Projets
Through our drive-by air pollution sensing research project, we are enabling cost-efficient collection of granular spatiotemporal pollution data through drive-by sensing.
Through this interactive machine translation tool, we hope to not only provide help for human-aided translations for underserved languages but also for certain use cases for highly resourced languages where a human in the loop can help aid translation activities.
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When students are stuck with a math problem, searching online for help can be challenging. Typing complex math problems also poses a significant barrier. We look to reimagine input modalities through camera to make search easily accessible on mobile devices…
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The goal of Project LITMUS is to discover strategies to evaluate massive multilingual models and also suggest data collection and training strategies to improve the performance of these models.
Our goal is to provide a simple and easy way to (i) remotely measure and observe the health of a sensor, and (ii) empower users to specify their acceptable data quality threshold driven by the application requirements.
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Blockene is a new blockchain architecture that reduces resource usage at member nodes by orders of magnitude, requiring only a smartphone to participate in block validation and consensus. Despite being lightweight, Blockene provides high throughput and scales to millions of…
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In the iBox project, we focus on the goal of «learning the network» to recreate real-world, end-to-end network path behaviour, based on input-output packet trace telemetry.
Aggify is a technique for optimizing loops over query results that overcomes these overheads, completely eliminating the loop by rewriting the query to use this generated aggregate.
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Patient-centred care and good communication between patients and healthcare providers has been shown to improve medical adherence. However, it is costly and difficult to provide, especially in Global Health settings where patient volumes are high and costs must be kept…