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Computer Vision and Sensing Systems (COVISS) Lab

At COVISS, we are interested in devising methods and systems that use information collected by multidimensional sensors to understand the physical world. These sensors may include traditional cameras, depth sensors, arrays of unidimensional sensors, or combinations thereof. In particular, we are interested in fusing observations obtained at different points in time or space or even with different sensing modalities. In order to keep our scientific contributions relevant, we work in close collaboration with researchers in several other areas, from agriculture to biomedical engineering and health sciences.

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Electric Machines and Power Electronics at Marquette (EMPOWER) Lab

The power end energy systems group at Marquette conducts advanced research in the areas of electrical machines, power electronics and drives. The research covers broad range of applications including, traction, aerospace , and renewable energy among others. The group is funded by various government agencies and industrial partners.

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Electric Machines and Drives (EMDL) Lab

Marquette University’s Electric Machines and Drives Laboratory (EMDL) is a facility located in Olin Engineering, room 511. This lab is supervised by Professor Nabeel A. O. Demerdash who is a Life-Fellow of IEEE. The main research topics pursued in this lab include design, analysis, optimization, and fault diagnostics of electric machines and drive systems.

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GasDay Lab

Marquette’s GasDay Lab does research in system identification, time series signal processing, filtering, mathematical and statistical modeling, data mining, and forecasting, including ensemble (consensus, combining) forecasting. We leverage knowledge from mathematics, statistics, computer science, and economics in addition to traditional electrical and computer engineering fields of controls, signal processing, machine learning, and artificial intelligence. We apply our research in the natural gas distribution and transmission industries.

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Knowledge and Information Discovery (KID) Lab

The Knowledge and Information Discovery (KID) lab focuses on problems at the intersection of machine learning and signal processing. Graduate and undergraduate students work on problems ranging from speech recognition to electricity demand forecasting.

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Machine Learning and Image Processing Lab

At Marquette’s Machine Learning and Image Processing Lab, students do research in image processing, including CT reconstruction, Organ Segmentation, Metal Artifact Reduction, Image Enhancement, Image Classification, Automatic Target Recognition, Moving Object Tracking, and Microscopic Imaging. They leverage knowledge from the state-of-the-art machine learning such as deep learning in addition to traditional statistics and signal processing

Learn more about the Machine Learning and Image Processing Lab.

Marquette Embedded Systems (MESS) Lab

The Marquette Embedded SystemS (MESS) Lab, located in Haggerty Hall, conducts research in the areas of design and design automation for embedded systems, multicore processors, and field programmable gate arrays (FPGAs). The outcomes of this research include hardware implementations, embedded firmware, and software programs as electronic design automation (EDA) tools to support new design methodologies or as optimization algorithms to solve specific optimization problems in these areas. The lab contains modern computers, some of which include 16 core processors and GPU devices (Tesla and Pascal architectures), and development software as well as various electronic equipment such as power sources, oscilloscopes, high accuracy current probes, microscopes, 3D printers, and reflow ovens.

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MEMS and Advanced Microsystems Lab

The MEMS and Advanced Microsystems Laboratory is found in the Department of Electrical and Computer Engineering at Marquette University. The lab conducts advanced microsystem, device fabrication, and materials research to develop state-of-the-art microelectromechanical systems (MEMS), nanoelectromechanical systems (NEMS), and smart system technologies such as: membrane sensors and actuators, phase change materials, micro-electrical contacts and micro-switches, energy harvesting and storage, and micro-grids.

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Microsensor Research Lab

The Clay Lafferty Microsensor Research Laboratory is equipped to support research in the areas of chemical, biological and physical sensors utilizing a variety of technologies and systems. The state-of-the-art facilities utilize a variety of sensor platforms including solid state and acoustic wave sensors, microelectromechanical systems (MEMS) devices, optical waveguide-based sensors and smart sensor systems for both liquid and gas phase monitoring. Optical sensing techniques are employed for complementary chemical identification as well as standalone chemical detection and quantification systems. Highly sensitive magnetic field sensing is also being investigated for various applications including electric battery management systems. The laboratory is involved in designing smart sensor systems relying on advanced sensor signal processing and estimation theory techniques. 

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System Analytics for Communications and Energy (SACE) Lab

The System Analytics for Communications and Energy (SACE) lab focuses on creating advanced probabilistic and data-driven models to enable the prediction of performance of critical cyber-physical infrastructures, such as smart grids. For example, one of the goals of the SACE lab is to advance the fundamental understanding of the vulnerability, reliability and security of smart grids while capturing the interdependencies among the underlying communication network (SCADA), the transmission grid, and the human-computer interactions. The SACE Lab has a dedicated space of approximately 1000 sq. ft. in Engineering Hall, 471. It houses HP Z6 G4 [Intel Zeon Silver 4114 CPU @2.2 GHz (40 CPUs)] workstations for performing both AC and DC power-flow simulation and cascading-failures simulations on power grid test systems (e.g., Polish power grid, IEEE 118, IEEE 300, etc.).

Learn more about the SACE Lab.