Conference: Women in Scientific Computing on Complex Physical and Biological Systems

研讨会“妇女在复杂的物理和生物系统的科学计算”将在佛罗里达州（UF）盖恩斯维尔，佛罗里达州从周一10月24日至周三10月26日，2022年的大学校园举行。研讨会将汇集来自计算数学、生命科学、计算机科学和工程等各个领域的顶尖专家，积极讨论复杂物理和生物系统科学计算的最新发展，并将其应用于气候变化、清洁能源和生物技术，同时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在生命科学、计算机科学和工程领域的快速传播，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，以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，并启动联合研究项目。该奖项支持研究人员和研究生的出席，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、少数民族研究人员和没有其他联邦支持的研究人员。科学计算是在计算机的帮助下，结合计算工具、技术和理论来解决科学和工程实际应用中产生的数学模型。计算数学不仅是应用数学来解决具有挑战性的现实世界问题，而且是从这些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，作为新发现不可缺少的力量，补充了实际实验。对于基于偏微分方程建模的底层复杂系统，其仿真性能不仅取决于计算能力，还取决于算法的效率和可靠性。设计稳健、高效的算法是表征科学和工程中许多现象的关键。生命科学是一个智力丰富的领域，它通过对生物学和数学的深刻理解之间的协同相互作用而取得了显著的进步。然而，生物学家被大量的实验数据压垮了。需要新的数据管理方法和定量理论来解释和分析他们的观察结果。近年来，与生命科学问题相关的科学计算领域出现了各种各样的挑战，如开发预测模型来检测疾病、特征降维等。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。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.