Explores challenges and solutions in resource-aware machine learning for IoT devices, including power analysis, classification, and dataset evaluation.
Explores high-performance OPF solvers, addressing challenges in power system optimization and showcasing significant speed-ups and memory-efficient approaches.
Covers the general logistics, course rationale, prerequisites, organization, credits, workload, grading, and course content, including swarm intelligence, foraging strategies, and collective phenomena.
Explores challenges in the IoT era, resource-constrained nodes, complex algorithms, security solutions, and blockchain adoption for secure data storage.
