Hao Do Phuc

I'm a PhD student in Computer Science at SUT (Federal State Budgetary Educational Institution of Higher Education "Saint Petersburg State University of Telecommunications named after prof. M.A. Bonch-Bruevich") currently working on machine learning applications in IoT security and network traffic analysis. My research focuses on developing novel approaches for detecting malicious traffic and botnet attacks in IoT networks using federated learning and deep learning techniques. I specialize in applying advanced machine learning models like Graph Neural Networks, Convolutional Neural Networks, and Transformers to network security challenges. My recent work has explored horizontal federated learning approaches for IoT malware detection, designing efficient feature extraction methods for attack classification, and leveraging pretrained models for various ML tasks.

Prior to my current research, I worked on human action recognition in video sequences using hybrid deep learning architectures combining FFT and EfficientNet models. I've published several papers in international conferences like ICACT, RIVF, and ICUMT, collaborating with researchers from multiple institutions to advance the fields of network security and machine learning. My current interests span federated learning, IoT security, computer vision, and natural language processing.