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Experience: Prof. Jude Hemanth is working as a Professor in the Department of ECE, Karunya University, Coimbatore, India. He also holds the position of “Visiting Professor” in the Faculty of Electrical Engineering and Information Technology, at the University of Oradea, Romania. He has authored more than 150 research papers in reputed SCIE-indexed International Journals and Scopus-indexed International Conferences. His Cumulative Impact Factor is more than 250. He has published 37 edited books with reputed publishers such as Elsevier, Springer, and IET. He holds professional membership with IEEE Technical Committee on Neural Networks (IEEE Computational Intelligence Society) and IEEE Technical Committee on Soft Computing (IEEE Systems, Man and Cybernetics Society), and ACM. | |
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Experience: Nasir Saeed, Senior Member of IEEE, received his Bachelor of Telecommunication degree from the University of Engineering and Technology, Peshawar, Pakistan, in 2009 and received a master's degree in satellite navigation from Polito di Torino, Italy, in 2012. He received his Ph.D. degree in electronics and communication engineering from Hanyang University, Seoul, South Korea in 2015. He was an Assistant Professor at the Department of Electrical Engineering, Gandhara Institute of Science and IT, Peshawar, Pakistan from August 2015 to September 2016. Dr. Saeed worked as an assistant professor at IQRA National University, Peshawar, Pakistan from October 2017 to July 2017. He is currently an associate professor of electrical engineering at northern border university, Arar, KSA. His current areas of interest include cognitive radio networks, underwater and underground wireless communications, satellite communications, flying networks, dimensionality reduction, and localization. | |
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Title: Research and Exploration of Federated Learning System Abstract: With the popularity of machine learning in many applications, data privacy has become a severe issue when machine learning is applied in the real world. Federated learning (FL), an emerging paradigm in machine learning, aims to train a centralized model while distributing training data among a large number of clients in order to avoid data privacy leaking, which has attracted great attention recently. In this talk, I will introduce two of our recently published works, focusing on real-world application (IEEE Network) and system security (ACM SoCC 2021) respectively. Besides, some of our future work and latest results will also be introduced in this talk. Experience: Dr. Ma Ruhui, Associate Professor, doctoral supervisor, Department of Computer Science, Shanghai Jiao Tong University, member of CCF, member of IEEE, is the provincial and Ministry co-built National Key Laboratory Breeding Base, Shanghai Key Laboratory of Scalable Computing and Systems, and Deputy Director of Shanghai Cloud Computing Joint Laboratory. His main research interests are artificial intelligence, computer vision, intelligent manufacturing, medical and industrial intersection, cloud computing system, cloud security, intelligent system, etc. He has won 1 first prize in Shanghai Technology Invention and 1 third prize in Jiangsu Science and Technology Progress. He has presided over 15 projects, including 2 National Natural Science Foundation projects and 1 Shanghai Special key project. In recent years, he has published more than 50 SCI/EI index papers in top international conferences and top international journals in the field of computer science. Including AAAI, ICCV, ACM MM, TPDS, TDSC, TBD, TCC, TETC, JCST, JSA, ICSM, ICPP, etc., 27 authorized invention patents (including 4 U.S. patents). I guided the | |
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Title: Bio-Inspired Sensing Principles for Novel Artificial Electronic Skins Abstract: Artificial electronic skins that mimic the sensory functionalities of natural skin are critical and highly desirable for the emerging fields of prosthetics and robotics. Complex sensing devices/systems have been explored to construct artificial electronic skins by spatially integrating multiple sensing elements or elaborately merging multiple sensing principles. However, the sophisticated fabrication, complex operation, and high power consumption pose challenges for their practical and widespread applications. Motivated by the limitations of the currently existing electronic skins and inspired by the sensing behaviors of natural human skin, in the past two years, we successfully developed a number of novel sensing mechanisms and created a whole set of innovative electronic skins with distinctive characteristics that cannot be achieved via state-of-the-art technologies. Furthermore, we demonstrated that diverse environmental stimuli in our daily life (e.g., temperature variation, static and/or dynamic pressure, mechanical vibration, etc.) can be detected and recorded in real-time with our electronic skins. These highly effective and energy-efficient electronic skins provide a much-improved human-machine interfacing medium and open up great opportunities for creating a new range of humanoid robotics, skin prosthetics, wearable healthcare devices, bioelectronics, and autonomous smart systems. Experience: Dr. Xiaodong Wu is an Associate Professor in the Department of Mechanical Engineering (ME) at Sichuan University. He obtained his bachelor's degree and doctor's degree from Sichuan University in Jun. 2014 and Dec. 2019. From Oct. 2017 to Jun. 2021, he worked as a Visiting Research Scholar in the Department of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. His research interests and fields focus on 1) flexible electronic materials, 2) flexible sensing technologies, 3) artificial electronic skin, 4) wearable healthcare and human-machine interfacing, and 5) bioinspired or biomimetic devices and systems. So far, he has published over 30 SCI papers in academic journals, including Science Advances, Advanced Materials, Advanced Functional Materials, Advanced Electronic Materials, ACS Applied Materials & Interfaces, etc., with more than 2000 citations (Google Scholar) and H-Index of 20. He also served as a reviewer for many academic journals, such as Science Advances, Advanced Functional Materials, ACS Applied Materials & Interfaces, and so on. Research Area: Flexible electronics, wearable sensors, healthcare devices |
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2023 3rd International Conference on Sensors and Information Technology(ICSI 2023) http://ic-si.net/