• SIST researchers made progress in IoT and fog-computing networks
    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...
    2021-03-24
  •  Important progress made in lightweight neural network and FFT
     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...
    2021-03-12
  • SIST Professor Zhao Dengji proposes novel discussions on mechanism design powered by social interactions
    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...
    2021-03-04
  • 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 device...
    2021-02-11
  • 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 ...
    2021-02-05
  • 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...
    2021-01-28
  •  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...
    2021-01-11
  • 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 resea...
    2021-01-08
  • Research group made an important advance in the scheduling mechanism of intelligent networks
    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...
    2020-12-22
  • SIST Makes Progress in Model Reduction for High-Dimensional Computational Models
    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...
    2020-12-08
  • SIST Published Multiple Papers at ECCV and ACM MM, 2020
    Recently, the Vision and Data Intelligence Center (VDI) of SIST published 4 papers at the European Conference on Computer Vision (ECCV, 2020) and 2 papers at the ACM International Conference on Multimedia (ACM MM, 2020). ECCV is one of the top three computer vision conferences, focusing on cutting-edge research in computer vision and ACM MM is also a class A conference recommended by the China Com...
    2020-11-05
  • SIST Researchers Make Significant Progress in the Verification of Side-Channel Resistance of Higher-Order Cryptographic Programs
    Professor Song Fu’s research group from the School of Information Science and Technology (SIST) has recently published an article entitled “A Hybrid Approach to Formal Verification of Higher-Order Masked Arithmetic Programs”. This article was published in ACM Transactions on Software Engineering Methodology (ACM TOSEM), one of the two most prestigious software engineering journal...
    2020-11-03
  • Communication-Efficient Edge AI: Algorithms and Systems
    Prof. Shi Yuanming’s research group and collaborators from HKUST and HKPolyU have surveyed the key techniques for improving the communication efficiency of performing artificial intelligence (AI) training and inference tasks at network edges, a.k.a., edge AI.  Edge AI is envisioned to promote the paradigm shift of futuristic 6G networks from “connected things” to “connected inte...
    2020-09-01
  • SIST Achieves Fruitful Results in AI Research Since 2020
    Since the beginning of 2020, a total of 29 academic papers from the Visual & Data Intelligence Center of SIST have been accepted by top-tier international conferences, covering research hotspots including computer vision, machine learning, natural language processing, computer graphics, and multi-agent systems. Those research outcomes address a variety of real-world problems in digital enterta...
    2020-06-05