Welcome to my personal website!

I am a researcher in artificial intelligence and learning-based systems, with expertise in reinforcement learning, foundation models, and adaptive decision-making for complex networked environments. My work focuses on designing robust and scalable AI frameworks for dynamic optimization, with particular emphasis on Open RAN architectures, multi-agent systems, and LLM-augmented control.

I completed my Ph.D. in Holcombe Department of Electrical and Computer Engineering at Clemson University, where my research advanced optimization-aware and learning-driven methods for next-generation wireless systems. Previously, I conducted research at the College of Engineering and Applied Science at University of Colorado Colorado Springs on semantic-aware reinforcement learning for communication networks. I hold an M.Sc. in Electrical Engineering from the University of Tehran and a B.Sc. from Iran University of Science and Technology.

My research bridges theory and deployment, developing AI systems that integrate principled learning, interpretability, and real-world constraints. I am broadly interested in applying foundation and multimodal models to adaptive, data-driven decision-making in networked and cyber-physical systems.

Research Interests

• AI for Wireless Communication Systems (5G/6G, O-RAN)
• Multi-Agent and DRL for Distributed Decision-Making
• Foundation and LMMs for Adaptive Control and Resource Allocation
• Meta-Learning, Transfer Learning, and Representation Learning
• Multimodal Perception and Learning for Autonomous and Intelligent Systems

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