Demo Data from EDBT 2026 / reviewers in the wild / expert
Yao Zheng 0003
dblp:66/3310-3
· DBLP profile ↗
16ranked-venue papers
0as first author
6since 2021 · last 2026
0000-0003-2126-2897ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 6 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 4 · 2 since 2021Computer networks · 2 · 1 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021Databases, data management, data science and information retrieval · 1Human-computer interaction and ubiquitous 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
2 papers |
Geometric modeling and processing · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
High-performance computing · 67% Performance modeling and evaluation · 33% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational science and engineering · 100% |
Topics — the 6 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Geometric modeling and processing
mesh generation |
1.3 | 2 | 2024 | Advancing Front Mesh Generation on Dirty Composite Surfaces · Comput. Aided Des. 2024 On the Efficiency of the Advancing-Front Surface Mesh Generation Algorithm · Comput. Aided Des. 2022 |
Geometric modeling and processing
fast marching method |
0.8 | 1 | 2024 | Advancing Front Mesh Generation on Dirty Composite Surfaces · Comput. Aided Des. 2024 |
Performance modeling and evaluation › parallel performance evaluation
multicore scalability |
0.7 | 1 | 2023 | Toward Exascale Computation for Turbomachinery Flows · SC 2023 |
High-performance computing
performance optimization at scale |
0.7 | 1 | 2023 | Toward Exascale Computation for Turbomachinery Flows · SC 2023 |
High-performance computing
scientific computing systems |
0.7 | 1 | 2023 | Toward Exascale Computation for Turbomachinery Flows · SC 2023 |
Computational science and engineering › computational fluid dynamics
large eddy simulation |
0.2 | 1 | 2023 | Toward Exascale Computation for Turbomachinery Flows · SC 2023 |
Methods — techniques the papers use, named apart from their topics
high-order unstructured solver · 1.3heterogeneous parallel porting · 1.3advancing front method · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | A Dual-Layer Dynamic Obstacle-Avoidance Path Replanning Framework Based on Transformer for UAV
Chenglou Liu, Fangfang Xie, Tingwei Ji, Yao Zheng 0003 |
IEEE Internet Things J. | 5 |
| 2024 | Advancing Front Mesh Generation on Dirty Composite Surfaces
Taoran Liu, Hongfei Ye, Jianjing Zheng, Yao Zheng 0003, Jianjun Chen 0002 |
Comput. Aided Des. | 4 |
| 2023 | Toward Exascale Computation for Turbomachinery FlowsabstractA state-of-the-art large eddy simulation code has been developed to solve compressible flows in turbomachinery. The code has been engineered with a high degree of scalability, enabling it to effectively leverage the many-core architecture of the new Sunway system. A consistent performance of 115.8 DP-PFLOPs has been achieved on a high-pressure turbine cascade consisting of over 1.69 billion mesh elements and 865 billion Degree of Freedoms (DOFs). By leveraging a high-order unstructured solver and its portability to large heterogeneous parallel systems, we have progressed towards solving the grand challenge problem outlined by NASA [1], which involves a time-dependent simulation of a complete engine, incorporating all the aerodynamic and heat transfer components. Yuhang Fu, Weiqi Shen, Jiahuan Cui, Yao Zheng 0003, Guangwen Yang 0002, Jifa Zhang, Tingwei Ji, Fangfang Xie, Xiaojing Lv, Guocheng Tao, Paul Tucker, Steven A. E. Miller, Shirui Luo, Seid Koric |
SC | 4 |
| 2023 | Parametric unsteady flow modeling by using meta learning
Xinshuai Zhang, Fangfang Xie, Tingwei Ji, Changdong Zheng, Yao Zheng 0003 |
Eng. Appl. Artif. Intell. | 6 |
| 2022 | On the Efficiency of the Advancing-Front Surface Mesh Generation Algorithm
Kaixin Yu, Jianjun Chen 0002, Kejie Fu, Jiangda He, Jianjing Zheng, Yao Zheng 0003 |
Comput. Aided Des. | 6 |
| 2021 | Particle pre-processing for particle-based fluid surface reconstructionabstractIn this paper, we present a particle pre-processing pipeline tailored for the screened Poisson surface reconstruction(SPR) implemented in particle-based fluid surface reconstruction. In order for the fluid solution to be stable, we take a more reliable surface particles detection method in the solver. On this basis, instead of computing implicit function from all fluid particles, we only use surface particles by means of SPR. In order to build a smoother, feature-preserved surface, we adapt a fluid particles pre-processing pipeline to compensate for the defects of fluid particles applied to SPR. In experiment, we demonstrate how the SPR can benefit from our pre-processing pipeline and a significant improvement in quality of reconstructed surfaces as compared to existing methods. Qiaorui Chen, Yao Zheng 0003 |
VINCI | 3 |
| 2017 | Domain decomposition approach for parallel improvement of tetrahedral meshes
Jianjun Chen 0002, Yao Zheng 0003, Chenfeng Li, Jianjing Zheng |
J. Parallel Distributed Comput. | 3 |
| 2016 | Booleans of triangulated solids by a boundary conforming tetrahedral mesh generation approach
Zhoufang Xiao, Jianjun Chen 0002, Yao Zheng 0003, Jianjing Zheng |
Comput. Graph. | 3 |
| 2014 | TLR: A Traffic-Light-Based Intelligent Routing Strategy for NGEO Satellite IP NetworksabstractWe present TLR, a traffic-light-based intelligent routing strategy for NGEO satellite IP networks. In TLR, a set of traffic lights are used to indicate the congestion status at both the current node and the next node. When a packet travels along a pre-calculated route to the destination, it may adjust the route dynamically, according to the real-time color of traffic lights at each intermediate node. Through the combination of preliminary planning and real-time adjustment, each packet can eventually get an approximately optimal transmission path. The multi-path routing mechanism in TLR can help achieve a good distribution of traffics when the network traffic increases. The Public Waiting Queue scheme in TLR can fully utilize free spaces of the buffer queues and lower the packet drop rate. While the concept of TLR has many advantages, it may result in endless-loop of routing. To eliminate this phenomenon, a defense scheme is incorporated in the design of TLR. A set of simulations are conducted using the Network Simulator (version 2) to verify the good performance of TLR, in terms of lower packet drop rate, better distribution of traffics and higher throughput, over the entire satellite constellation. Guanghua Song, Mengyuan Chao, Bowei Yang, Yao Zheng 0003 |
IEEE Trans. Wirel. Commun. | 4 |
| 2013 | ROIN: reputation-oriented inverted indexing for the P2P network
Guanghua Song, Bowei Yang, Zhixing Wu, Junna Chuai, Yao Zheng 0003 |
J. Supercomput. | 5 |
| 2010 | PIVOT: An adaptive information discovery framework for computational grids
Guiyi Wei, Athanasios V. Vasilakos, Bin Xiao 0001, Yao Zheng 0003 |
Inf. Sci. | 5 |
| 2010 | A game-theoretic method of fair resource allocation for cloud computing services
Guiyi Wei, Athanasios V. Vasilakos, Yao Zheng 0003, Naixue Xiong |
J. Supercomput. | 3 |
| 2009 | CAD/CAE integration framework with layered software architectureabstractBy introducing an open-sourced CAD abstraction component common geometry module (CGM) as the integration middleware, a three-layer scheme is implemented to integrate our CAE software high end digital prototyping (HEDP) with mainstream CAD software. The major advantages of a layered software design are two-folded for CAE software developers. One is to provide unified interfaces with the differences of currently available CAD products hided. The other is to encapsulate common services relevant to geometry in the integration middleware. Both advantages could help alleviate development burdens greatly. Moreover, this paper will introduce three important functionalities for CAE systems built on the integration middleware, i.e. data transfer, defeaturing and virtual geometry operations with some practical examples. The above work consists of our preliminary efforts for the research of a third-party CAD/CAE integration middleware neutral for any CAD and CAE products. Bing-wan Cao, Jianjun Chen 0002, Yao Zheng 0003 |
CAD/Graphics | 4 |
| 2008 | ResourceDog: A Trusted Resource Discovery and Automatic Invocation P2P Framework
Bowei Yang, Guanghua Song, Yao Zheng 0003 |
NPC | 3 |
| 2005 | Parallel Unstructured Quadrilateral Mesh Generation
Jianjun Chen 0002, Yao Zheng 0003 |
ISPA | 2 |
| 2005 | Scalable Parallel Quadrilateral Mesh Generation Coupled with Mesh PartitioningabstractIn this paper, we present our efforts to parallelize an unstructured quadrilateral mesh generator. Its serial version is based on the divider-and-conquer idea, and mainly includes two stages, i.e. geometry decomposition and mesh generation. Both stages are parallelized separately. A highly efficient fine-grain level parallel scheme is presented to parallelize the stage of geometry decomposition. A SubDomain Graph (SDG), which represents the connections of subdomains, is constructed. The task of parallel mesh generation is then reduced to that of the SDG partitioning. Since the number of elements in subdomains could be pre-computed before meshing, a static load balancing scheme to partition the SDG performs well with the aid of Metis tools. Numerical results show that scalable timing performance could be achieved by using the parallel mesh generator with resulting meshes nicely partitioned among processors, which enables a fast parallel simulation environment by eliminating the traditional I/O-busy process of mesh repartitioning. Jianjun Chen 0002, Yao Zheng 0003, Xia Ning |
PDCAT | 2 |