Nasim Nezhadsistani

Nasim Nezhadsistani received her B.Sc. and M.Sc. degrees in Electrical Engineering in 2014 and 2017, respectively. She is currently a doctoral researcher with the Communication Systems Group (CSG) at the Department of Informatics, University of Zurich, under the supervision of Prof. Dr. Burkhard Stiller. She has been with CSG as a Research Assistant since 2022.

Her research focuses on Explainable and Trustworthy Artificial Intelligence (XAI), machine learning for cybersecurity, and intelligent next-generation communication networks, particularly 5G, Beyond-5G, and 6G systems. Her current work investigates efficient and reliable explanation methods for machine-learning models, explainable intrusion and anomaly detection, and the evaluation of explanation quality in security-critical applications.

Her broader research interests include decentralized and federated learning, sustainable AI, network security, and blockchain-enabled systems. She is particularly interested in developing transparent, robust, and resource-efficient AI solutions for secure intelligent networked systems.

• Explainable and Trustworthy Artificial Intelligence (XAI)
• Machine Learning for Cybersecurity
• Network Security and Intrusion Detection
• 5G, Beyond-5G, and 6G Networks
• Federated and Decentralized Learning
• Blockchain and Distributed Systems

[Journal Paper] Nasim Nezhadsistani, Mohsen Tajgardan, Mahdi Rabbani, Weijie Niu, and Burkhard Stiller, “Design and Evaluation of a Robust and Explainable Intrusion Detection Framework for 5G/B5G Networks,” Computer Networks, vol. 278, Art. 112100, 2026.

[Journal Paper] Nasim Nezhadsistani, Naghmeh S. Moayedian, Arash Bozorgchenani, and Burkhard Stiller, “A Multi-Objective Task Offloading and Resource Allocation in Blockchain-Enabled IoT Networks,” Ad Hoc Networks, vol. 193, Art. 104361, 2026.

[Conference Paper] Nasim Nezhadsistani, Chao Feng, Youssef Ehab Youssef Farag, Francisco Enguix, and Burkhard Stiller, “Toward Sustainability-Aware Decentralized Federated Learning for Anomaly Detection in 5G and Beyond 5G,” ICT 2026, 2026.

[Conference/Demo] Nasim Nezhadsistani and Burkhard Stiller, “Interactive XAI Dashboard for 5G/B5G Intrusion Detection,” EuCNC 2026, Málaga, Spain, 2026.

[Conference Paper] Francisco Enguix, Saúl Cerdá-Peris, Nasim Nezhadsistani, Burkhard Stiller, and Carlos Carrascosa, “S-ACoaL: A Semantic-Driven Coalition Consensus Algorithm for Decentralized Federated Learning,” FLICS 2026, pp. 213–221, 2026.

[Journal Paper] Nasim Nezhadsistani, Naghmeh S. Moayedian, and Burkhard Stiller, “Blockchain-Enabled Federated Learning in Healthcare: Survey and State-of-the-Art,” IEEE Access, vol. 13, pp. 119922–119945, 2025.

[Book Chapter] Nasim Nezhadsistani and Burkhard Stiller, “Leveraging Explainable AI for Cybersecurity,” in Challenges and Solutions for Cybersecurity and Adversarial Machine Learning, pp. 271–306, 2025.

[Conference Paper] Nasim Nezhadsistani and Burkhard Stiller, “ML-based Anomaly Detection in 6G Networks: A Survey on the Current Status, Challenges, and Future Directions,” IEEE 6GNet 2024, pp. 1–9, 2024.

[Book Chapter] Nasim Nezhadsistani, Seyed Mojtaba Hosseini Bamakan, and Naghmeh Sadat Moayedian. "Blockchain consensus algorithms: Past, present, and future trends." In Distributed Computing to Blockchain, pp. 145-171. Academic Press, 2023. Link

[Jornal Paper] Bamakan, Seyed Mojtaba Hosseini, Nasim Nezhadsistani, Omid Bodaghi, and Qiang Qu. "Patents and intellectual property assets as non-fungible tokens; key technologies and challenges." Scientific Reports 12, no. 1 (2022): 2178.Link

[Full Paper] Nourmohammadi, Reza, Mahdi Arabian, Masoumeh Ghorbanpour, Mohammad M. Nazemi, and Nasim Nezhadsistani. "NFT Scoring: An Analysis of the Considerable Features." In Proceedings of the 2022 5th International Conference on Blockchain Technology and Applications, pp. 57-62. 2022.Link