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PhD Candidate
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Virginia Commonwealth University
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Information, Data, Network, and Communication Sciences
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Self-Driving MAC Protocol Optimization in WLAN Networks
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Hana’s primary research goals are directed toward designing self-driving, autonomous communication protocols. Traditional communication protocols are designed through long-time and hard-work human efforts. The increasing availability and performance demands of various applications suggest that general-purpose protocol stacks are not always adequate and need to be replaced by application tailored protocols. Hana’s research aims to shift the human-based protocol design process toward a vision of an intelligent designing process that adapts and optimizes network protocols under various environment contexts such as device characteristics, application requirements, user objectives, and network conditions. More specifically, Hana focuses on data-driven MAC protocol optimization for IEEE 802.11. Taking a cross-layer optimization approach, her research shows what impact different factors across different layers can have on each other. By using machine learning techniques, she designs intelligent, self-driven MAC protocols that are autonomous, and able to perceive the surrounding environment and its characteristics (e.g., mobility patterns, other nodes joining and leaving) to efficiently optimize their design.
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Hannaneh Barahouei Pasandi is a Ph.D. student in the Computer Science Department at Virginia Commonwealth University, conducting research in the Mobile Systems & Intelligent Communication Lab led by Dr. Tamer Nadeem. She received her Master’s degree from Université Grenoble Alpes. Hana’s research broadly focuses on wireless communication, with emphasis on the design and implementation of data-driven MAC protocols that not only consider conventional factors but also extract and include important environmental factors in designing protocols for IEEE WLANs. Hana is the recipient of the N2-Women Young Researcher Fellowship in IEEE PerCom’19 among multiple IEEE/ACM awards. More information about Hana and her work can be found on her website: https://hanabhp.github.io
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Personal home page
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