CPS: Frontier: Collaborative Research: Data-Driven Cyberphysical Systems
CPS: Frontier: Collaborative Research: Data-Driven Cyberphysical Systems
批准号:
1645832
负责人:
Yisong Yue
金额:
$28.12万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-10-01 至 2021-09-30
中文摘要
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英文摘要
Data-driven cyber-physical systems are ubiquitous in many sectors including manufacturing, automotive, transportation, utilities and health care. This project develops the theory, methods and tools necessary to answer the central question "how can we, in a data-rich world, design and operate cyber-physical systems differently?" The resulting data-driven techniques will transform the design and operation process into one in which data and models - and human designers and operators - continuously and fluently interact. This integrated view promises capabilities beyond its parts. Explicitly integrating data will lead to more efficient decision-making and help reduce the gap from model-based design to system deployment. Furthermore, it will blend design- and run-time tasks, and help develop cyber-physical systems not only for their initial deployment but also for their lifetime.While proposed theory, methods and tools will cut across the spectrum of cyber-physical systems, the project focuses on their implications in the emerging application of additive manufacturing. Even though a substantial amount of engineering time is spent, additive manufacturing processes often fail to produce acceptable geometric, material or electro-mechanical properties. Currently, there is no mechanism for predicting and correcting these systematic, repetitive errors nor to adapt the design process to encompass the peculiarities of this manufacturing style. A data-driven cyber-physical systems perspective has the potential to overcome these challenges in additive manufacturing. The project's education plan focuses on the already much needed transformation of the undergraduate and graduate curricula to train engineers and computer scientists who will create the next-generation of cyber-physical with a data-driven mindset. The team will reach out to K-12 students and educators through a range of activities, and to undergraduate students from underrepresented groups through year-long research projects. All educational material generated by the project will be shared publicly.
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DOI:
--
发表时间:
2019-07
期刊:
影响因子:
--
作者:
[Abhinav Verma;Hoang Minh Le;Yisong Yue;Swarat Chaudhuri]
通讯作者:
Abhinav Verma;Hoang Minh Le;Yisong Yue;Swarat Chaudhuri
Teaching Multiple Concepts to a Forgetful Learner
向健忘的学习者教授多种概念
DOI:
--
发表时间:
2019
期刊:
Advances in neural information processing systems
影响因子:
--
作者:
[Hunziker, A]
通讯作者:
Hunziker, A
DOI:
--
发表时间:
2019-07
期刊:
ArXiv
影响因子:
--
作者:
[Jialin Song;Ravi Lanka;Yisong Yue;M. Ono]
通讯作者:
Jialin Song;Ravi Lanka;Yisong Yue;M. Ono
Learning to make decisions via submodular regularization
学习通过子模正则化做出决策
DOI:
--
发表时间:
2020
期刊:
International Conference on Learning Representations
影响因子:
--
作者:
[Alieva, A., Aceves, A., Song, J., Mayo, S., Yue, Y., Chen, Y.]
通讯作者:
Chen, Y.
Minimax Model Learning
极小极大模型学习
DOI:
--
发表时间:
2021
期刊:
24TH INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS (AISTATS
影响因子:
--
作者:
[Voloshin, C, Jiang, N, Yue, YS]
通讯作者:
Yue, YS
共 8 条
Expeditions: Collaborative Research: Understanding the World Through Code
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批准号:1918865
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项目类别:Continuing Grant
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资助金额:$80.0万
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财政年份:2020
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负责人:Yisong Yue
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依托单位:
海外基金