The Tiny Machine Learning (TinyML) Research Group is at the intersection of applied machine learning, embedded systems development, signal processing, and IoT. Modern microcontrollers are rather energy-efficient and allows for efficient data acquisition, signal processing and processing of machine learning models. Our project work includes design and application of classification, regression and anomaly detection in IoT-like devices. It also involves the design of Neural Network Accelerators that utilize both Artificial Neural Networks and Spiking Neural Networks. These efforts are aimed at augmenting the functionality and capability of low-power, intelligent devices.