Rate My Professor Yan Huang

Yan Huang is an Associate Professor of Software Engineering in the Department of Software Engineering and Game Development within the College of Computing and Software Engineering at Kennesaw State University, joining the institution in 2019 upon earning his Ph.D. from Georgia State University that same year. His pioneering research introduced the first academic exploration into Personalized Federated Learning (PFL) architecture and aggregation algorithms, designed to achieve individualized learning objectives for clients while avoiding performance sacrifices, particularly for non-IID data distributions. Huang's scholarly output exceeds 30 publications in top-tier journals and conferences, including IEEE Internet of Things Journal, Neural Networks, IEEE Transactions on Industrial Informatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, and IEEE Transactions on Emerging Topics in Computational Intelligence. Key works encompass "Independence and Unity: Unseen Domain Segmentation Based on Federated Learning" (IEEE Internet of Things Journal, 2023), "Exploring Personalization via Federated Representation Learning on Non-IID Data" (Neural Networks, 2023), "FedEE: A Federated Graph Learning Solution for Extended Enterprise Collaboration" (IEEE Transactions on Industrial Informatics, 2022), "Collaborative city digital twin for the COVID-19 pandemic: A federated learning solution" (Tsinghua Science and Technology, 2021, Excellent Paper Award), and "Realizing the Heterogeneity: A Self-Organized Federated Learning Framework for IoT" (IEEE Internet of Things Journal, 2020). His federated learning papers have garnered over 1,100 citations within two years, demonstrating substantial impact in privacy protection, IoT, and machine learning fields.