Professor Jingdong Han (Peking University) and Dr. Yi Pan, a Fellow of numerous international academies and engineering institutes. These partnerships enhance the quality and visibility of his research.

๐Ÿ† LEGACY AND FUTURE CONTRIBUTIONS

Dr. Chen aims to further explore bioinformatics and artificial intelligence, with a focus on real-world applications. His work in software development, interdisciplinary research, and professional service ensures his lasting academic legacy and continuing innovation.

๐Ÿฅ‡ AWARD PREFERENCE

For his outstanding achievements and global impact, Dr. Weiyang Chen is a strong nominee for the Best Researcher Award.

๐Ÿ“š TOP NOTES PUBLICATIONS

๐Ÿ“„ 1. A high precision method of segmenting complex postures in Caenorhabditis elegans and deep phenotyping to analyze lifespan
  • Authors: Bingyue Dong, Weiyang Chen

  • Journal: Scientific Reports

  • Year: 2025

๐Ÿ“„ 2. Exploring the relationship among Alzheimerโ€™s disease, aging and cognitive scores through neuroimaging-based approach
  • Authors: Jinhui Sun, Jingdong Jackie Han, Weiyang Chen

  • Journal: Scientific Reports

  • Year: 2024

๐Ÿ“„ 3. An automatic measurement method for the response of Caenorhabditis elegans to chemicals
  • Authors: Nan Zhang, Yanmin Nie, Bingyue Dong, Weiyang Chen, Shan Gao

  • Journal: Technology and Health Care
    (Official Journal of the European Society for Engineering and Medicine)

  • Year: 2024

๐Ÿ“„ 4. Automated recognition and analysis of body bending behavior in C. elegans
  • Authors: Hui Zhang, Weiyang Chen

  • Journal: BMC Bioinformatics

  • Year: 2023

Amin Hekmatmanesh | Algorithm Development | Best Researcher Award

Dr. Amin Hekmatmanesh l Algorithm Development ย | Best Researcher Award

LUT University, Finland

Author Profile

Google Scholar

๐Ÿ”Ž Summary

Dr. Amin Hekmatmanesh is a skilled biomedical engineer and data scientist, specializing in wearable sensors, AI, and machine learning applications for health technologies. He has extensive experience in biosignal processing (EEG, ECG, PPG, EMG, GSR, IMU), rehabilitation robotics, and medical device development. With a Ph.D. in Mechanical Engineering (Biomedical Engineering), he has made significant contributions to the field by developing real-time systems for rehabilitation and health monitoring. His research focuses on using AI to advance rehabilitation robotics and human-robot interactions, publishing over 30 peer-reviewed articles. He is also an active reviewer and editorial board member for several high-ranking journals.

๐ŸŽ“ Education

Dr. Hekmatmanesh holds a Ph.D. in Mechanical Engineering (Biomedical Engineering) from LUT University in Finland, where he achieved a GPA of 4.33. His dissertation focused on artificial intelligence and machine learning for EEG signal processing in rehabilitation robotics. He also completed his M.Sc. in Biomedical Engineering at Shahed University in Iran, with a perfect GPA of 4.0, and a B.Sc. in Electrical Engineering from Islamic Azad University, graduating with a GPA of 4.1.

๐Ÿ’ผ Professional Experience

Dr. Hekmatmanesh has a diverse professional background, having worked as a Lead Project Manager at Mevea Company, where he managed health monitoring system projects, incorporating wearable sensor technology. At Flowgait Company, he contributed to mathematical solutions for horse motion analysis. As a Junior Researcher and Project Manager at LUT University, he focused on wearable sensor systems and health monitoring. Additionally, he worked as a Research Assistant at Tehran University, working on diagnostic algorithms and therapeutic systems in health technologies.

๐Ÿ“š Academic Citations

Dr. Hekmatmanesh has published over 30 peer-reviewed papers, including book chapters and review articles, and his work has contributed significantly to the biomedical engineering and AI fields. His research has received wide recognition, and he is regularly invited to participate in scientific conferences and review for high-impact journals, showcasing his influence and contributions to advancing health technologies.

๐Ÿ”ง Technical Skills

Dr. Hekmatmanesh is highly proficient in biosignal processing, including EEG, ECG, PPG, EMG, GSR, and IMU signals. He is skilled in machine learning and AI, specifically for biosignal classification and real-time system development. His technical expertise extends to embedded electronics, sensor design, and circuit board assembly. He is proficient in Python and Matlab for data analysis and has experience using version control tools like GitHub to manage research projects.

๐ŸŽ“ Teaching Experience

Dr. Hekmatmanesh has been actively involved in teaching and mentoring within the biomedical engineering field. He has supervised PhD students and contributed to academic programs by delivering lectures and guiding research projects in health technologies, machine learning, and rehabilitation robotics.

๐Ÿ”ฌ Research Interests On Algorithm Development

Dr. Hekmatmaneshโ€™s research interests include the development of wearable sensor systems for health monitoring, AI and machine learning techniques for biosignal classification, and the design and control of rehabilitation robotics. He is also focused on human-robot interactions and improving prosthetics control through innovative AI applications in healthcare.

๐Ÿ“– Top Noted Publications

Nanocaged platforms: modification, drug delivery and nanotoxicity. Opening synthetic cages to release the tiger
    • Authors: PS Zangabad, M Karimi, F Mehdizadeh, H Malekzad, A Ghasemi, …
    • Journal: Nanoscale
    • Year: 2017
Review of the state-of-the-art of brain-controlled vehicles
    • Authors: A Hekmatmanesh, PHJ Nardelli, H Handroos
    • Journal: IEEE Access
    • Year: 2021
Neurosciences and wireless networks: The potential of brain-type communications and their applications
    • Authors: RC Moioli, PHJ Nardelli, MT Barros, W Saad, A Hekmatmanesh, …
    • Journal: IEEE Communications Surveys & Tutorials
    • Year: 2021
A combination of CSP-based method with soft margin SVM classifier and generalized RBF kernel for imagery-based brain computer interface applications
    • Authors: A Hekmatmanesh, H Wu, F Jamaloo, M Li, H Handroos
    • Journal: Multimedia Tools and Applications
    • Year: 2020
EEG control of a bionic hand with imagination based on chaotic approximation of largest Lyapunov exponent: A single trial BCI application study
    • Authors: A Hekmatmanesh, RM Asl, H Wu, H Handroos
    • Journal: IEEE Access
    • Year: 2019