معرفی
Amir Sonee is a Postdoctoral Research Associate at the Centre for AI Fundamentals within the Department of Computer Science, focusing on privacy-preserving techniques in probabilistic machine learning and federated learning systems. He holds a PhD and M.Sc. in Electrical Engineering from Ferdowsi University of Mashhad and Sharif University of Technology, respectively, with a B.Sc. from Ferdowsi University of Mashhad. His research integrates machine learning, data privacy, physical layer security, and wireless communications, emphasizing theoretical foundations and practical applications. He has collaborated with institutions like King's College London and National Yang Ming-Chiao Tung University on projects involving secure federated learning in wireless environments.
Education:
- PhD in Electrical Engineering (2011–2017), Ferdowsi University of Mashhad
- M.Sc. in Electrical Engineering (2008–2010), Sharif University of Technology
- B.Sc. in Electrical Engineering (2004–2008), Ferdowsi University of Mashhad
Research interests span privacy-preserving machine learning, federated learning, secure wireless communication, and information-theoretic approaches to network security. His work bridges theoretical advancements with real-world challenges in trustworthy AI and distributed systems.
He is part of the MCAIF: Centre for AI Fundamentals project, exploring reinforcement learning and neural networks for AI applications. His contributions include optimizing federated learning protocols under communication constraints and advancing secrecy capacities in multi-user wireless systems.
