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Southeast University, China

2026 14th International Conference on Intelligent Computing and Wireless Optical Communications (ICWOC 2026) & ISA Global LiFi Summit will be held during May 15-17, 2026 in Nanjing, China. It's sponsored by Southeast University, China, ISA, and LiFi; hosted by School of Information Science and Engineering, Southeast University, China; co-hosted by Southwest Jiaotong University, China and Chongqing University, China; Technically co-sponsored by IEEE and IEEE Photonics Society.

Email: saraxc17@163.com

- Wireless Communications & Mobile Computing - Communication & Information Theory - Computer & Network Security (intrusion detection, encryption) - Cross-Layer Optimized Wireless Networks - MIMO Systems (massive MIMO, beamforming) - Next-Generation Mobile Networks (5G-Advanced, 6G) - Wireless LANs/WPANs (Wi-Fi 7, Bluetooth 5.4) - Wireless Sensor Networks (low-power IoT nodes) - Cooperative/Cognitive Radio Networks - Vehicular Communication (V2X, C-V2X) - Emergency & Disaster-Response Communication Platforms - Edge Computing for Wireless Networks - Optical Networking Technologies (SDN/NFV for optical networks, sliceable optics) - Optical Switching & Network Elements (ROADMs, optical cross-connects, micro-ring resonators) - Coherent Optical Transmission (100G+/400G/800G systems) - Wavelength Division Multiplexing (DWDM, CWDM) - Optical Fiber Reliability & Fault Tolerance - Energy-Efficient Optical Network Design

Sichuan Province Computer Federation

It is sponsored by Sichuan Province Computer Federation and technically assisted by many local and international universities. This conference provides you opportunity to meet with academicians as well as practitioners in the fields of Artificial Intelligence and Big Data from all over the world, and get the latest insights from every area of Artificial Intelligence and Big Data theory and practice.

Tel.: [86-28-87777577];     Email: emmaawang2019@sina.com

Artificial Intelligence: Intelligent information systems; Intelligent data mining and farming; Intelligent web-based business; Intelligent agents; Intelligent networks; Intelligent databases; Intelligent user interface; AI and evolutionary algorithms; Intelligent tutoring systems; Reasoning strategies; Distributed AI algorithms and techniques; Distributed AI systems and architectures; Neural networks and applications; Heuristic searching methods; Languages and programming techniques for AI; Constraint-based reasoning and constraint programming; Intelligent information fusion; Learning and adaptive sensor fusion; Search and meta-heuristics; Multisensor data fusion using neural and fuzzy techniques; Integration of AI with other technologies; Evaluation of AI tools; Social intelligence (markets and computational societies); Social impact of AI; Emerging technologies; Brain models, Brain mapping, Cognitive science; Natural language processing; Fuzzy logic and soft computing; Software tools for AI; Decision support systems; Automated problem solving.

Hangzhou Dianzi University, China

As the integration of signal processing and machine learning deepens, this interdisciplinary field is experiencing rapid advancements. The emergence of deep learning has significantly enhanced the automation and intelligence of signal analysis, achieving remarkable breakthroughs in domains such as audio processing, image recognition, and medical diagnostics. Simultaneously, multimodal data fusion and AI-driven signal analysis have emerged as critical trends. However, challenges such as limited model interpretability, robustness against noise and distributional shifts, and adaptability in resource-constrained environments remain pressing issues, necessitating further research and practical exploration.

Tel.: [+86-021-59561560];     Email: amychou2020@163.com

Machine learning methods/ algorithms: Computer Vision & Virtual Reality; Image Processing & Understanding; Image/Video Processing and Coding; Natural Language Processing; Machine learning methods; Learning and adaptive control; Learning/adaption of recognition and perception; Learning for Handwriting Recognition; Learning in Image Pre-Processing and Segmentation; Learning in process automation; Learning of appropriate behaviour; Learning of action patterns; Learning robots; Feature extractions; Support vector machines (SVM); Least-squares SVM (LS-SVM); Twin SVM (TWSVM); Extreme learning machine (ELM); Artificial neural network (ANN); Classification techniques; Kernel design; Reinforce learning; Deep learning.