Welcome to my personal website!
I am a Ph.D. graduate in the Holcombe Department of Electrical and Computer Engineering at Clemson University where I completed my dissertation under supervision of Dr. Fatemeh Afghah. My research focuses on artificial intelligence and deep reinforcement learning for dynamic optimization in wireless communication systems, particularly Open RAN, multi-agent learning, and LLM-augmented decision-making.
Prior to joining Clemson, I was a research assistant in the College of Engineering and Applied Science at University of Colorado Colorado Springs, where I worked 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 work bridges theory and application—developing adaptive AI solutions that are robust, scalable, and grounded in real-world communication challenges.
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
News
- [2025 November] I successfully defended my Ph.D. in November 2025 — cheers to the next step!
- [2025 November] Our journal paper “Task-Specific Sharpness-Aware O-RAN Resource Management using Multi-Agent Reinforcement Learning” has been accepted to IEEE Transactions on Machine Learning in Communications and Networking (IEEE TMLCN).
- [2025 January] Our conference paper “LLM-Augmented Deep Reinforcement Learning for Dynamic O-RAN Network Slicing” has been accepted to IEEE ICC — SAC Machine Learning for Communications and Networking Track at Montreal, Canada.
- [2024 December] Our conference paper “Meta reinforcement learning approach for adaptive resource optimization in O-RAN” has been accepted to IEEE WCNC at Milan, Italy.
- [2024 November] Passed Ph.D. Comprehensive Exam.
- [2024 October] Our Journal paper on “Joint path planning and power allocation of a cellular-connected UAV using apprenticeship learning via deep inverse reinforcement learning” has been accepted to Computer Networks Journal.
- [2023 October] Presented conference paper “Open RAN LSTM Traffic Prediction and Slice Management using Deep Reinforcement Learning” in IEEE 2023 Asilomar Conference on Signals, Systems, and Computers at Pacific Grove, CA, USA.
- [2023 August] Our conference paper on “[Open RAN LSTM Traffic Prediction and Slice Management using Deep Reinforcement Learning] ((https://ieeexplore.ieee.org/abstract/document/10476972))” has been accepted to IEEE Asilomar 2023.
- [2023 August] Our conference paper on “[Attention-based Open RAN Slice Management using Deep Reinforcement Learning] ((https://ieeexplore.ieee.org/abstract/document/10436850))” has been accepted to IEEE Globecom 2023.
- [2023 March] Passed Ph.D. Qualification Exam.
- [2022 December] Presented conference paper “Evolutionary Deep Reinforcement Learning for Dynamic Slice Management in O-RAN” virtually in IEEE Global Communications Conference (GLOBECOM) at Rio de Janeiro, Brazil.
- [2022 May] Presented conference paper “Semantic-Aware Collaborative Deep Reinforcement Learning Over Wireless Cellular Networks” virtually in IEEE International Conference on Communications (ICC) at Seoul, Korea.
- [2021 April] Presented conference paper “Performance Analysis and Optimization of Uplink Cellular Networks with Flexible Frame Structure” virtually in IEEE 93rd Vehicular Technology Conference (VTC2021-Spring) at Helsinki, Finland.
- [2022 August] Joined Clemson University as an Ph.D. Student.
- [2021 January] Joined University of Colorado Colorado Springs as an Research Assistant.