
About
Dr. Roman Kolcun is a Research Fellow at the Department of Computer Science and Technology, University of Cambridge. His work focuses on Internet of Things (IoT) systems, privacy preservation, edge computing, and wireless sensor networks. He employs machine learning techniques like neural networks and Bayesian models for IoT device identification and security. He is involved in the DADA Project and Compute First Networking initiatives, exploring edge computing and network security challenges. His research emphasizes ethical data capture and scalable device identification in real-world IoT environments.
Key research interests include: IoT device identification using network traffic analysis, privacy-preserving mechanisms in smart home ecosystems, and retraining machine learning models at the edge to maintain accuracy over time. His projects address energy efficiency in serverless edge computing and federated learning approaches for model updates.
Labs/Teams: Active contributor to the DADA Project (https://dada.cl.cam.ac.uk) and Compute First Networking (https://www.cl.cam.ac.uk/research/srg/projects/cfn/).
Publications trends show focus on edge computing, IoT security, and scalable machine learning deployments. His work bridges theoretical machine learning advancements with practical edge infrastructure challenges, emphasizing real-world IoT ecosystem resilience.
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