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Junyuan Chen

dblp:299/2317 · DBLP profile ↗
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4ranked-venue papers
1as first author
4since 2021 · last 2026
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 1 first-author · 2 since 2021Applied, interdisciplinary, general and emerging computing · 2 · 2 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 architecture, parallel and distributed computing, and storage systems
2 papers
Emerging computing paradigms · 60% Memory systems · 40%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Emerging computing paradigms
neuromorphic computing
2.022026
A sensing-memory-computing integrated optoelectronic synaptic device based on Ag/PtTe2/FTO for artificial vision information processing · Sci. China Inf. Sci. 2026
Robust optoelectronic dual-mode memristor enabled by ZnO/MoS2 heterojunction for synaptic bionics and in-memory computing · Sci. China Inf. Sci. 2026
Memory systems
in-memory computing
1.012026
Robust optoelectronic dual-mode memristor enabled by ZnO/MoS2 heterojunction for synaptic bionics and in-memory computing · Sci. China Inf. Sci. 2026
Emerging computing paradigms › neuromorphic computing
memristive devices
1.012026
Robust optoelectronic dual-mode memristor enabled by ZnO/MoS2 heterojunction for synaptic bionics and in-memory computing · Sci. China Inf. Sci. 2026
Memory systems
processing-in-memory
1.012026
Robust optoelectronic dual-mode memristor enabled by ZnO/MoS2 heterojunction for synaptic bionics and in-memory computing · Sci. China Inf. Sci. 2026

Methods — techniques the papers use, named apart from their topics

heterojunction design · 1.0
YearPublicationVenuePosition
2026 Robust optoelectronic dual-mode memristor enabled by ZnO/MoS2 heterojunction for synaptic bionics and in-memory computing
Youshan Gui, Junyuan Chen, Tenglong Guo, Suo Zhang, Xian Wei, Xiaojuan Lian, Er-Tao Hu, Haifeng Ling
Sci. China Inf. Sci.5
2026 A sensing-memory-computing integrated optoelectronic synaptic device based on Ag/PtTe2/FTO for artificial vision information processing
Xiaojuan Lian, Chaoyi Ban, Junyuan Chen, Zhikuang Cai, Lei Wang 0056
Sci. China Inf. Sci.6
2025 Network collaborator: Knowledge transfer between network reconstruction and community detection
Chao Wang 0099, Kai Wu 0003, Junyuan Chen, Jing Liu 0006
Neurocomputing4
2021 A Memetic Algorithm for Optimizing Inter-links to Enhance the Robustness of Interdependent Networks Against Malicious Attacks
abstract
In real life, independent networks exist widely and their robustness has received significant attention. When an interdependent network faces attacks, the failure can propagate along inter-links to the whole network and the damage caused by malicious attacks is more serious. However, in terms of designing the robust inter-links of interdependent networks, most of the existing strategies target at random attacks and make little use of the inner structure of interdependent networks. In this paper, we propose a specific memetic algorithm (MA) for optimizing the inter-links to enhance the robustness of interdependent networks against malicious attacks, termed as MA-RINint. Moreover, we design an effective crossover operator based on retaining the inter-links of adjacent nodes and a local search operator according to the degree of nodes. In the experiments, we compare the proposed algorithm with five existing methods on three types of interdependent networks with different sizes, and the experimental results show that MA-RINint performs excellently in enhancing the robustness of interdependent networks.
Junyuan Chen, Jing Liu 0006
CEC1