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Qun Jin

Professor

Waseda University

Japan

Research Interests

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About

Dr. Qun Jin is an Associate Professor at Waseda University in Japan. His research interests encompass areas such as residential load forecasting using graph neural networks, network intrusion detection frameworks, and the integration of traditional medicine into modern reproductive technologies. Additionally, Dr. Jin has made significant contributions to the fields of decentralized federated learning, smart grid security, financial risk assessment, and machine learning applications in healthcare.

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Collaborators (15)

Weiren Yu

Assistant Professor

University of Warwick

UNITED KINGDOM

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Yegang Du

Tohoku University

JAPAN

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Guanqun Sun

Researcher

Japan Advanced Institute of Science and Technology

JAPAN

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Zheng Yan

Aalto University

FINLAND

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Xingru Huang

Queen Mary University of London

UNITED KINGDOM

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Laurence T. Yang

St. Francis Xavier University

CANADA

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Atsushi OGIHARA

Waseda University

JAPAN

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Ruichen Cong

Assistant Professor

Waseda University

JAPAN

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Shohei SHIMIZU

Shiga University

JAPAN

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Katsutoshi Yada

Professor

Kansai University

JAPAN

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Shoji Nishimura

Professor

Waseda Daigaku Riko Gakujutsuin

JAPAN

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Ran Dong

Lecturer

Chukyo University

JAPAN

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Kevin Wang

University of Auckland

NEW ZEALAND

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Jianjia Wang

Assistant Professor

Xi’an Jiaotong-Liverpool University

CHINA

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Bo WU

Assistant Professor

Tokyo Institute of Technology

JAPAN

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Qun Jin

Research Interests

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About

Articles (51)

Health information–seeking behavior for gastric cancer in Japan: Analysis of temporal changes and regional differences using Google Trends

Lesion-aware visio-linguistic context regularization for radiology report generation

Study of Human Papillomavirus Vaccine–Related Social Media Content Across Eight Social Media Platforms: Scoping Review of Communication Content, Information Sources, and Analytical Approaches

Variational GAN-Enhanced Causal Effect Inference for Interpretable Learning in Heterogeneous IoT Systems

Active Learning with Generative AI to Enhance Learning Experience: Experiment Design and Verification

Analysis of Combined Impact of Information and Emotional Content on User Engagement Based on Social Media Data

HCI-Enhanced Online Learning Support with AI Tutors in Metaverse

Assessing ChatGPT-generated comments for video-based learning content to enhance knowledge and emotional support based on scaffolding theory

A Robustness Enhancement Strategy for Structure-Sensitive Tasks via Diverse Adversarial Perturbations

A hybrid CNN–Mamba state space model with pyramid-pooled skip connections for prostate tumor segmentation

A global-to-local state space model with context-mixing dynamic kernels for medical image classification

An automatic photovoltaic cell anomaly detection framework based on adversarial reconstruction of deep multi-scale feature

CMSA: Addressing semantic discrepancy and context dependency in multimodal sentiment analysis

Ontology-enhanced subgraph reasoning with prompt learning for inductive knowledge graph completion

V-trex: Visual-prompt enhanced detection with attention selection fusion module and random-crop quadruplet loss

ChatGPT-Generated Comments Based on Scaffolding Theory for Online Learning Support

Classification of Approval Desires and Analysis of Emotional and Linguistic Features in SNS Posts Using Generative AI

LLM-Enhanced Explanatory Signals for Improved API Recommendation in Consumer Electronics Software Development

Multimodal Global Semantics-Based Triple-Fusion Branch Framework for Fake News Detection

S-PFEL: Secured Prototypical Personalized Federated Edge Learning for Consumer Electronics

Decentralized Federated Graph Learning With Lightweight Zero Trust Architecture for Next-Generation Networking Security

Integrating Acupuncture and Herbal Medicine into Assisted Reproductive Technology: A Systematic Review and Meta-Analysis of East Asian Traditional Medicine

Ego-centric multiple-correlation and temporal graph neural networks based residential load forecasting

MTRC: A self-supervised network intrusion detection framework based on multiple Transformers enabled data reconstruction with contrastive learning

Locational False Data Injection Attack Detection in Smart Grid Using Recursive Variational Graph Autoencoder

Financial risk assessment of imbalanced data based on nonlinear causal time-series network

Research on predicting the sleep status of orthopedic pain patients based on machine learning

Meta-Data-Guided Robust Deep Neural Network Classification with Noisy Label

Exploring multi-granularity contextual semantics for fully inductive knowledge graph completion

Reconstructed Graph Neural Network With Knowledge Distillation for Lightweight Anomaly Detection

Blinding and blurring the multi-object tracker with adversarial perturbations

Decoupling representation contrastive learning for carbon emission prediction and analysis based on time series

Adaptive Weighting via Federated Evaluation Mechanism for Domain Adaptation with Edge Devices

ConeE: Global and local context-enhanced embedding for inductive knowledge graph completion

A Text-Enhanced Transformer Fusion Network for Multimodal Knowledge Graph Completion

Heterogeneous network influence maximization algorithm based on multi-scale propagation strength and repulsive force of propagation field

Personalized Federated Learning With Model-Contrastive Learning for Multi-Modal User Modeling in Human-Centric Metaverse

Group Behavior Prediction and Evolution in Social Networks

Influence maximization algorithm based on group trust and local topology structure

A Self-Supervised Learning Based Framework for Eyelid Malignant Melanoma Diagnosis in Whole Slide Images

Behavioral Analysis of Mowing Workers Based on Hilbert–Huang Transform: An Auxiliary Movement Analysis of Manual Mowing on the Slopes of Terraced Rice Fields

Bi-Dueling DQN Enhanced Two-Stage Scheduling for Augmented Surveillance in Smart EMS

Intelligent Containment Control With Double Constraints for Cloud-Based Collaborative Manufacturing

Edge-Enabled Two-Stage Scheduling Based on Deep Reinforcement Learning for Internet of Everything

GOMPS: Global Attention-based Ophthalmic Image Measurement and Postoperative Appearance Prediction System

Dynamic Multi-view Group Preference Learning for group behavior prediction in social networks

A short-term residential load forecasting scheme based on the multiple correlation-temporal graph neural networks

Hic-KGQA: Improving multi-hop question answering over knowledge graph via hypergraph and inference chain

Rumor source localization in social networks based on infection potential energy

Coevolution modeling of group behavior and opinion based on public opinion perception

Information Theoretic Learning-Enhanced Dual-Generative Adversarial Networks With Causal Representation for Robust OOD Generalization

Collaborators (15)

Weiren Yu

Yegang Du

Guanqun Sun

Zheng Yan

Xingru Huang

Laurence T. Yang

Atsushi OGIHARA

Ruichen Cong

Shohei SHIMIZU

Katsutoshi Yada

Shoji Nishimura

Ran Dong

Kevin Wang

Jianjia Wang

Bo WU

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