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healthcare application needs to analyze sensitive patient data across distributed nodes. Researchers and students can explore privacy-preserving algorithms and technologies like federated learning and zero
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Seizure prediction algorithms will be developed using the one-of-a-kind ultra-long-term human intracranial EEG dataset obtained from the Neurovista Corporation clinical trial of their Seizure
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. The project will focus on automated distributional shift detection and monitoring, invariant and distributionally robust representation learning algorithms, and deployment-time calibration with uncertainty
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substantial research project, GPA 80%+ from a reputed university Refereed publications including journal or conference of high repute Desirable Background in Algorithms and Data Structures
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This project will investigate and develop the ways in which AI algorithms and practices can be made transparent and explainable for use in law enforcement and judicial applications The Faculty
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PETs: This aspect requires a significant math background as it involves exploiting various mathematical results to develop a concrete cryptographic algorithm. Although desired, background in advanced
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traditional and advanced optimization techniques, including analytical models, simulation-based approaches, and data-driven algorithms. The research also considers practical constraints such as cost, process
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the different actors' beliefs and intentions. We will study the properties of such explanations, present algorithms for automatically computing them as well as extensions to existing frameworks and evaluate
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the construction of PRS and enhance disease prediction. Students will gain experience in: Statistical genetics and GWAS methodology Machine learning approaches for high-dimensional data Algorithm development and
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broad range of topics: from model-predictive building control and community battery integration to wind farm optimisation and multi-decade investment planning, we support clever algorithms and data