Demo Data from VLDB 2026 / reviewers in the wild / expert
Xinyu Zhang 0020
dblp:58/4582-20 · also Xin-Yu Zhang 0020
· DBLP profile ↗
11ranked-venue papers
3as first author
9since 2021 · last 2025
0000-0002-4986-4649ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 5 · 2 first-author · 5 since 2021Databases, data management, data science and information retrieval · 3 · 1 first-author · 2 since 2021Computer networks · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Image and video processing · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing › motion analysis
human motion analysis |
0.6 | 1 | 2022 | Human motion segmentation based on structure constraint matrix factorization · Sci. China Inf. Sci. 2022 |
Image and video processing › video segmentation
motion segmentation |
0.6 | 1 | 2022 | Human motion segmentation based on structure constraint matrix factorization · Sci. China Inf. Sci. 2022 |
Methods — techniques the papers use, named apart from their topics
structure constraint matrix factorization · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Collaborative optimization of vessel scheduling and tugboat allocation in seaports using a multi-action deep reinforcement learning framework
Xinyu Zhang 0020, Yuankui Li |
Eng. Appl. Artif. Intell. | 2 |
| 2025 | World model-based reinforcement learning for autonomous ship safe collision avoidance
Kangjie Zheng, Xinyu Zhang 0020, Ryan Wen Liu, Jialin Ma, Jinlong Cui |
Eng. Appl. Artif. Intell. | 2 |
| 2025 | Optimization of integrated accurate ride-tide planning and vessel scheduling in multi-functional ports with long channels
Xinyu Zhang 0020, Zaili Yang, Jingyun Wang 0002, Chengbo Wang 0001 |
Expert Syst. Appl. | 1 |
| 2025 | Research on Intelligent Collision Avoidance and Obstacle Avoidance of Unmanned Surface Vehicle in Multitarget Encounter ScenarioabstractWith the rapid development of Internet of Things (IoT) technology, Unmanned Surface Vehicles (USVs), as critical nodes in distributed maritime sensing networks, have seen their autonomous collision avoidance capabilities become central to enabling coordination among multiple devices and real-time decision-making. Based on this, this paper presents an intelligent strategy for collision and obstacle avoidance in USVs during multi-target encounter scenarios. A collision risk model based on the International Regulations for Preventing Collisions at Sea (COLREGs) and common practices of sailors is constructed, with it being used as a constraint for the differential evolution algorithm (DE). The objective function is decomposed geometrically and in terms of states, transforming the evaluation of the entire path into evaluating individual path points. In this way, high-quality path points are fully utilized, and a fitness function is built based on each individual path point. The population initialization operation of the DE algorithm is improved through a chaotic multi-population parallel optimization strategy, with a chaotic matrix being introduced to enhance search traversal. Additionally, a parameter randomization strategy is introduced in mutation and crossover operations to avoid local optima, and each subpopulation is optimized in parallel to obtain the best collision avoidance route. Finally, the simulation experiments results demonstrate that the improved DE algorithm demonstrates superior performance in both collision avoidance efficiency and path optimization, confirming the effectiveness of the approach in complex multi-target encounter scenarios. Zhongming Xiao, Baoyi Hou, Jun Ning, Xinyu Zhang 0020, Zhengjiang Liu |
IEEE Internet Things J. | 4 |
| 2024 | Robust optimization for a class of ship traffic scheduling problem with uncertain arrival and departure times
Xinyu Zhang 0020, Runfo Li, Chengbo Wang 0001, Biao Xue |
Eng. Appl. Artif. Intell. | 1 |
| 2024 | COLERGs-constrained safe reinforcement learning for realising MASS's risk-informed collision avoidance decision making
Chengbo Wang 0001, Xinyu Zhang 0020, Hongbo Gao 0001, Musa Bashir, Huanhuan Li 0001, Zaili Yang |
Knowl. Based Syst. | 2 |
| 2023 | Disruption management-based coordinated scheduling for vessels and ship loaders in bulk ports
Jingyun Wang 0002, Xinyu Zhang 0020, Zaili Yang, Nyamatari Anselem Tengecha |
Adv. Eng. Informatics | 2 |
| 2022 | Collaborative optimization for loading operation planning and vessel traffic scheduling in dry bulk ports
Xinyu Zhang 0020, Zaili Yang, Xinjian Wang |
Adv. Eng. Informatics | 1 |
| 2022 | Human motion segmentation based on structure constraint matrix factorization
Hongbo Gao 0001, Juping Zhu, Zhen Kan, Xinyu Zhang 0020 |
Sci. China Inf. Sci. | 5 |
| 2019 | Intelligent multi-task allocation and planning for multiple unmanned surface vehicles (USVs) using self-organising maps and fast marching method
Yuanchang Liu, Rui Song 0005, Richard W. G. Bucknall, Xinyu Zhang 0020 |
Inf. Sci. | 4 |
| 2009 | Sea Surface Simulation in Large Coastal Region for Maritime SimulatorsabstractA novel method for simulating large-scale, nearshore sea surface is presented. The whole simulating process can be divided into two phases: pre-computing phase and real-time computing phase. In pre-computing phase, wave parameter distribution of a simulation area is worked out using the SWAN (Simulating WAves Nearshore) model on a coarse grid. In real-time computing phase, a small height field surrounding the viewpoint is generated using the Fast Fourier Transformation (FFT) based method every frame. The wave parameters used in the FFT-based method are dynamically changed according to viewpoint’s projective position on the coarse grid. Then, the height field is saved as a vertex texture, which can be tiled in horizontal directions seamlessly. At last, the vertex texture is sampled by a sector sea surface, which is viewpoint-dependent and has Level Of Detail (LOD) effect. Several shading trips are used to generate optical effects of sea surface, such as reflection, refraction etc. Experimental results show this method can be applied to simulating large-scale sea surface in real-time with realistic effect. It is especially suitable for the application in maritime simulators. Yongjin Li, Yicheng Jin, Helong Shen, Xinyu Zhang 0020 |
ICIG | 5 |