The tiny Machine Learning and Embedded Computing Lab (tML-EC) focuses on developing energy-efficient AI and computing solutions for embedded systems, IoT, and resource-constrained devices. Our research spans malware detection for embedded processors, machine learning for edge devices, efficient hardware design, and quantum hyperdimensional computing (HDC). We aim to bridge the gap between machine learning (ML) algorithms and practical deployment on low-power systems.