Electrical Engineering & Computer Science

The lab focuses on developing future power and energy systems. The research areas include renewable energy integration, rural power grid development, demand-side management, smart meter data analysis, and electric arc protection. The mission is to develop a safe, smart, and sustainable (SSS) power and energy system for the future.

The lab conducts research at the forefront of machine learning for multi-modal spatiotemporal data. In particular, our research investigates advanced algorithms for: fusing multi-modal data along different spatiotemporal time-scales; dimensionality reduction, and pattern classification of multi-modal data; understanding multi-modal relationships for graph representation learning; predicting future events through multi-modal forecasting methods; exploring data augmentation and graph expansion from multi-modal graph embeddings.

The lab is equipped with 3D printers, software-defined radios (SDRs), vector network analyzers (VNAs, up to 67 GHz), and a walkable anechoic chamber with a dimension of W = 11’, H = 9’6”, and L = 21’.

The research focuses on developing microwave sensing and direction-finding systems for civil and military applications, which can be applied to infrastructure inspections, rescue missions, electronic support, and electronic warfare.

The lab is at the forefront of investigating innovative approaches for designing, implementing, and verifying mobile robots and real-time/embedded systems.

Developed systems/frameworks play pivotal roles in safety-critical applications, clean and smart energy systems, precision agriculture, safe mining operations, applications within the field of biomedical engineering, and ensuring security in cyber-physical systems.

The research extends to virtual reality, augmented reality, and user interfaces. Cybersickness is a particular focus of the lab but also includes XR usability and development.