- Facilities Listing
- Engineering Room Resources (Faculty & Staff)
- Laboratory Safety
- Equipment Policies
- (414) 288-6000
1637 W. Wisconsin Ave.
Milwaukee, WI 53233
Olin Engineering Center
1515 W. Wisconsin Ave.
Milwaukee, WI 53233
- David Newman
Director of Engineering Operations
PROBLEM WITH THIS WEBPAGE?
Report an accessibility problem
To report another problem, please contact email@example.com.
Haggerty Hall & Olin Engineering Center
First built in 1941, Haggerty Hall features a first-floor study area, the Engineering Student Success Center, remodled classrooms, modern materials labs, computer labs and several other teaching and research facilities. Connected to Haggerty Hall, the Olin Engineering Center is a four-level facility with engineering labs and offices.
Deburring and Surface Finishing Research Lab
Internal Combustion Engines
Engineering Student Success Center (Haggerty Hall, 139)
An extension of the Engineering Academic Advising Center, the Engineering Student Success Center is a transformative learning environment where students are supported and challenged to pursue academic excellence, share knowledge, and develop interpersonal skills.
Advanced Systems and Assembly Manufacturing Lab (Haggerty Hall)
Medical Imaging Lab (Haggerty Hall)
*No research laboratories on the second floor.
Orthopaedic and Rehabilitation Engineering Center (Olin Engineering Center, 323)
The Orthopaedic & Rehabilitation Engineering Center (OREC) is designed to promote and encourage significant advances in clinical research through coordinated endeavors between Marquette University and the Medical College of Wisconsin. These opportunities are afforded to faculty and students at Marquette University and to faculty, fellows, and residents in the Departments of Orthopaedic Surgery, and Physical Medicine and Rehabilitation at the Medical College of Wisconsin. OREC builds upon prior successful collaborations in the fields of orthopaedic biomechanics, biomaterials, rehabilitation engineering, and human motion analysis.
Electric Machines and Drives Lab (Haggerty Hall, 379)
The Electric Machines and Drives Laboratory is a facility for research on modern electric machinery in adjustable speed drives and electromechanical systems in general, including associated electromagnetic and power electronic studies and simulation model developments.
Biohazard Level II Lab (Haggerty Hall, 410)
The Biohazard Level II Lab focuses on the design and assessment of more sustainable water and wastewater treatment technologies that are able to simultaneously mitigate the risks posed by microbial and chemical contaiminants.
Hydraulics Lab (Haggerty Hall, 430)
Research in the Hydraulics Lab spans a breadth of areas in hydrology and water resources engineering. The current focus of research in the lab focuses on drone remote sensing, flood-frequency analysis and watershed management policy.
Waves and Signals Lab (Haggerty Hall, 440)
Marquette Embedded Systems Lab (Haggerty Hall, 451)
The Marquette Embedded Systems Lab researchers focus on machine learning based energy optimization in multicore processors and datacenters, uncertainty modeling and design methods for embedded systems, energy and power simulation, field programmavle gate arrays, drone design and power distribution network configuration.
Computational Vision and Sensing Systems Lab (Haggerty Hall, 450)
At COVISS, researchers 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, they are interested in fusing observations obtained at different points in time or space or even with different sensing modalities.
GasDay Lab (Olin Engineering Center, 534)
At Marquette’s GasDay Lab, students do research in system identification, time series signal processing, filtering, mathematical and statistical modeling, data mining, and forecasting, including ensemble (consensus, combining) forecasting. They 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.