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Introduction
I am Pantea Karimi, a Ph.D. student in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT. I am advised by Mohammad Alizadeh in the Networking and Mobile Systems Group. Currently, I'm interested in improving video conferencing applications using advanced computer vision and video compression techniques. I received my B.S. in Electrical Engineering at the Sharif University of Techology, where I worked on Decentralized Systems and Blockchains
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Publications
Publications (6)
Assessing and enhancing human learning through question-answering is vital, yet automating this process remains challenging. While large language models (LLMs) excel at summarization and query responses, their ability to generate meaningful questions for learners is underexplored. We propose Savaal, a scalable question-generation system with three...
Many problems that cloud operators solve are computationally expensive, and operators often use heuristic algorithms (that are faster and scale better than optimal) to solve them more efficiently. Heuristic analyzers enable operators to find when and by how much their heuristics underperform. However, these tools do not provide enough detail for op...
Many problems that cloud operators solve are computationally expensive, and operators often use heuristic algorithms (that are faster and scale better than optimal) to solve them more efficiently. Heuristic analyzers enable operators to find when and by how much their heuristics underperform. However, these tools do not provide enough detail for op...
Video conferencing systems suffer from poor user experience when network conditions deteriorate because current video codecs simply cannot operate at extremely low bitrates. Recently, several neural alternatives have been proposed
that reconstruct talking head videos at very low bitrates using sparse representations of each frame such as facial lan...
Real-time video streaming relies on rate control mechanisms to adapt video bitrate to network capacity while maintaining high utilization and low delay. However, the current video rate controllers, such as Google Congestion Control (GCC) in WebRTC, are very slow to respond to network changes, leading to link under-utilization and latency spikes. Wh...
Video conferencing systems suffer from poor user experience when network conditions deteriorate because current video codecs simply cannot operate at extremely low bitrates. Recently, several neural alternatives have been proposed that reconstruct talking head videos at very low bitrates using sparse representations of each frame such as facial lan...