Deep learning has expanded its application to many real-world problems, but at the same time, it is found to be very vulnerable to some simple adversarial attacks. Though various defense mechanisms have been proposed to improve robustness of deep learning software, many of them are ineffective against adaptive attacks. Thus, it is an important and arduous task to study the attack and defense metho...

Prof. Gao Shenghua’s research group from the Visual & Data Intelligence Center focuses on using deep learning and sparse/low-rank models to explore the low-dimensional structure in huge high-dimensional data, and uses it to solve practical computer vision problems, including target recognition, action recognition, image or video generation, 3D reconstruction, etc. Recently the group published...

Assistant Professor Wang Xiong’s research group from Smart Medical Information Research Center at SIST is focusing on electromagnetic acoustic hybrid imaging, focused microwave and ultrasound hyperthermia for cancer, and research on electromagnetic wave and acoustic wave metasurfaces. Recently, the group has made a series of advances in the field of electromagnetic acoustic imaging. 1. Precl...

Prof. Wu Tao’s research group at SIST is committed to developing Micro Electro Mechanical Systems (MEMS) devices using advanced sensing materials and micro/nano technology. Their research interests mainly include the coupling mechanism and sensing application of multiferroic materials, piezoelectric acoustic micro/nano devices and IC  interface circuits, and magnetoelectric sensors. Rec...

Recently, Assistant Professor Zhou Yong’s group in the SIST has made significant progress in the fields of IoT networks and fog-computing networks. Their achievements were published separately in two journals: (1) in IEEE Internet of Things Journal in an article entitled “Wireless-Powered Over-the-Air Computation in Intelligent Reflecting Surface-Aided IoT Networks”, and (2) in I...

 Recently, two studies from SIST Professor Ha Yajun’s group in the Reconfigurable and Intelligent Computing Lab were accepted by the ACM/IEEE Design Automation Conference (DAC). The studies were entitled "TAIT: One-Shot Full-Integer Lightweight DNN Quantization via Tunable Activation Imbalance Transfer", and "Bitwidth-Optimized Energy-Efficient FFT Design via Scaling Informati...

Recently, SIST Professor Zhao Dengji’s paper entitled “Mechanism Design Powered by Social Interactions” was accepted by the 20th International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-2021), Blue Sky Ideas Track. Unlike other technical paper reviewing processes, the emphasis of this track is on visionary ideas, long-term challenges, new research opportunities and con...

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 device...

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 ...

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...

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...

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 resea...

Professor Shao Ziyu’s research group of SIST made an important advance in intelligent networking, addressing the following challenge: “How to systematically design effective predictive scheduling algorithms for intelligent networks?” Their results, of high importance to recent software-defined networking (SDN) systems, were published in an article entitled “Predictive Switch-Controller Associa...

In the past two years, two novel model reduction methods for high-dimensional stochastic computational models were proposed by the Visual and Data Intelligence Center (VDI Center) of SIST. The first method, proposed in the article entitled “Rank adaptive tensor recovery-based model reduction for partial differential equations with high-dimensional random inputs”, provided a new systematic comput...