Research in EECS
The departmental research areas include the following. Click on any title for more details.
- - research areas include electromagnetics, antennas, microwave, and wireless communications. Applications address current academic, industry, and society needs. Examples include the design of antennas, antenna arrays, and microwave RF devices for communication and sensing applications.
- - an interdisciplinary research area that is applied to areas such as VLSI design automation, cheminformatics, computational materials, and cyber-physical systems.
- - research includes areas within STEM education and K-12 education.
- - is focused on both fundamental and applied research in the interrelated fields of conventional electric power systems and electric machinery, renewable energy and distributed generation, energy economics and policy issues, power quality, power electronics and drives. The overall scope of research encompasses a broad spectrum of electrical energy applications including investor-owned utilities, rural electric associations, manufacturing facilities, regulatory agencies, and consulting engineering firms.
- - research is focused on compiler-based code and data transformation, memory optimization for both multi-core and many-core processors, speculative parallelization, approximate computation and GPU-based acceleration of Big Data applications (such as graph processing and machine learning algorithms).
- - an interdisciplinary area that bridges research and application of methodology from robotics, machine vision, machine learning, human-computer interaction, human factors, and cognitive science. Students will learn about fundamental research in human-centered robotics, as well as develop computational models for robotic perception, internal representation, robotic learning, human-robot interaction, and robot cognition for decision making.
- - is an interdisciplinary research area that encompasses the fields of control systems, communications, signal and image processing, compressive sensing, robotics, and mechatronics. Focus areas include intelligent and learning control systems, fault detection and system identification, computer vision and pattern recognition, sensor development, mobile manipulation and autonomous systems. Applications can be found in renewable energy and power systems, materials processing, sensor and control networks, bio-engineering, intelligent structures, and geosystems.
- - includes research in developing mathematical foundations and algorithm design needed for computers to learn. Focus areas include fundamental research in machine learning and numerical methods, as well as developing novel algorithms for bioinformatics, data mining, computer vision, biomedical image analysis, parallel computing, natural language processing, and data privacy.
- - research includes mobile networks, sensor networks, pervasive computing, and wireless networking. Focus areas include credible network simulation, cyber-physical systems, game theoretic algorithm design, middleware, and mobile social applications. Interdisciplinary research also exists, mainly in the use of wireless sensor networks for environmental monitoring and development of energy efficient buildings.