On March 5, 2025, Sabtain Ahmad received the Critical Infrastructure Award 2024 of the Austrian Academy of Sciences (ÖAW). The award aims to recognize young scientists in fields such as computer science and related disciplines for their exceptional contributions to safety-critical infrastructures such as transportation systems, energy networks, or telecommunications networks. The award supports outstanding academic achievements by young researchers during their PhD studies and is endowed with 10,000 Euros.

In his research, Sabtain Ahmad focuses on using Artificial Intelligence (AI) to improve real-time decision-making at the edge of critical infrastructures, improving efficiency, energy consumption, and aspects of privacy. The growing reliance on critical infrastructures, such as water management, energy networks, and transportation systems, demands real-time monitoring and intelligent decision-making to ensure their safety and efficiency. However, these infrastructures generate vast amounts of data at the network edge, often in remote or resource-constrained environments, creating challenges in energy consumption, communication efficiency, and data privacy. Traditional cloud-based analytics struggle to process this data efficiently due to latency, bandwidth limitations, and privacy concerns. His research addresses these challenges by developing AI-driven Edge Intelligence frameworks that enable energy-efficient, real-time decision-making at the network edge. By leveraging federated learning and edge computing, his work optimizes how AI models are trained and deployed on resource-limited edge devices, reducing the need for continuous data transmission while ensuring low-latency, privacy-preserving operations.

Congratulations to Sabtain Ahmad for his outstanding scientific achievements!

About Sabtain Ahmad

Sabtain Ahmad is a PreDoc researcher at TU Wien Informatics, specializing in Edge AI and distributed Machine Learning for safety-critical infrastructures. He holds a Master’s degree in Data Science from TU Berlin and a Bachelor’s degree in Computer Science from the National University of Computer and Emerging Sciences (FAST-NU), where he graduated Magna Cum Laude. His research excellence has earned him prestigious awards, including the Critical Infrastructure Award of the Austrian Academy of Sciences, a NetIdee PhD Dissertation Award, and an ICT R&D Award from FAST-NU. He actively contributes as a reviewer for core AI and systems conferences, a program committee member, and a co-teacher at TU Wien. Engaged in international collaborations, his work bridges academia and industry to develop energy-efficient, AI-driven solutions for resilient and sustainable critical infrastructures.

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