Demo Data from EDBT 2026 / reviewers in the wild / expert
Shengxue Wang
dblp:379/7094
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2026
0009-0008-1950-4520ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 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 |
Geometric modeling and processing · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Geometric modeling and processing › shape optimization
isogeometric shape optimization |
1.0 | 1 | 2026 | Integrating surface lofting and hybrid sensitivity analysis for isogeometric shape optimization of shell structures · Comput. Aided Des. 2026 |
Geometric modeling and processing › solid modeling
shell structures |
0.3 | 1 | 2026 | Integrating surface lofting and hybrid sensitivity analysis for isogeometric shape optimization of shell structures · Comput. Aided Des. 2026 |
Methods — techniques the papers use, named apart from their topics
surface lofting · 1.0hybrid sensitivity analysis · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Integrating surface lofting and hybrid sensitivity analysis for isogeometric shape optimization of shell structures
Xiaoxiao Du 0002, Mengchan Liu, Shengxue Wang, Gang Zhao 0007 |
Comput. Aided Des. | 3 |
| 2024 | A Laser-Induced Graphene-Based Flexible Multimodal Sensor for Material and Texture PerceptionabstractHumans can perceive and interact with their surroundings through multiple senses. For intelligent robots, multimodal sensors are crucial for them to perceive and understand the environment. In this work, we propose a multi-layered flexible multimodal sensor based on laser-induced graphene, capable of detecting both touchless signals (such as the distance from external objects and their material) and tactile signals (three-dimensional force). The sensor has advantages in durability and stability. Under normal force, the sensitivity is –7.449% N–1in the range of 0 N to 1.5 N and –0.273% N–1in the range of 1.5 N to 30 N, with fast response (17 ms) and recovery (37 ms). Furthermore, using the Convolutional Neural Networks (CNN) model, we develop an intelligent soft robot system capable of distinguishing objects of different materials and fabric textures with accuracies of 99% and 88.75%, respectively. The proposed flexible multimodal sensor holds a significant effect on the perception and interaction of intelligent robots with the environment. Youning Duo, Jinxi Duan, Shengxue Wang |
IROS | 5 |