Peilin Shao | AI and Automation in Architecture | Young Researcher Award

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Assist. Prof. Dr. Peilin Shao | AI and Automation in Architecture | Young Researcher Award

Lecturer | Shanxi Datong University | China

Assist. Prof. Dr. Peilin Shao is a Lecturer at Shanxi Datong University specializing in intelligent manufacturing, with academic training in industrial and manufacturing systems engineering as well as mechanical design, manufacturing, and automation. He has been actively involved in advanced research on assembly process modeling, knowledge graph construction, and AI-driven inference, contributing to projects that integrate large language models with manufacturing knowledge systems and supporting intelligent decision-making in complex engineering processes. His work encompasses assembly deviation analysis, process knowledge graph frameworks, and intelligent question-answering methods, with publications in reputable journals such as the Proceedings of the Institution of Mechanical Engineers, Applied Sciences, and the International Journal of Advanced Manufacturing Technology, alongside conference contributions in intelligent networked systems. Dr. Shao has demonstrated research leadership through collaborative projects and scholarly contributions that advance intelligent manufacturing. His research impact includes 8 citations, 5 publications, and an h-index of 1.

Profiles: Scopus | ORCID

Featured Publications

1. Qiao L., Shao P., Zhao H., Huang Z., An assembly deviation calculation method based on surface deviation modeling for circumferential grinding plane. Proc. Inst. Mech. Eng. Part B: J. Eng. Manuf., 2021.

2. Shao P., Huang Z., Qiao L., A novel assembly knowledge graph construction framework enhanced by large language model. Int. J. Adv. Manuf. Technol., 2025, Accepted.

Dr. Peilin Shao’s work advances intelligent manufacturing by integrating large language models with assembly process knowledge, enabling smarter, data-driven engineering decisions. His vision is to accelerate industry transformation through AI-enabled knowledge engineering that fosters sustainable, high-precision, and globally competitive manufacturing practices.

Shixun Wu | AI and Automation in Architecture | Best Researcher Award

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Dr. Shixun Wu | AI and Automation in Architecture | Best Researcher Award

Vice Professor | Chongqing Jiaotong University | China

Dr. Shixun Wu, Vice Professor at the College of information Science and Engineering and Vice Dean of the Department of Communication Engineering at Chongqing Jiaotong University, is a specialist in wireless communication, wireless localization, and machine learning. With advanced training in applied mathematics and a doctorate in electrical and computer engineering, he has contributed extensively to intelligent transportation systems, cooperative mobile localization, Wi-Fi fingerprinting, secrecy communication, and RFID identification protocols. His work includes impactful publications in leading journals and collaborative projects that advance high precision positioning, reinforcement learning based communication strategies, and secure wireless systems. Dr. Wu has held key academic and leadership roles that support program development, research coordination, and the cultivation of emerging scholars. His professional recognition includes contributions to competitive research initiatives, involvement in editorial and review activities, and active participation in scholarly communities and technical organizations. His record reflects sustained excellence in advancing communication technologies and intelligent networked systems, positioning him as a distinguished candidate for this award. His research impact includes 380 citations, 38 publications, and an h-index of 11.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Zhang H., Xu K., Huang D., He D., Wu S., Xian G., Hybrid decision-making for intelligent high-speed train operation using boundary constraint and pre-evaluation reinforcement learning. IEEE Trans. Intell. Transp. Syst., 2024, 25(11), 17979-17992.
2. Wu S., Wang S., Xu K., Wang H., Hybrid TOA/AOA cooperative mobile localization in 4G cellular networks. IEIE Trans. Smart Process. Comput., 2013, 2(2), 77-85.
3. Wu S., Zeng X., Zhang M., Cumanan K., Waraiet A., Chu Z., Xu K., LCVAE-CNN: Indoor Wi-Fi Fingerprinting CNN positioning method based on LCVAE. IEEE Internet Things J., 2025, Accepted.
4. Zhang M., Ding X., Tang Y., Wu S., Xu K., Star-RIS assisted secrecy communication with deep reinforcement learning. IEEE Trans. Green Commun. Netw., 2024, Accepted.
5. Yang X., Wu B., Wu S., Liu X., Zhao W.G.W., Time slot detection-based M-ary tree anticollision identification protocol for RFID tags in the Internet of Things. Wirel. Commun. Mob. Comput., 2021, Article ID 6638936.

Dr. Shixun Wu’s research advances precise wireless localization, intelligent communication systems, and machine learning-driven network optimization, strengthening the foundations of next-generation connected technologies. His contributions support safer transportation, more reliable indoor positioning, and secure communication frameworks that benefit both industry and society. He envisions scalable intelligent networks that enhance global digital infrastructure and drive innovation across smart mobility and IoT systems.

Suparna Biswas | AI and Automation in Architecture | Best Researcher Award

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Dr. Suparna Biswas | AI and Automation in Architecture | Best Researcher Award

Associate Professor | Guru Nanak Institute of Technology | India

Dr. Suparna Biswas is Associate Professor in the Department of Electronics and Communication Engineering and Controller of Examinations at Guru Nanak Institute of Technology, with expertise in image processing, signal processing, control systems, and machine learning. She earned her PhD in Engineering from IIEST Shibpur after completing her M.Tech in Control Systems at Jadavpur University and B.Tech in Electronics and Communication Engineering at Kalyani Government Engineering College. With extensive academic and administrative experience, she has advanced through faculty roles and taken on leadership responsibilities such as coordinating NAAC and AQAR committees, serving as convener of faculty development programs and national conferences, and securing competitive research funding. Her prolific research record includes more than 60 publications in SCI, Scopus, and WoS indexed journals and conferences, authorship of books, and contributions to patents, with recent works addressing vision transformers, signal analysis, and AI applications in healthcare. She has guided PhD and postgraduate scholars and consistently contributed to advancing academic innovation. Recognized with multiple honors including Best Paper Awards at international conferences, the JIS Samman for patent publications, and the Most Promising Academician award, she also serves as reviewer for reputed SCI and Scopus journals and holds editorial board memberships. A corporate member of the Institution of Engineers (India) and an active member of FOSET, she has also completed certifications in machine learning, artificial intelligence, and data science. Dr. Biswas’s academic and research contributions underscore her leadership in engineering education and her commitment to advancing multidisciplinary innovation. Her Scopus profile reflects 84 citations, 27 publications, and an h-index of 4.

Profiles: Scopus | Google Scholar | ORCID

Featured Publications

1. Biswas S., Designing optimal Vision Transformer architecture using differential evolution for tomato leaf disease classification. Comput. Electron. Agric., 2025, 238, 110824.

2. Chattopadhyaya A., Biswas S., Rakshit S., Jana N.D., Mondal A., Statistical Signal Processing and Machine Learning Based Diagnosis of Arrhythmia. Int. J. Comput. Inf. Syst. Ind. Manag. Appl., 2025, 17, 362–374.