Dr. Liang-Liang Xie
Energy Efficient Communication for Wireless Sensor Networks
 
Wireless sensor networking is an emerging technology that has a wide range of potential applications including environment and habitat monitoring, as well as traffic control. These networks normally consist of a large number of distributed sensor nodes, each operating on a battery. In many applications it is difficult to change or  recharge batteries for these nodes. Prolonging the network lifetime by efficiently using battery energy is a critical issue in the operation of wireless sensor networks. Dr. Xie and his research team will develop energy-efficient wireless communication schemes for sensor networks.

Dr. Kaan Erkorkmaz
Virtual Prototyping and Control for High-Tech Manufacturing
 
Ultra-precise motion delivery is a technology that is crucial in high-tech manufacturing sectors. The ability to fabricate or assemble parts within micron to nanometer level tolerances at higher speeds will lead to higher productivity rates, lower costs, and better product quality, all of which benefit the Ontario economy. Dr. Erkorkmaz and his research team are working to develop new ultra-precision motion delivery technologies for high-tech manufacturing applications. New machine concepts, virtual prototyping techniques, and computer control theory will be investigated.  

Dr. Myra Annette Fernandes
Memory and Brain Changes Associated with Aging
 
Many older adults in Ontario report concerns regarding memory loss.  Dr. Fernandes and her team will develop a model of how memory works in young adulthood, how it breaks down as we age, and how senior citizens cope with multiple stimuli in today’s fast-paced environments. Her research will identify how memory deficits associated with normal aging can be lessened, or even improved. Dr. Fernandes and her team will use neuroimaging, and cutting-edge techniques in the analysis of network patterns of brain activation.

Dr. Joseph Veilleux Emerson
Assessing and Improving Quantum Information Processing Devices
 
Quantum mechanics describes the novel ways in which energy and matter can interact at very small scales, for example, in atomic and sub-atomic systems. Quantum information science is based on the discovery that quantum mechanical effects in small scale systems can revolutionize information technology, leading, in particular, to quantum computation and quantum communication devices which can vastly outperform their conventional counterparts.  Existing small-scale systems are very sensitive to noise and do not perform reliably. Dr. Emerson and his research team will develop methods for assessing and improving the performance of quantum information devices in the presence of noise, with the long-term goal of making commercially viable  quantum information processors a reality.

Dr. John Chun-Han Lin
Improving our Understanding of Ontario’s Climate
 
Climate change is taking place and becoming more pronounced in the higher latitudes, within which Ontario’s borders are found. As a province with a large number of farms, Ontario critically needs accurate predictions of future climate conditions to help resource managers and policy makers better manage risks arising from climate change. Dr. Lin and his research team will work to improve the understanding of the current-day climate conditions with observations and cutting-edge computer models, and enhance Ontario’s capability to predict future climate conditions.

Dr. Pascal Poupart
Understanding Rich Sensor Data
 
The proliferation of affordable sensors such as video cameras, microphones, sonars, accelerometers, and heat/temperature/pressure sensors, creates an opportunity to design better processing systems such as in health care delivery and business. However, the information provided by those sensors is often difficult to use since it consists of a stream of numbers that are often noisy and have no obvious interpretation. Dr. Pascal Poupart and his team will develop new algorithms to combine sensor processing with high-level decision-making.

Dr. Ihab Francis Ilyas
Effective Retrieval and Cleaning of Uncertain Databases
 
Data integration from multiple sources, object tracking, health informatics applications and sensor networks generate data that involve missing values, duplications or inconsistency. Dr. Ihab Ilyas and his research team will seek to enable users and applications to efficiently handle uncertain data sets by specifying quality requirements that will be used to guide the exploration, cleaning and processing of the underlying data. Their research will have a significant impact on a large class of emerging computer applications, and will allow efficient handling of large volumes of non-traditional data.

Dr. Karim Sallaudin Karim
Smart Pixels for Biomedical Imaging Applications
 
Active-matrix flat-panel imagers comprise the majority of large hospital-grade digital imagers today and are used in chest and breast x-ray imaging. Dr. Karim Karim's team will develop large area digital imagers based on intelligent pixel technology. The improvements that result from using intelligent pixels will help enable 3D imaging, mechanically flexible imagers and highly sensitive optical imagers in the ultraviolet region. These new technologies will usher in a new generation of large area digital imagers for medical imaging, biometric devices for security, and devices for pathogen detection in agriculture.

Dr. William Shelbourne Epling
Reducing Vehicle Emissions
 
Significantly improved vehicle fuel economy can be realized with known, slight modifications to today’s engines. Reducing certain emissions in the exhaust, however, is impossible with today’s catalytic converters. Dr. William Epling and his research team will focus on developing advanced catalyst components for the reduction of these emissions in the more fuel-efficient engines. New catalyst chemistry will be used to improve emissions control performance. Dr. Epling's project will result in improved air quality in Ontario via decreased vehicle emissions, which for the first time would also include carbon dioxide.

Dr. Sukhvinder S. Obhi
Spatial Processing for Action Planning
 
Dr. Obhi's research team will work to understand how spatial information is represented in the brain. Representations of targets, such as a coffee cup, can be in relation to the body, egocentric, or other visible objects, allocentric. Most research has focussed on egocentric representations and little is known about how these are combined with allocentric representations. Using experiments where participants make targeted pointing movements in the presence or absence of non-target objects, the team will explain how these representational schemes are used to guide actions. Further experiments will highlight the neural systems underlying these processes.