Title: Special Topics in Circuits and Embedded Systems: Artificial Intelligence and Machine Learning for IoT and HCPS
Description: Focus on emerging artificial intelligence and machine learning (ML) methods for sensing and control in Internet of Things and human-cyber-physical systems. Such systems--found in many application domains such as mobile health, smart-built environments, intelligent transportation, etc.--are characterized by multimodal time-series data, low-latency requirements, resource constraints, complex spatiotemporal dynamics, and computing distributed across edge-cloud. Through lectures, paper presentations, and application-inspired project, introduction to topics such as deep-learning methods for processing time-series and multimodal data; architectures that combine data-driven and mechanistic models; sim2real challenges in deep-reinforcement-learning-based control of physical systems; adaptation to dynamics; and systems issues, such as implementations in resource-constrained and distributed settings. Designed for students familiar with basic ML methods including deep neural networks, one ML software platforms, and software development.
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