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个人简介
We analyze complex, high-dimensional data sources in a variety of application domains. We develop scalable algorithms with theoretical performance guarantees utilizing physics-based sensor models. Towards that end we combine elements of Bayesian inference, information theory, optimization, and machine learning in our research. Formulating problems in this context has led to interesting questions in probabilistic inference, information planning, scene understanding, and Bayesian structural inference (to name a few). Applications expose our ideas to the challenges and complexity of real world data and environments. Examples include multi-modal data fusion, distributed inference under resource constraints, multi-object tracking, and accelerated materials design. I am interested in all aspects of the process of going from sensing to information to understanding to action.
研究兴趣
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Felipe Oviedo, David S. Hayden, Thomas Heumeuller,Jonas Wortmann,Jose Dario Perea, Richa Naik,Hansong Xue, Juan Lavista,John Fisher III,Christoph J Brabec,Tonio Buonassisi
crossref(2023)
Nature Reviews Materialsno. 4 (2023): 241-260
arxiv(2022)
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arXiv (Cornell University) (2021)
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