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About HNNDL 2026

2026 International Conference on Human-Computer Interaction, Neural Networks and Deep Learning


The 2026 International Conference on Human-Computer Interaction, Neural Networks and Deep Learning ( HNNDL 2026 ) will be held in Shanghai from January 9 to 11, 2026! This conference focuses on cutting-edge research results in computer fields such as human-computer interaction, neural networks and deep learning, aiming to build a high-level academic exchange platform and promote in-depth exchanges and cooperation among scholars, engineers and industry professionals around the world. The meeting will set up multiple links such as thematic reports, oral reports, poster presentations, etc., to provide participants with opportunities to fully demonstrate research results and explore technological trends. In addition, the conference will also invite well-known experts to report on the conference and share the latest research results and future development directions. We warmly appeal to researchers, scholars, engineers and professionals in related fields to actively participate in and jointly promote the development of human-computer interaction, neural networks and deep learning, and jointly create a new era of intelligent technology!

重要时间

Important Dates

Full Paper Submission Date

December 15, 2025

Registration Deadline

December 20, 2026

Final Paper Submission Date

December 30, 2026

Conference Dates

January 9-11, 2026

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Call For Papers

hot.gif The topics of interest include, but are not limited to:

Man-Machine Interaction

Artificial Intelligence

Knowledge-augmented methods

Multi-task learning

Self-supervised learning

Contrastive learning

Generation model

Data augmentation

Word embedding

Structured prediction

Transfer learning / domain adaptation

Representation learning

Generalization

Model compression methods

Parameter-efficient finetuning

Few-shot learning

Reinforcement learning

Optimization methods

Continual learning

Adversarial training

Meta learning

Causality

Graphical models

Human-in-a-loop / Active learning


Neural Network

Deep learning algorithm and its application

Application of Convolutional Neural Network ( CNN ) in Image Processing

Recurrent neural network ( RNN ) and its application in sequence data

Autoencoder and generation model

The application of neural network in natural language processing ( NLP )

Application of Neural Network in Medical Image Analysis

Application of neural network in bioinformatics

Application of Neural Network in Intelligent Transportation System

Application of neural network in robot control

Application of Neural Network in Recommendation System

Application of neural network in anomaly detection and early warning  

Federated learning and distributed neural networks

Hardware acceleration of neural networks

Application of Neural Network in Internet of Things ( IoT )

Application of neural network in edge computing

Neural Networks and Photonics


Deep Learning

Deep Learning Basic Algorithms

Deep Learning in Computer Vision

Natural Language Processing combined with Vision

Migration Learning

Domain Adaptation

Augmented Learning

Federated Learning and Privacy Preservation

Self-supervised vs. unsupervised learning

Deep Learning Model Interpretability

Edge Computing


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Submission

news.gif Please send the full paper(word+pdf) to Submission System: 

Submission System (Chinese)

Submission System  (English)

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publlication

Publication

All papers submitted to HNNDL 2026 will be reviewed by two or three expert reviewers from the conference committees. After a careful reviewing process, all accepted papers will be published in the Conference Proceedings, and submitted to EI Compendex, Scopus for indexing.

Note: All submitted articles should report original results, experimental or theoretical, not previously published or being under consideration for publication elsewhere. Articles submitted to the conference should meet these criteria. We firmly believe that ethical conduct is the most essential virtue of any academic. Hence, any act of plagiarism or other misconduct is totally unacceptable and cannot be tolerated.

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