Current and Past I-Corps Teams
PI: Prof. Bing Xu
iPSCs can be differentiated into different cell types, having enormous potential for cell therapy, but the risk of tumor formation from undifferentiated cells (cells that stay the same) remains a major obstacle. This project will develop a molecular method to eliminate undifferentiated iPSCs.
Epilepsy Treatment Project
PI: Associate Prof. Suzanne Paradis
Epilepsy is a neurological disorder that affects 3.4 million Americans with an associated direct cost of to the US of $28 billion per year. Underlying seizures are due to local imbalances between excitatory and inhibitory connections within neuronal circuits causing abnormal hyperexcitability within specific areas of the brain. This novel therapeutic intervention involves resetting such imbalances.
PI: Assistant Prof. Rebecca Gieseking
Hydrogen is a zero-carbon fuel that can reduce humanity’s greenhouse gas emissions for a sustainable future. However, most hydrogen is currently produced from fossil fuels because it is difficult and energy-intensive to split water into hydrogen and oxygen. State-of-the-art platinum catalysts are expensive and can be poisoned by contaminants. This project promises to harness solar energy, efficiently producing hydrogen from water at a lower cost by reducing the amount of expensive metal required.
PI: Dr. Christopher Doona
There is a critical need for self-decontaminating, self-deodorizing, self-disinfecting, and/or self-cleaning surfaces, particularly for textiles used in individual protective garments, especially so during the current global pandemic.
This invention uses a novel chemical method to functionalize various surfaces with a stimuli-responsive hydrogel polymer that responds to external stimuli by taking up, storing, and controllably releasing gaseous or aqueous chlorine dioxide (ClO2) for the purposes of inactivating harmful microorganisms, neutralizing odors, and eliminating pathogenic virus.
PI: Associate Prof. Olga Papaemmanouil
OptMark is a toolkit that quantifies the quality of a query optimizer, independently of any other component of the database management system. This toolkit is able to accomplish this by two ways: first, by decoupling the quality of an optimizer from the quality of its underlying execution engine; and second, by evaluating independently both the effectiveness of an optimizer and its efficacy.
OptMark’s approach for evaluating the effectiveness of an optimizer involves reporting the three effectiveness metrics absolute performance factor, relative performance factor, and optimality frequency. OptMark is able to report the relative and absolute performance factor of a given profiling query by generating and executing a sample of plans compared with the optimizer chosen plans.