Electrical Engineering & Computer Science

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The Department of Electrical Engineering & Computer Science blends theory and practical application to advance innovation in computing, communications, and systems engineering. Students work with faculty on research in areas such as embedded systems, power electronics, software engineering, and data systems. With access to state-of-the-art labs and collaborative projects, graduates are well prepared for technology-driven careers in industry and academia.

Mines Professor Named in World’s Top 2%

Dr. Nirmalya Thakur, assistant professor of Electrical Engineering and Computer Science, has been named among the world’s top 2% of scientists for his research in artificial intelligence and human behavior.

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Ask an EECS Student

Have questions about what it’s really like to study Electrical Engineering, Computer Engineering, Computer Science, or Data Science & Engineering at South Dakota Mines? Send an email to one of our EECS student ambassadors! They’re happy to share their experiences, talk about classes, campus life, and anything else you’re curious about.

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Research Labs & Centers

Work with our renowned faculty and collaborate on groundbreaking projects that address real-world challenges. The hands-on experience and expertise you will acquire here will not only contribute to your academic growth but also prepare you for successful careers in academia, industry, or government agencies.
The SGERL 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 MLIS 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.
Virtual Reality Lab
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.

 

Have more questions?

Department Head:
Dr. Jeffrey McGough