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SIST researchers propose novel techniques for defect imaging
Electromagnetic imaging technology with array sensors is used extensively to detect defects in industries where structural integrity and safety are critical, such as aerospace, high-speed railway, pressure vessels, energy facilities and precision manufacturing. SIST Assistant Professor Ye Chaofeng and his research group in the Precision Sensing and Intelligent Testing lab (PSIT) have designed two novel probes and testing systems for the imaging of defects. Both achievements were recently publish
2021-02-08
News
Important progress made by SIST in the field of computer data storage
Data storage is one of the fundamental systems in computer architecture. There are a variety of data structures to implement data indexing at a high speed in a computer system. B+-Tree, a data structure designed for disks and single-core processors proposed in the 1970s, is currently still indispensable in many databases and file systems. One of the promising data storage devices to transplant and deploy B+-Tree is non-volatile memory (NVM), which has attracted wide attention in recent years, as
2021-02-04
News
Wang Hao’s research group at SIST propose an efficient algorithm for deep neural network model compression
As one of the most popular fields in artificial intelligence, deep neural network (DNN) is a promising approach to realize many AI tasks such as speech recognition, image classification and autonomous driving. At the same time, with advances in the technology of edge computing and internet of things, it is necessary to deploy pretrained DNN models at the edge of networks and on the terminal devices. However, these DNN models usually contain a massive number of parameters, proving a huge challeng
2021-02-01
News
Multiple important papers by SIST published in the mainstream journals in the area of power and energy
The Center for Intelligent Power and Energy Systems (CiPES) of SIST is a subdivided research group focusing mainly on the study of electric power and energy. It studies topics including power generation, transmission/distribution, storage and utilization, and aims to propose reliable, efficient, low-carbon and intelligent power solutions for the sustainable development of domestic energy. Recently, CiPES published three papers addressing topics in Internet of Things (IoT) energy harvesting, powe
2021-01-11
News
CAS Academician Jiang Hualiang gave a seminar at SIST, ShanghaiTech University on drug discovery and development based on artificial intelligence
On December 23, 2020, School of Information Science and Technology (SIST) of ShanghaiTech University invited Professor Jiang Hualiang, the Former Director of the Shanghai Institute of Materia Medica, Chinese Academy of Sciences (CAS), Distinguished Adjunct Professor of the Shanghai Institute for Advanced Immunochemical Studies (SIAIS) of ShanghaiTech, and the Academician of the CAS, to give a seminar entitled Drug Discovery and Development based on Artificial Intelligence. The seminar was hosted
2021-01-08
News
The METAL group of SIST proposed a new kinetic energy harvesting circuit design
Ambient energy harvesting technology provides the most promising energy solution for future battery-less, ubiquitous, and maintenance-free Internet of Things (IoT) devices. Among all types of ambient energy sources, mechanical kinetic energy can be better associated with human and machine movements, as there is plenty of motion information combined with the mechanical movements of parts. The research on kinetic energy harvesting and its applications in future battery-less IoT devices has attract
2021-01-08
News
Prof. Laurent Kneip’s Group Proposes a Novel Algorithm in Globally-optimal Event Camera Motion Estimation
ShanghaiTech Automation and Robotics Center(STAR Center) of SIST under the direction of Professor Laurent Kneip recently proposed a novel, globally optimal algorithm that can be applied to a variety of motion estimation problems of event cameras and verified by experiments. The algorithm is based on the branch and bound optimization technique, and the accuracy of the algorithm is one order of magnitude higher than that of local optimization methods. With the title of globally optimal event camer
2021-01-01
News
Prof. Tu Kewei’s Research Group Make Progress in Natural Language Processing
Recently, Dr. Kewei Tus research group at the Vision and Data Intelligence Center of the School of Information Science and Technology, ShanghaiTech University published three papers at the main conference of EMNLP 2020, as well as four papers at the extended paper collection EMNLP Findings. Empirical Methods in Natural Language Processing (EMNLP) is one of the top three conferences (ACL, EMNLP and NAACL) in the field of natural language processing. It enjoys a high international reputation and i
2020-12-31
News
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SIST researchers propose novel techniques for defect imaging
Electromagnetic imaging technology with array sensors is used extensively to detect defects in industries where structural integrity and safety are critical, such as aerospace, high-speed railway, pressure vessels, energy facilities and precision manufacturing. SIST Assistant Professor Ye Chaofeng and his research group in the Precision Sensing and Intelligent Testing lab (PSIT) have designed two novel probes and testing systems for the imaging of defects. Both achievements were recently publish
2021-02-08
News
Important progress made by SIST in the field of computer data storage
Data storage is one of the fundamental systems in computer architecture. There are a variety of data structures to implement data indexing at a high speed in a computer system. B+-Tree, a data structure designed for disks and single-core processors proposed in the 1970s, is currently still indispensable in many databases and file systems. One of the promising data storage devices to transplant and deploy B+-Tree is non-volatile memory (NVM), which has attracted wide attention in recent years, as
2021-02-04
News
Wang Hao’s research group at SIST propose an efficient algorithm for deep neural network model compression
As one of the most popular fields in artificial intelligence, deep neural network (DNN) is a promising approach to realize many AI tasks such as speech recognition, image classification and autonomous driving. At the same time, with advances in the technology of edge computing and internet of things, it is necessary to deploy pretrained DNN models at the edge of networks and on the terminal devices. However, these DNN models usually contain a massive number of parameters, proving a huge challeng
2021-02-01
News
Multiple important papers by SIST published in the mainstream journals in the area of power and energy
The Center for Intelligent Power and Energy Systems (CiPES) of SIST is a subdivided research group focusing mainly on the study of electric power and energy. It studies topics including power generation, transmission/distribution, storage and utilization, and aims to propose reliable, efficient, low-carbon and intelligent power solutions for the sustainable development of domestic energy. Recently, CiPES published three papers addressing topics in Internet of Things (IoT) energy harvesting, powe
2021-01-11
News
CAS Academician Jiang Hualiang gave a seminar at SIST, ShanghaiTech University on drug discovery and development based on artificial intelligence
On December 23, 2020, School of Information Science and Technology (SIST) of ShanghaiTech University invited Professor Jiang Hualiang, the Former Director of the Shanghai Institute of Materia Medica, Chinese Academy of Sciences (CAS), Distinguished Adjunct Professor of the Shanghai Institute for Advanced Immunochemical Studies (SIAIS) of ShanghaiTech, and the Academician of the CAS, to give a seminar entitled Drug Discovery and Development based on Artificial Intelligence. The seminar was hosted
2021-01-08
News
The METAL group of SIST proposed a new kinetic energy harvesting circuit design
Ambient energy harvesting technology provides the most promising energy solution for future battery-less, ubiquitous, and maintenance-free Internet of Things (IoT) devices. Among all types of ambient energy sources, mechanical kinetic energy can be better associated with human and machine movements, as there is plenty of motion information combined with the mechanical movements of parts. The research on kinetic energy harvesting and its applications in future battery-less IoT devices has attract
2021-01-08
News
Prof. Laurent Kneip’s Group Proposes a Novel Algorithm in Globally-optimal Event Camera Motion Estimation
ShanghaiTech Automation and Robotics Center(STAR Center) of SIST under the direction of Professor Laurent Kneip recently proposed a novel, globally optimal algorithm that can be applied to a variety of motion estimation problems of event cameras and verified by experiments. The algorithm is based on the branch and bound optimization technique, and the accuracy of the algorithm is one order of magnitude higher than that of local optimization methods. With the title of globally optimal event camer
2021-01-01
News
Prof. Tu Kewei’s Research Group Make Progress in Natural Language Processing
Recently, Dr. Kewei Tus research group at the Vision and Data Intelligence Center of the School of Information Science and Technology, ShanghaiTech University published three papers at the main conference of EMNLP 2020, as well as four papers at the extended paper collection EMNLP Findings. Empirical Methods in Natural Language Processing (EMNLP) is one of the top three conferences (ACL, EMNLP and NAACL) in the field of natural language processing. It enjoys a high international reputation and i
2020-12-31
News
per page
8
records
total
214
records
firstpage
<<previouspage
nextpage>>
endpage
PageNumber
7
/
27
jumpto
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