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A Survey on Energy Consumption and Environmental Impact of Video Streaming

Published in arXiv preprint arXiv:2401.09854, 2024

Analyzes energy consumption and environmental implications of video streaming technologies and infrastructures.

Recommended citation: S. Afzal, N. Mehran, Z. Azimi, F. Tashtarian, H. Amirpour, and R. Prodan. (2024). *A Survey on Energy Consumption and Environmental Impact of Video Streaming.* arXiv preprint arXiv:2401.09854.
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Towards ML-Driven Video Encoding Parameter Selection for Quality and Energy Optimization

Published in 16th International Conference on Quality of Multimedia Experience (QoMEX), 2024

Explores machine learning-based methods to optimize video encoding parameters for improved quality and energy efficiency.

Recommended citation: Z. Azimi, R. Farahani, V.V. Menon, C. Timmerer, and R. Prodan. (2024). *Towards ML-Driven Video Encoding Parameter Selection for Quality and Energy Optimization.* 16th International Conference on Quality of Multimedia Experience (QoMEX).
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Towards AI-assisted Sustainable Adaptive Video Streaming Systems: Tutorial and Survey

Published in arXiv preprint arXiv:2406.02302, 2024

A comprehensive survey and tutorial on AI-assisted sustainable adaptive video streaming systems.

Recommended citation: R. Farahani, Z. Azimi, C. Timmerer, and R. Prodan. (2024). *Towards AI-assisted Sustainable Adaptive Video Streaming Systems: Tutorial and Survey.* arXiv preprint arXiv:2406.02302.
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Decoding Complexity-Aware Bitrate-Ladder Estimation for Adaptive VVC Streaming

Published in 32nd European Signal Processing Conference (EUSIPCO), 2024

Introduces a decoding complexity-aware approach to improve bitrate ladder estimation for adaptive VVC video streaming.

Recommended citation: Z. Azimi, A. Premkumar, R. Farahani, V.V. Menon, C. Timmerer, and R. Prodan. (2024). *Decoding Complexity-Aware Bitrate-Ladder Estimation for Adaptive VVC Streaming.* 32nd European Signal Processing Conference (EUSIPCO).
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Towards an Energy-Efficient Video Processing Tool with Large Language Models

Published in Proceedings of the 4th Mile-High Video Conference, 2025

Proposes a novel LLM-based video processing tool that enhances energy efficiency in media workflows.

Recommended citation: Z. Azimi, R. Farahani, C. Timmerer, and R. Prodan. (2025). *Towards an Energy-Efficient Video Processing Tool with LLMs.* Proceedings of the 4th Mile-High Video Conference.
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Talk 1 on Relevant Topic in Your Field

Published: March 01, 2012

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Tutorial 1 on Relevant Topic in Your Field

Published: March 01, 2013

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Talk 2 on Relevant Topic in Your Field

Published: February 01, 2014

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Conference Proceeding talk 3 on Relevant Topic in Your Field

Published: March 01, 2014

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Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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