Demo Data from VLDB 2026 / reviewers in the wild / expert
Eric Li 0001
dblp:82/3391-1 · also Quan Bing Eric Li
· DBLP profile ↗
10ranked-venue papers
0as first author
7since 2021 · last 2026
0000-0001-9656-9258ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 7 · 4 since 2021Systems, architecture and hardware · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Applied, 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 |
Computational fabrication · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Human-robot interaction · 100% | |
| Artificial intelligence
1 paper |
Motion planning and robot control · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational fabrication › origami design
origami mechanism |
0.9 | 1 | 2025 | Development of Bioinspired Five-DOF Origami for Robotic Spine Assistive Exoskeleton · IEEE Trans. Robotics 2025 |
Computational fabrication › soft robotics
soft robot design |
0.9 | 1 | 2025 | Development of Bioinspired Five-DOF Origami for Robotic Spine Assistive Exoskeleton · IEEE Trans. Robotics 2025 |
Human-robot interaction › assistive robotics
exoskeleton design |
0.9 | 1 | 2025 | Development of Bioinspired Five-DOF Origami for Robotic Spine Assistive Exoskeleton · IEEE Trans. Robotics 2025 |
Robotics › Motion planning and robot control › robot control
adaptive control |
0.3 | 1 | 2025 | Development of Bioinspired Five-DOF Origami for Robotic Spine Assistive Exoskeleton · IEEE Trans. Robotics 2025 |
Robotics › Motion planning and robot control
robot control |
0.3 | 1 | 2025 | Development of Bioinspired Five-DOF Origami for Robotic Spine Assistive Exoskeleton · IEEE Trans. Robotics 2025 |
Methods — techniques the papers use, named apart from their topics
cable-driven actuation · 2.6under-actuated mechanism · 1.7underactuated mechanism · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | EDGAN: a novel GAN framework incorporating a diversity discriminator for robust data generation
Aiguo Cheng, Caiyu Ma, Zhicheng He 0004, Hexin Jiang, Eric Li 0001 |
Appl. Intell. | 5 |
| 2025 | Investigating 3D object detection using stereo camera and LiDAR fusion with bird's-eye view representation
Zhicheng He 0004, Aiguo Cheng, Shengshi Zhong, Eric Li 0001 |
Neurocomputing | 6 |
| 2025 | Development of Bioinspired Five-DOF Origami for Robotic Spine Assistive ExoskeletonabstractFrequent and high-load manual material handling (MMH) tasks often cause back injuries to the workers, and backsupport exoskeletons are developed for individuals with MMH tasks. However, these exoskeletons usually cannot adapt well to the movements of the wearer's spine. This paper introduces a new bio-inspired 5-DOF origami, and via mechanical design, a unique rigid-flexible coupled bio-inspired origami mechanism is proposed. This origami mechanism is compact and lightweight, and it has stable kinematic behaviors. With the designed origami mechanisms, a novel active origami-based robotic spine assistive exoskeleton (OSAE) is developed to assist individuals with MMH tasks during the symmetric and asymmetric lifting. The OSAE is actuated by a cable-driven module through an under-actuated spine module that consists of seven origami mechanisms. With the designed spine module, the OSAE can adapt well to the wearer's spine motions during MMH tasks. Modeling of the 5- DOF origami is described, and an adaptive control strategy is proposed for the exoskeleton to adapt to different lifting methods and objects with different weights. The experimental results demonstrate the effectiveness of the proposed OSAE. During the symmetric lifting of a 10-kg object, a reduction of 41.28% of the average muscle activity of the wearer's lumbar erector spinae muscle (LES) is observed, and reductions of 30.15% and 39.54% of the average muscle activities of the wearer's left and right LES are observed, respectively, during the asymmetric lifting of a 10- kg object. Bing Chen 0005, Xiang Ni, Lei Zhou 0029, Bin Zi, Eric Li 0001, Dan Zhang 0006 |
IEEE Trans. Robotics | 5 |
| 2024 | Robust locally nonlinear embedding (RLNE) for dimensionality reduction of high-dimensional data with noise
Eric Li 0001 |
Neurocomputing | 2 |
| 2024 | A minimum complexity interaction echo state network
Xu Xu 0004, Eric Li 0001 |
Neural Comput. Appl. | 3 |
| 2023 | A novel marine predators algorithm with adaptive update strategy
Zhicheng He 0004, Eric Li 0001, Yuanyi Huang |
J. Supercomput. | 4 |
| 2022 | A novel efficient method for welding spots detection
Zhicheng He 0004, Yadong Ma, Eric Li 0001 |
Multim. Tools Appl. | 4 |
| 2020 | The feedback artificial tree (FAT) algorithm
Zhicheng He 0004, Eric Li 0001 |
Soft Comput. | 3 |
| 2017 | The artificial tree (AT) algorithm
Zhicheng He 0004, Eric Li 0001, Aiguo Cheng |
Eng. Appl. Artif. Intell. | 4 |
| 2017 | Stability and instability of a neuron network with excitatory and inhibitory small-world connections
Dongyuan Yu, Xu Xu 0004, Eric Li 0001 |
Neural Networks | 4 |