▷Travel Information
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▷Keynote Speakers
Prof. Zhihan Lyu, Qingdao University
Zhihan Lyu is a distinguished professor at Qingdao University. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE) and a fellow of the British Computer Society. He has previously served as a research and development engineer at the French National Center for Scientific Research and as a Marie Curie scholar of the European Union. He has published over 270 high-quality papers in the fields of virtual reality, Internet of Things (IoT), and big data. This includes more than 160 papers in SCI-indexed journals, of which over 80 are published in journals listed in the first and second zones of the Chinese Academy of Sciences. Additionally, he has published a total of 44 papers in top journals such as IEEE/ACM Transactions. Lv Zhihan has led one project funded by the National Natural Science Foundation of China Youth Fund and one project funded by the Shandong Provincial Natural Science Foundation Youth Fund. He also serves as an editorial board member and guest editor for prestigious journals such as Plos One, IEEE Access, IET Image Processing, and Neurocomputing.
Dr. Milaan Parmar, Jilin University of Finance and Economics
Milaan Parmar is a lecturer at Jilin University of Finance and Economics. He has over 5 years of teaching experience in the higher education industry. He specializes in data mining, big data development and applications, and clustering algorithms in the R, Python, and MATLAB platforms. His research interests include pattern recognition, machine learning, and data analysis. He has published and collaborated on more than 10 articles in computer science journals, possessing relevant expertise in machine learning. His research focuses on developing functional deep learning models for image processing using neural network frameworks. The modeling work aims to evaluate combinations of different deep learning models for improving image reconstruction. These deep learning models will contribute to image understanding research, thereby advancing disease diagnosis through MRI scans.

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