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Field
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focuses on developing the first-ever closed-loop cardiopulmonary resuscitation (CPR) feedback device. The device uses non-invasive sensors to measure blood oxygenation in the brain and tells the CPR
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features from multiple imaging modalities (CT, MRI, PET, ultrasound); (2) design advanced AI algorithms for early-stage cancer detection with high sensitivity and specificity; (3) create user-centric AI co
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will also collaborate with a postdoctoral researcher and another PhD candidate on creating new GPU-enabled pharmacophore searching algorithms. Prospective validation will be achieved by predicting
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: the physical layer of telecommunications, technologies related to industrial and defense applications (optical sensors, lasers, instrumentation for photonics), photovoltaics and hydrogen production. Research
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on practical feedback linearization with limited or imperfect models. Learning-enabled control dynamics Embedding optimization and learning algorithms (e.g., SGD, Bayesian updates) into control design and
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network integration for emerging low-energy opto-electronic AI systems and beyond. The challenge: Machine learning and neural networks are super-charging the complexity of problems that computer algorithms
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Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 2 months ago
. Lab Research: • AI-Driven Algorithms & Software: Develop deep leering/machine learning/statistical based algorithms to elucidate lncRNAs, fusion transcripts, RNA modifications, and circular RNAs in
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significantly. Unfortunately, it is challenging to measure groundwater fluxes in the field. A new iFlux sensor prototype to measure real-time groundwater fluxes in the field is a promising technique, but is a
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of algorithmic systems. The research will investigate how clinicians interact with automated and machine learning–based decision-support systems, with a particular focus on cognitive workload, trust, situational