Paul Joe Maliakel

Paul Joe Maliakel is a PreDoc Researcher at Technische Universität Wien, affiliated with the Computational Sustainability department (E191-05). His work focuses on addressing data incompleteness in federated learning systems and optimizing energy efficiency for AI applications.

Research Interests:

• Computational Sustainability
• Federated Learning
• Edge Analytics
• Machine Learning
• Energy-Efficient Computing
• GAN Applications

Recent Publications Trends: His research spans federated learning architectures, energy-efficient AI inference, and data sustainability in edge computing environments. Key contributions include the FLIGAN framework for handling incomplete data in federated systems and analyses of energy-performance trade-offs in LLM deployments.

Projects: Active in FWF-funded initiatives like Themis (2024–2027) and TRITON (2023–2027), as well as the Virtual Shepherd project (2024–2026), focusing on sustainable edge analytics.