Conference: Women in Scientific Computing on Complex Physical and Biological Systems
Conference: Women in Scientific Computing on Complex Physical and Biological Systems
批准号:
2212165
负责人:
Chunmei Wang
金额:
$2.74万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-08-15 至 2023-07-31
中文摘要
研讨会“女性参与复杂物理和生物系统的科学计算”将于2022年10月24日星期一至10月26日星期三在佛罗里达州盖恩斯维尔的佛罗里达大学校园举行。研讨会将汇集来自计算数学、生命科学、计算机科学和工程学各个领域的顶尖专家,积极讨论复杂物理和生物系统的科学计算的最新发展,以及在气候变化、清洁能源和生物技术方面的应用,并推动这些快速发展领域的最新发展。研讨会将提供一个跨学科的论坛,促进复杂物理和生物系统的科学计算研究,促进新的数学和计算方法迅速传播到生命科学、计算机科学和工程学,并激励更多的研究人员在这些重要领域工作。研讨会将包括演讲、海报、小组讨论、小组讨论和辅导课程,这些活动将促进思想的深入交流、促进富有成效的互动、确定挑战、促进跨学科合作和发起联合研究项目。该奖项支持研究人员和研究生参加,优先考虑女性研究人员、研究生、博士后学者、早期职业研究人员、少数族裔研究人员和没有其他联邦资助的研究人员。科学计算是一种计算工具、技术和理论的组合,用于在计算机的帮助下解决科学和工程中的实际应用中产生的数学模型。计算数学不仅是数学在解决具有挑战性的现实世界问题上的应用,而且是从这种应用中发现新的数学理论。数学建模和模拟形成了一种预测方法,补充了真实实验,成为新发现不可或缺的力量。仿真性能不仅依赖于计算能力,还依赖于由偏微分方程建模的底层复杂系统的算法效率和可靠性。设计健壮和高效的算法对于描述科学和工程中的许多现象至关重要。生命科学是一个智力丰富的领域,通过对生物学和数学的深入理解之间的协同作用,这一领域得到了显着的进步。然而,生物学家被大量的实验数据淹没了。需要新的数据管理方法和量化理论来解释他们的观察结果并将其与背景联系起来。近年来,与生命科学中的问题相关的科学计算中出现了各种挑战,例如开发用于无序检测的预测模型、特征降维。这些问题和许多其他悬而未决的问题将在参加研讨会的不同科学家群体中进行讨论。这一奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The workshop "Women in Scientific Computing on Complex Physical and Biological Systems'' will be held on the campus of the University of Florida (UF) in Gainesville, FL from Monday October 24 to Wednesday October 26, 2022. The workshop will bring together leading experts from various areas of computational mathematics, life science, computer science, and engineering to vigorously discuss recent developments in scientific computing on complex physical and biological systems with applications to climate change, clean energy, and biotechnology as well as to advance the state-of-the-art developments in these rapidly developing fields. The workshop will provide a cross-disciplinary forum for catalyzing the research in scientific computing on complex physical and biological systems, facilitating rapid diffusion of new mathematical and computational methods into life science, computer science, and engineering, and stimulating more researchers to work in these important areas. The workshop will consist of presentations, posters, panel discussions, group discussions and tutorial sessions which will stimulate an intensive exchange of ideas, foster fruitful interactions, identify challenges, promote interdisciplinary collaborations and initiate joint research projects. This award supports the attendance of both researchers and graduate students, with priorities given to female researchers, graduate students, postdoctoral scholars, early career researchers, minority researchers and researchers who do not have other federal support. Scientific computing is a combination of computing tools, techniques, and theories to solve mathematical models arising from real applications in science and engineering with the help of a computer. Computational mathematics is not only the application of mathematics for solving challenging real-world problems but also the discovery of new mathematical theories originating from such applications. Mathematical modeling and simulations form a predictive methodology that supplements real experiments as indispensable power for new discoveries. Simulation performance relies not only on computational power but also on the algorithm efficiency and reliability for the underlying complex systems modeled by PDEs. Designing robust and efficient algorithms is crucial for characterizing many phenomena in science and engineering. Life science is an intellectually rich field that has been advanced remarkably through a synergistic interplay between the deep understanding of biology and mathematics. However, biologists are overwhelmed by the amount of experimental data. New methods for data-management and quantitative theories are needed to interpret and contextualize their observations. A variety of challenges in scientific computing related to problems in life science, such as developing predictive models for disorder detection, feature dimensionality reduction, have emerged in recent years. These issues and many other open problems will be discussed among the diverse group of scientists participating in the workshop.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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会议论文
Collaborative Research: Friedrichs Learning: Mathematical Foundation and Applications
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批准号:2206332
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项目类别:Standard Grant
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资助金额:$12.57万
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财政年份:2022
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负责人:Chunmei Wang
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依托单位:
CAREER: Primal-Dual Weak Galerkin Finite Element Methods
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批准号:2136380
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项目类别:Continuing Grant
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资助金额:$40.0万
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财政年份:2021
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负责人:Chunmei Wang
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依托单位:
Innovative Weak Galerkin Finite Element Methods with Application in Fluorescence Tomography
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批准号:1905195
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项目类别:Standard Grant
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资助金额:$1.45万
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财政年份:2018
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负责人:Chunmei Wang
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依托单位:
CAREER: Primal-Dual Weak Galerkin Finite Element Methods
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批准号:1749707
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项目类别:Continuing Grant
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资助金额:$40.0万
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财政年份:2018
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负责人:Chunmei Wang
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依托单位:
CAREER: Primal-Dual Weak Galerkin Finite Element Methods
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批准号:1849483
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项目类别:Continuing Grant
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资助金额:$40.0万
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财政年份:2018
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负责人:Chunmei Wang
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依托单位:
Innovative Weak Galerkin Finite Element Methods with Application in Fluorescence Tomography
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批准号:1648171
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项目类别:Standard Grant
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资助金额:$6.4万
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财政年份:2016
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负责人:Chunmei Wang
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依托单位:
Polytopal Element Methods in Mathematics and Engineering; October 26 - 28, 2015; Atlanta, GA
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批准号:1542183
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项目类别:Standard Grant
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资助金额:$2.5万
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财政年份:2015
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负责人:Chunmei Wang
-
依托单位:
Innovative Weak Galerkin Finite Element Methods with Application in Fluorescence Tomography
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批准号:1522586
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项目类别:Standard Grant
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资助金额:$9.86万
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财政年份:2015
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负责人:Chunmei Wang
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依托单位:
海外基金