Weixian Liao

Assistant Professor

Towson University

United States

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About

Weixian Liao is an Assistant Professor at Towson University, USA. His research primarily focuses on artificial intelligence, federated learning, and cybersecurity, with recent publications addressing topics such as model calibration, multi-task learning in smart transportation, and distributed IoT security. He has contributed significantly to the advancement of knowledge in deep learning applications and their integration with blockchain technology.

Articles (14)

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2025

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2024

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2024

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2024

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2023

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2023

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2023

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2022

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2022

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2022

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2020

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Towson University

UNITED STATES

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Weixian Liao

Research Interests

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About

Articles (14)

Survey of Artificial Intelligence Model Marketplace

Survey on Multi-Task Learning in Smart Transportation

Incentive Design for Heterogeneous Client Selection: A Robust Federated Learning Approach

Evaluating Impact of Image Transformations on Adversarial Examples

Deep Neural Networks for Spatial-Temporal Cyber-Physical Systems: A Survey

Survey of Distributed and Decentralized IoT Securities: Approaches Using Deep Learning and Blockchain Technology

Blockchain-Empowered Federated Learning Through Model and Feature Calibration

Resource-Aware Knowledge Distillation for Federated Learning

A Fairness-Aware Peer-to-Peer Decentralized Learning Framework with Heterogeneous Devices

Secure IoT Search Engine: Survey, Challenges Issues, Case Study, and Future Research Direction

WSCC: A Weight-Similarity-Based Client Clustering Approach for Non-IID Federated Learning

Priority-aware Reinforcement Learning-Based Integrated Design of Networking and Control for Industrial Internet of Things

Spectrum Availability Prediction for Cognitive Radio Communications: A DCG Approach

Zero Knowledge Clustering Based Adversarial Mitigation in Heterogeneous Federated Learning

Collaborators (5)

Xuhui Chen

Yifan Guo

Wei Yu

Michael McGuire

Qianlong Wang

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