Analog and Mixed Signal Research Lab
The AMS lab is involved in the hardware design of adaptive, trainable neural networks to be used in non-invasive fault detection programs in production lines or detection of various tumour shapes in the human body. This includes expertise in designing and safeguarding hardware chips in automobiles and cell phones against information-stealing; facilitates testing and characterization, specifically, full speed time / frequency domain testing and device characterization and modeling; creating designs with full CAD support which includes schematic capture, simulation, layout, verification, and process simulation when necessary and access to Cadences and Synopsys tools for research and teaching activities.

Centre for Hybrid Automotive Research and Green Energy (CHARGE)
UWindsor's Centre for Hybrid Automotive Research and Green Energy — under the Canada Research Chair Program in Electrified Transportation Systems — advances knowledge, technology and expertise through world-class transformative and disruptive research and innovation in the area of electric vehicle science and engineering. In an effort to produce far-reaching research solutions, the CHARGE Labs focuses on major research areas such as electric machine design and testing, machine drives and control, electric vehicle simulation and inductive and conductive charging.

electrical MIcro & Nano Devices and Sensors Research Lab (e-Minds Centre)
e-Minds is leading academic and industry cross-functional projects to introduce and implement next-generation micromachined smart sensor systems in a wide range of fields that make abundant use of sensors and transducers such as medical, environmental sciences, agriculture, and personal electronics. This research lab focuses on creating opportunities for the development of revolutionary new sensors that are small enough for integration into microelectronic systems and instrumentation, more easily deployable in a multitude of sensing applications and capable of sensing unique aspects of the environment. 

The Intelligent Signal Processing Laboratory (ISPLab) pursues frontier and original research in the design/theory, realization, and applications of digital filters, deep neural networks, deep fuzzy-neural networks, discrete Gabor transform, and optimization algorithms for the analysis, modeling, and processing of signals and smart data for building real-time intelligent signal processing systems.

​Microelectromechanical Systems (MEMS) Lab
The Microelectromechanical Systems (MEMS) Lab is focused in the research of MEMS electrostatic sensors and actuators, capacitive micro-machined ultrasonic transducers, planar and non-planar beamforming acoustical arrays, FMCW short and long range radars, ultra-wideband radars, sonoluminescence based MEMS transducer, MEMS multi-spectral multi-functional transducers, 3-D packaging and integration and MEMS micro-power generator.

Radio Frequency Identification (RFID) and Smart Sensors Research Centre
The RFID Research Centre focuses on the design and testing of RFID and smart sensors. The centre has the expertise to collaborate with industry in various fields including: Automation and identification; Smart wireless sensors; Security and tracking; Supply chain management; Transport, warehousing and logistics applications; Industrial engineering; Radio Frequency Identification (RFID) and Wireless charging technology.

Research Centre for Integrated Microsystems (RCIM)
The Research Centre for Integrated Microsystems (RCIM) is located within the Department of Electrical and Computer Engineering in the Faculty of Engineering at the University of Windsor. The RCIM group is focused on carrying out leading edge research, developing collaborative partnerships and educating highly qualified graduate students in the areas of Microelectronics and Microeletromechanical systems [MEMS].

Wireless Communications and Information Processing (WiCIP) Research Laboratory
The WiCIP Research Lab Focuses on three major research areas of wireless and computer networking: (1) Internet of Things (IoT), Machine to Machine (M2M), Sensor Networks, and Ultra-Wide Band precise indoor positioning; (2) Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communications, connected vehicles; (3) Wireless networks, mobile networks, and network security.