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Celebrating the 70th Anniversary of Beijing University of Posts and...
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Celebrating the 70th Anniversary of Beijing University of Posts and Telecommunications—Computer Science and Engineering

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 15 October 2026 | Viewed by 917

Special Issue Editors

Prof. Dr. Shaozhang Niu

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Guest Editor
School of Computer Science (National Pilot Software Engineering School), Beijing University of Posts and Telecommunications, Beijing 100876, China
Interests: multimedia security; image recognition
Special Issues, Collections and Topics in MDPI journals
Dr. Jiwei Zhang

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Guest Editor
School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China
Interests: computer vision; information security
Special Issues, Collections and Topics in MDPI journals
Dr. Feifei Kou

E-Mail Website
Guest Editor
School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China
Interests: artificial intelligence; big data mining; semantic learning; search and recommendation
Special Issues, Collections and Topics in MDPI journals
Dr. Yongmei Tan

E-Mail Website
Guest Editor
School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China
Interests: AI; NLP
Dr. Renzhi Yuan

E-Mail Website
Guest Editor
School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
Interests: space communication; satellite optical communication; ultraviolet optical communication; underwater optical communication; optical receivers; optimal quantum detection; quantum detection in classical and quantum optical communications
Special Issues, Collections and Topics in MDPI journals
Dr. Chunping Li

E-Mail Website
Guest Editor
School of Software, Tsinghua University, Beijing 100084, China
Interests: artificial intelligence; data analysis and data mining; machine learning and automated reasoning

Special Issue Information

Dear Colleagues,

Founded in 1955, Beijing University of Posts and Telecommunications (BUPT) has emerged as one of China's leading institutions, renowned for its contributions to the fields of telecommunications, computer science, and engineering. As a cornerstone in national technological development, BUPT was among the first to be included in the national “211 Project” and the "985 Project Advantage Discipline Innovation Platform". Furthermore, it has consistently been recognized as a top-tier university in the fields of computer science and engineering.

Over the past 70 years, BUPT has made groundbreaking advancements in computer science, ranging from theoretical foundations in algorithms and software engineering to innovations in network infrastructure, intelligent systems, and cybersecurity. To commemorate the 70th anniversary of Beijing University of Posts and Telecommunications, this Special Issue aims to highlight the latest research, cross-disciplinary developments, and emerging technologies in the field of computer science and engineering. We welcome contributions that cover a wide array of theoretical innovations, practical breakthroughs, system-level designs, and comprehensive reviews.

The scope of this Special Issue includes, but is not limited to, the following topics:

  • Computer architecture and systems;
  • Distributed systems and cloud computing;
  • Network protocols and communication systems;
  • Machine learning and deep learning;
  • Artificial intelligence in engineering applications;
  • Data science and big data technologies;
  • Cybersecurity and privacy protection;
  • Blockchain and decentralized computing;
  • Internet of Things (IoT) and intelligent systems;
  • High-performance computing and edge computing;
  • Human–computer interaction and user interface design;
  • Software engineering and development practices;
  • Embedded systems and system-on-chip technologies;
  • Digital signal processing and multimedia systems;
  • Computational intelligence and optimization.

We invite submissions that explore the latest advancements in computer science and engineering, contributing to the growing body of knowledge and celebrating BUPT’s 70 years of excellence and innovation in the field.

Prof. Dr. Shaozhang Niu
Dr. Jiwei Zhang
Dr. Feifei Kou
Dr. Yongmei Tan
Dr. Renzhi Yuan
Dr. Chunping Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • computer architecture
  • distributed systems
  • cloud computing
  • network protocols
  • machine learning
  • deep learning
  • artificial intelligence
  • data science
  • big data
  • cybersecurity
  • blockchain
  • IoT (Internet of Things)
  • high-performance computing
  • edge computing
  • software engineering

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

25 pages, 3879 KB  
Article
Robust Occluded Object Detection in Multimodal Autonomous Driving: A Fusion-Aware Learning Framework
by Zhengqing Li and Baljit Singh
Electronics 2026, 15(1), 245; https://doi.org/10.3390/electronics15010245 - 5 Jan 2026
Viewed by 282
Abstract
Reliable occluded object detection remains a persistent core challenge for autonomous driving perception systems, particularly in complex urban scenarios where targets are predominantly partially or fully obscured by static obstacles or dynamic agents. Conventional single-modality detectors often fail to capture adequate discriminative cues [...] Read more.
Reliable occluded object detection remains a persistent core challenge for autonomous driving perception systems, particularly in complex urban scenarios where targets are predominantly partially or fully obscured by static obstacles or dynamic agents. Conventional single-modality detectors often fail to capture adequate discriminative cues for robust recognition, while existing multimodal fusion strategies typically lack explicit occlusion modeling and effective feature completion mechanisms, ultimately degrading performance in safety-critical operating conditions. To address these limitations, we propose a novel Fusion-Aware Occlusion Detection (FAOD) framework that integrates explicit visibility reasoning with implicit cross-modal feature reconstruction. Specifically, FAOD leverages synchronized red–green–blue (RGB), light detection and ranging (LiDAR), and optional radar/infrared inputs, employs a visibility-aware attention mechanism to infer target occlusion states, and embeds a cross-modality completion module to reconstruct missing object features via complementary non-occluded modal information; it further incorporates an occlusion-aware data augmentation and annotation strategy to enhance model generalization across diverse occlusion patterns. Extensive evaluations on four benchmark datasets demonstrate that FAOD achieves state-of-the-art performance, including a +8.75% occlusion-level mean average precision (OL-mAP) improvement over existing methods on heavily occluded objects O=2 in the nuScenes dataset, while maintaining real-time efficiency. These findings confirm FAOD’s potential to advance reliable multimodal perception for next-generation autonomous driving systems in safety-critical environments. Full article
(This article belongs to the Special Issue Celebrating the 70th Anniversary of Beijing University of Posts and Telecommunications—Computer Science and Engineering)
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22 pages, 3408 KB  
Article
A High-Performance Branch Control Mechanism for GPGPU Based on RISC-V Architecture
by Yao Cheng, Yi Man and Xinbing Zhou
Electronics 2026, 15(1), 125; https://doi.org/10.3390/electronics15010125 - 26 Dec 2025
Viewed by 274
Abstract
General-Purpose Graphics Processing Units (GPGPUs) rely on warp scheduling and control flow management to organize parallel thread execution, making efficient control flow mechanisms essential for modern GPGPU design. Currently, the mainstream RISC-V GPGPU Vortex adopts the Single Instruction Multiple Threads (SIMT) stack control [...] Read more.
General-Purpose Graphics Processing Units (GPGPUs) rely on warp scheduling and control flow management to organize parallel thread execution, making efficient control flow mechanisms essential for modern GPGPU design. Currently, the mainstream RISC-V GPGPU Vortex adopts the Single Instruction Multiple Threads (SIMT) stack control mechanism. This approach introduces high complexity and performance overhead, becoming a major limitation for further improving control efficiency. To address this issue, this paper proposes a thread-mask-based branch control mechanism for the RISC-V architecture. The mechanism introduces explicit mask primitives at the Instruction Set Architecture (ISA) level and directly manages the active status of threads within a warp through logical operations, enabling branch execution without jumps and thus reducing the overhead of the original control flow mechanism. Unlike traditional thread mask mechanisms in GPUs, our design centers on RISC-V and realizes co-optimization at both the ISA and microarchitecture levels. The mechanism was modeled and validated on Vortex SimX. Experimental results show that, compared with the Vortex SIMT stack mechanism, the proposed approach maintains correct control semantics while reducing branch execution cycles by an average of 31% and up to 40%, providing a new approach for RISC-V GPGPU control flow optimization. Full article
(This article belongs to the Special Issue Celebrating the 70th Anniversary of Beijing University of Posts and Telecommunications—Computer Science and Engineering)
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