Machine Learning-centric, Energy-Optimized Wireless Systems - Spring 2021 Research Seminar
Paul G. Allen School via YouTube
Learn Backend Development Part-Time, Online
AI Engineer - Learn how to integrate AI into software applications
Overview
Google, IBM & Meta Certificates – 40% Off
One plan covers every Professional Certificate on Coursera.
Unlock All Certificates
Explore cutting-edge approaches to energy-optimized, machine learning-centric artificial intelligence of things (AIoT) systems in this research seminar. Delve into the challenges of optimized system integration for AIoT devices with strict energy, power, cost, and size constraints. Learn about cross-layer optimization techniques that span deep learning algorithms, wireless communication, digital signal processing, and VLSI hardware architecture. Discover novel hardware-friendly algorithms and VLSI systems designed for ultra-low power and energy-aware wireless IoT applications. Gain insights from Hun-Seok Kim, an assistant professor at the University of Michigan, Ann Arbor, as he shares his expertise in system analysis, algorithm development, and efficient VLSI architectures for various technological domains.
Syllabus
Machine Learning-centric, Energy-Optimized Wireless Systems (Hun-Seok Kim, U of Michigan, Ann Arbor)
Taught by
Paul G. Allen School