Concordia Computational Intelligence Laboratory (CCIL) grew out of the work and research of members of Concordia University's Computer Engineering and Computer Science faculty as well as a number of graduate students and collaborators in a range of other academic disciplines.  The CCIL is situated in the new Engineering and Computer Science building as of 2005.  Though still in its beginnings, CCIL is evolving rapidly as the research areas and teams expand.  Much of the Laboratory's work revolves around Artificial Intelligence and Artificial Life, Pattern Recognition and Image Processing.

Concordia's Artificial Life Group is a discussion and interdisciplinary research group consisting primarily of faculty members from different departments as well as graduate students, although others are welcome to join us. We meet a couple of times each term to discuss aspects of artificial life, which we consider to include genetic algorithms, evolutionary computation, digital life, DNA computing and similar topics. These meetings have led to research collaborations between our members.

Members of the group conduct research in different areas of wireless and optical communications. Their research spans a wide spectrum ranging from the physical to application layer and is of both theoretical and experimental nature. The group has very strong ties with the telecommunications industry. Particular areas of research include: Digital Communications, Information Theory, Channel Coding, Source Coding, MIMO systems, CDMA and 4G systems, Coding and signal processing for data transmission and storage, Smart antennas for wireless applications,  Network Architectures and Media Access Protocols for Wireless Communication Networks, Performance Modeling of Wireless and Wired Communication Networks, Multimedia Communication over the Internet, Optical Networks, MPLS-based networks, Multicasting and Quality of Service, satellite communications.

Research activities include Design and fabrication of array of nano-particles and nano wires for applications in photonic, biomedical and sensing devices, Design and fabrication of MEMS devices; Design, microfabrication, characterization, and physical modeling of active microwave devices in III-Nitride semiconductor family; Theory, modeling, analysis, and characterization of novel electronic materials, x-ray imaging detectors, photodetectors, thin-film and non-structured photovoltaic solar cells, and III-V nitride devices.
 

Research Labs: 
MEMS Laboratory:   Investigations on fundamental issues related to Micro Structures, Optical Devices, Silicon Anisotropic Etching.

Nanodevice Laboratory: Design, Fabrication and Characterization of Nanoscale electron devices, Nanophotonics Sensors.

Reliable Electron Devices Laboratory: Design, microfabrication, characterization, and physical modeling of active microwave devices.

Material and Device Characterization Laboratory:  Characterizations of carrier transport, electrical and optical properties of electronic and optoelectronic materials and devices.

The VLSI research group is engaged in the research of very large scale integrated circuits. The research activities are in the areas of design and implementation of analog-mixed signal circuits, integrated sensors, and VLSI systems for signal processing, communications, robotics and other applications.

Research activities of photonics research group cover:  modeling and characterization of semiconductor materials and electronic devices, optical sensors for communication and health related applications, fiber-optic communication systems, microwave photonics, fiber-optic based sources and quantum dot semiconductors, Investigation of radio over fiber systems, and fiber Raman amplifiers.

Members of the group conduct research in different areas including: Software engineering, Real-time embedded software systems, Formal methods, Modeling, Validation and testing, Communication protocol engineering, Multimedia communication architectures and protocols, Service engineering, Evolutionary computation for pattern recognition and image processing, Machine learning for engineering applications.

The group aims to contribute to multi-disciplinary research activities that target advances in the development of control systems and robotics technologies with applications to a wide range of industrial systems. Our objective is to organically fuse and integrate theoretical concepts, computational methods, and engineering design principles through multi-disciplinary research initiatives and cooperation.