{"id":411,"date":"2022-01-28T08:37:26","date_gmt":"2022-01-28T08:37:26","guid":{"rendered":"https:\/\/mcsoc-forum.org\/site\/?page_id=411"},"modified":"2026-02-11T05:02:53","modified_gmt":"2026-02-11T05:02:53","slug":"special-track-embedded-machine-learning-and-data-analytics","status":"publish","type":"page","link":"https:\/\/mcsoc-forum.org\/site\/index.php\/special-track-embedded-machine-learning-and-data-analytics\/","title":{"rendered":"Special Track: Embedded Machine Learning and Data Analytics"},"content":{"rendered":"\n
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Track Chairs<\/h2>\n
\n
\"Prof.\n

Prof. Kasem Khalil<\/a><\/strong>
University of Mississippi, USA<\/span><\/p>\n<\/div>\n

\"Prof.\n

Prof. Qinglin Yang<\/a><\/strong>
Guangzhou University, China<\/span><\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

The Embedded Machine Learning and Data Analytics track explores the innovative integration of machine learning algorithms and data analytics techniques within embedded systems. This track aims to highlight the transformative potential of deploying intelligent analytics directly on edge devices, enabling real-time decision-making and enhancing system performance. Participants will delve into state-of-the-art research, practical implementations, and emerging trends in the field, covering applications such as IoT, smart sensors, healthcare, and autonomous systems. Join us to uncover the future of embedded intelligence and its impact on various industries.

Topic of Interests:<\/strong><\/p>\n\n\n\n