Prof. Sun-Yuan Kung, Princeton University, USA (Life Fellow of IEEE)
S.Y. Kung, Life Fellow of IEEE, is a Professor of Electrical and Computer Engineering at the Princeton University. His research areas include VLSI array processors, AI algorithms, machine learning, deep learning networks, neural architectural search, and compressive privacy. He was a founding member of several Technical Committees of the IEEE Signal Processing Society. He was elected to Fellow of IEEE in 1988 and served as a Member of the Board of Governors of the IEEE Signal Processing Society (1989-1991). He was a recipient of IEEE Signal Processing Society's Technical Achievement Award for the contributions on "parallel processing and neural network algorithms for signal processing" (1992); a Distinguished Lecturer of IEEE Signal Processing Society (1994); a recipient of IEEE Signal Processing Society's Best Paper Award (1996); IEEE Third Millennium Medal (2000), and CIE-GNYC’s Asian American Engineer of the Year Award (2023). Since 1990, he has been the Editor-In-Chief of the Journal of VLSI Signal Processing Systems. He has authored and co-authored more than 500 technical publications and numerous textbooks including ``VLSI Array Processors'', Prentice-Hall (1988); ``Digital Neural Networks'', Prentice-Hall (1994) ; ``Principal Component Neural Networks'', John-Wiley (1996); ``Biometric Authentication: A Machine Learning Approach'', Prentice-Hall (2004); and ``Kernel Methods and Machine Learning”, Cambridge University Press (2014).
Prof. Xiaohu Ge, Huazhong University of Science and Technology, China (IET Fellow)
Xiaohu Ge received the Ph.D.degree in communication and information engineeringfrom the Huazhong University of Scienceand Technology (HUST), China, in 2003. He has been worked with HUST, since November2005. Prior to that, he worked as a Researcher at Ajou University, South Korea, and the Politecnico Di Torino,Italy, from January 2004 to October 2005. He is currently a full Professorwith the School of Electronic Information and Communications,HUST. He is also an Adjunct Professor with the Faculty of Engineeringand Information Technology, University of Technology Sydney (UTS), Australia. He has published more than 200 SCI academic papers, with more than 10,000 citations from Google Scholar, including several best papers of the IEEE Communications Society. He is the Chinese representative of the International Federation for Information Processing (IFIP), the Fellow of the IET, the editor of IEEE Wireless Communications, IEEE Transactions on Vehicular Technology, etc.. He serves as the symposium chair of more than 30 international conferences such as IEEE ICC and IEEE GlobeCom.
Prof. Tao Lei, Shaanxi University of Science and Technology, China (IEEE Senior Member)
Title: Lightweight Networks for Abdominal Image Segmentation
Abstract: With the rapid development of deep learning techniques, smart medicine has become a hot spot and attract the attention of many scholars. At present, a large number of state-of-the-art deep network modes have been proposed and used for abdominal medical image segmentation. Although these networks improve accuracy of target segmentation in abdominal images, they still suffer from some challenges. Especially, popular medical image segmentation networks require a mountain of parameters, high memory usage, high computational costs, which leads to a difficulty of deploying these networks in low-resource devices. To address the issue, this report mainly introduces the design methods of lightweight networks, including our works on the design of lightweight networks for abdominal image segmentation. These lightweight networks not only effectively reduce the number of parameters and computational costs, but also improve the organ segmentation accuracy for abdominal images.
Tao Lei is currently a Professor with the School of electric Information and Artificial Intelligence, Shaanxi University of Science and Technology. He is a senior member of IEEE, CCF, and CSIG. He was selected into the Shaanxi Province High-level Talent Program in 2017. He has served at more than ten international conferences as co-chair, co-publication chair, and co-award chair. His current research interests include image processing, pattern recognition, and machine learning. He has authored and co-authored 80+ research papers including IEEE TIP, TFS, TGRS, TCDS, TRPMS, ICASSP, ICME, ICIP, and FG, where 3 papers are selected as ESI highly cited papers. The google scholar citation is 2000+.
As a project leader, he hosts the National Natural Science Foundation of China (four projects), the Outstanding Youth Fund of Shaanxi Province, and the Key Research and Development Program of Shaanxi.
Title: Comming soon...
Abstract: Comming soon...
Dr. Shruti Jain is an Associate Dean (Innovation) and Professor in the Department of Electronics and Communication Engineering at the Jaypee University of Information Technology, Waknaghat, H.P, India. She has received her Doctor of Science (D.Sc.) in Electronics and Communication Engineering. She has teaching experience of around 18 years. She has filed eight patents, of which one has been granted and five are published. She has published more than 24 book chapters, and 125 research papers in reputed indexed journals and in international conferences. She has also published 14 books. She has completed two government-sponsored projects. She has guided 07 Ph.D. students and now has 04 registered students. She has also guided 11 M Tech scholars and more than 97 B Tech undergrads. She has organized 09 conferences of IEEE and Springer as Conference General Chair. Her research interests are Image and Signal Processing, Soft Computing, Internet-of-Things, Pattern Recognition, Bio-inspired Computing, and Computer-Aided Design of FPGA and VLSI circuits. She is a senior member of IEEE, Executive member of IEEE Delhi Section, life member and Executive member of Biomedical Engineering Society of India, and a member of IAENG. She is a member of the Editorial Board of many reputed journals. She is also a reviewer of many journals and a member of TPC of different conferences. She was awarded by Nation Builder Award in 2018-19 and enlisted in 2% scientist of world rankings of 2021 published by Elsevier, data compiled by Stanford University.
Prof. Xiaofeng Ding, Huazhong University of Science and Technology, China
Title: Privacy Preserving Problems in Big Data Publishing
Abstract: The need to efficiently store and query large scale datasets is evident in the growing number of data-intensive applications, particularly to maximize the mining of intelligence from these data (e.g., to inform decision making). However, directly releasing dataset for analysis may leak sensitive information of an individual even if the data is anonymized, as demonstrated by the re-identification attacks on the DBpedia datasets. In this talk, we introduce a novel k-decomposition algorithm and define a new information loss matrix designed for utility measurement in massively large graph datasets. We also propose a novel privacy preserving framework that can be seamlessly integrated with graph storage, anonymization, query processing, and analysis.
I am currently a Professor and Pd.D Supervisor in the School of Computer Science and Technology at Huazhong University of Science and Technology (HUST). I received my Ph.D degree in Computer Science from HUST in 2009. I also worked as Research Fellow at the National University of Singapore and the University of South Australia during 2010-2013. My research interests mainly include data privacy and query processing, data encryption, graph databases and deep learning. Most of my works are published in reputable jounrals or conferences like IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Dependable and Secure Computing, International Conference on Very Large Data Bases (VLDB), IEEE International Conference on Data Engineering (ICDE), ACM Conference on Information and Knowledge Management (CIKM) and etc.