Bao Peng | Big Data | Excellence in Research Award

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Prof. Bao Peng | Big Data | Excellence in Research Award

Professor | Shenzhen University of Information Technology | China

Prof. Bao Peng is an expert in millimeter-wave radar sensing, computer vision, and intelligent signal processing, with a focus on device-free human sensing, gesture recognition, and multimodal data fusion. He has published 54 papers, cited over 580 times, 13 h-index and collaborated with more than 110 researchers globally. His key contributions include cross-modal radar frameworks with information-maximization enhancement, lightweight self-attention-free transformer models for gesture recognition, and fusion-driven architectures for end-to-end human motion understanding, enabling efficient, low-data, and interpretable AI solutions. His work also extends to industrial applications, such as intelligent monitoring of unmanned pumping stations and YOLO-based infrastructure inspection, demonstrating broad societal and industrial relevance. By combining advanced signal processing with practical AI deployment, Prof. Peng’s research strengthens human–machine interaction, autonomous systems, and smart sensing technologies, contributing to safer, more efficient, and globally impactful innovations.

Profile: Scopus

Featured Publications

1. (2025). Cross-modal device-free radar sensing with information maximization enhancement and few-shot learning. IEEE Transactions on Microwave Theory and Techniques.

2. (2025). Device-free gesture recognition using multidimensional feature representation and lightweight self attention-free transformer. IEEE Transactions on Consumer Electronics.

3. (2025). End-to-end human motion recognition with multidomain dual attention transformer fusion network and millimeter-wave radar. IEEE Transactions on Consumer Electronics.

Cited by: 7

4. (2024). Visual analysis method for unmanned pumping stations on dynamic platforms based on data fusion technology. Eurasip Journal on Advances in Signal Processing.

Cited by: 1

5. (2024). GAM-YOLOv8n: Enhanced feature extraction and difficult example learning for site distribution box door status detection. Wireless Networks.

Cited by: 5

Prof. Bao Peng research transforms radar-based perception into practical AI solutions, advancing intelligent monitoring, autonomous systems, and human–machine interaction to foster safer, smarter, and more sustainable technological ecosystems.

Amirhossein Ghasemi Abyaneh | Machine Learning | Best Researcher Award

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Mr. Amirhossein Ghasemi Abyaneh | Machine Learning | Best Researcher Award

Researcher | Kharazmi University | Iran

Mr. Amirhossein Ghasemi Abyaneh is an emerging scholar in the field of artificial intelligence applications in sustainable supply chains, affiliated with Kharazmi University, Tehran, Iran. His academic endeavors focus on integrating advanced data analytics, optimization techniques, and machine learning frameworks to enhance decision-making, efficiency, and sustainability across complex supply chain networks. With 3 published research papers and an h-index of 1, Mr. Abyaneh has begun establishing a scholarly footprint that bridges technology-driven innovation with environmental and operational resilience. His work, including the open-access article “An Analytical Review of Artificial Intelligence Applications in Sustainable Supply Chains” (2025, Supply Chain Analytics), provides critical insights into the evolving intersection of AI and sustainability, emphasizing how digital intelligence can optimize resource utilization, reduce carbon footprints, and strengthen circular economy practices. Having received citations from international scholars, he actively contributes to the global academic dialogue on sustainable logistics, smart manufacturing, and responsible innovation. Mr. Abyaneh’s collaborative research network includes seven co-authors from diverse academic and institutional backgrounds, reflecting a strong interdisciplinary approach that combines engineering, data science, and environmental management. His studies aim to foster both theoretical advancement and practical applicability, offering valuable implications for policymakers, corporations, and researchers seeking to transition toward greener, data-driven supply chains. Beyond academic impact, his contributions align with global sustainability goals, promoting knowledge transfer, digital equity, and responsible AI adoption for societal benefit.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Sharbati, A., Movahed, A. B., Abyaneh, A. G., & Rahmanian, F. (2025). Risk assessment of healthcare systems using the FMEA method: Medication management process. Journal of Future Digital Optimization, 1(1), 71–85.
Cited by: 4

2. Abyaneh, A. G., Movahed, A. B., Abyari, A., Nodehfarahani, A., & Khakbazan, M. (2025). Evaluating the RFID technology in Costco Company: A focus on logistics and supply chain management. Applied Innovations in Industrial Management, 5(2), 34–51.
Cited by: 2

3. Movahed, A. B., Abyaneh, A. G., Khakbazan, M., & Movahed, A. B. (2025). Smart economy cybersecurity: AI-driven risk management in digital markets. In Dynamic and Safe Economy in the Age of Smart Technologies (pp. 49–72).
Cited by: 2

4. Abyaneh, A. G., Ghanbari, H., Mohammadi, E., Amirsahami, A., & Khakbazan, M. (2025). An analytical review of artificial intelligence applications in sustainable supply chains. Supply Chain Analytics, 100173.
Cited by: 1

5. Abyaneh, A. G., Khakbazan, M., & Movahed, A. B. (2026). Artificial intelligence in digital marketing: Trends, challenges, and strategic opportunities. In Improving Consumer Engagement in Digital Marketing Through Cognitive AI (pp. 225–260)

Mr. Amirhossein Ghasemi Abyaneh envisions a future where artificial intelligence empowers sustainable industrial transformation, enabling supply chains to become more adaptive, transparent, and environmentally responsible. His research advances the integration of smart analytics and sustainability principles, fostering innovation that supports global climate resilience and ethical technological progress.

Mohammad Amin | Gradient boosting | Young Scientist Award

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Mr. Mohammad Amin | Gradient boosting | Young Scientist Award

Mohammad Amin | RWTH Aachen University | Germany

Mr. Mohammad Yazdi is a distinguished researcher and academic with expertise in information technology, e-learning systems, and research data management. He holds advanced degrees in information systems and has built a robust academic and professional profile through his work in integrating IT solutions for collaborative research, developing interactive e-learning media, and enabling process mining for research data life cycles. Professionally, he has contributed to several high-impact projects, including the implementation of web services for integrated government systems, evaluation of FAIR data management architectures, and the orchestration of research cluster collaborations, demonstrating strong technical and leadership skills. His research focuses on e-learning as an interactive IT-based learning medium, process mining, IT resource management in research projects, and operational support systems, with a publication record spanning reputable conferences and journals. His works, including “E-learning sebagai media pembelajaran interaktif berbasis teknologi informasi,” “How to Manage IT Resources in Research Projects? Towards a Collaborative Scientific Integration Environment,” and “Event Log Abstraction in Client-Server Applications,” have collectively garnered significant citations, underscoring their academic impact. He has been recognized for his scholarly contributions and actively participates in academic dissemination through editorial roles and conference presentations. With a commitment to advancing digital transformation in education and research, Mohammad Yazdi stands out as a thought leader and innovator in his field, with 29 citations across 23 documents, 10 publications, and an h-index of 4

Profile: Google Scholar | Scopus | ORCID

Featured Publications

1. M. Yazdi*, E-learning sebagai media pembelajaran interaktif berbasis teknologi informasi. Foristek, 2012, 2(1), 680.

2. M. Yazdi*, Implementasi Web-Service pada Sistem Pelayanan Perijinan Terpadu Satu Atap di Pemerintah Kota Palu. Seminar Nasional Teknologi Informasi & Komunikasi Terapan, 2012, 450–457, 24.

3. M. Politze, F. Claus, B. Brenger, M.A. Yazdi*, B. Heinrichs, A. Schwarz, How to Manage IT Resources in Research Projects? Towards a Collaborative Scientific Integration Environment. 2020, 22.

4. M.A. Yazdi*, P. Farhadi Ghalati, B. Heinrichs, Event Log Abstraction in Client-Server Applications. 13th Int. Conf. Knowledge Discovery and Information Systems, 2021, 13.

5. M.A. Yazdi*, Enabling Operational Support in the Research Data Life Cycle. Proc. 1st Int. Conf. Process Mining – Doctoral Consortium, 2019, 13.