Conference: EPSCoR Workshop on Machine Learning for Analysis of High-Energy Cosmic Particles

会议：EPSCoR 高能宇宙粒子机器学习分析研讨会

• 批准号: 2336900
• 负责人: Frank Schroeder
• 金额: $ 10万
• 依托单位: University of Delaware
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2336900&HistoricalAwards=false
• 关键词: Conference; EPSCoR; Workshop; Machine; Learning

This project will support a workshop on the application of Machine Learning for the Analysis of High-Energy Cosmic Particles. The workshop will be hosted by the University of Delaware and will bridge the themes: "Windows of the Universe" and "Harnessing the Data Revolution." Natural objects in the Universe, which are yet unknown, accelerate particles to energies far beyond human technological capabilities. A primary objective of particle astrophysics is to locate and comprehend the sources of these cosmic particles. To achieve this, specialized astroparticle observatories have been deployed to collect a diverse range of data. The advancement of science in this field hinges significantly on the quality of data analysis, benefiting from recent progress in machine learning, including artificial neural networks. Beyond the exchange of recent results and ideas in machine learning for high-energy particle astrophysics, the workshop will enhance scientific capabilities in this domain and serve the purpose of training a future workforce proficient in applying machine learning techniques. Special attention will be given to equity, diversity, and inclusion, with a hybrid format enabling broad participation, including both in-person and remote attendees. To maximize its impact, the workshop will involve co-organizers and participants from several EPSCoR states.The organizers will host a hybrid workshop with a conference-like format focusing on the application of machine learning for analyzing cosmic particles, including cosmic rays, high-energy gamma rays, and ultra-high-energy neutrinos—integral components of multi-messenger astronomy. Institutions in EPSCoR jurisdictions have begun to engage in this endeavor and anticipate a significant future role in NSF experiments, such as IceCube at the South Pole. Recognizing the value of in-person meetings for effective discussions and networking, this hybrid workshop will bring approximately 50 in-person participants to the University of Delaware for one week in early 2025, while also facilitating participation from additional online attendees. The organization of the workshop builds upon the successful multi-institutional collaboration established through the "NSF IceCube EPSCoR Initiative: IceCube and the Data Revolution" and will further encourage the involvement of EPSCoR institutions in this research area. Intellectual merits will be delivered through scientific exchanges during the workshop and, in the long term, by publishing workshop products on an open access platform in a citable manner. Supporting the NSF EPSCoR mission in various ways, the workshop will generate broader impacts and spur research initiatives by facilitating the exchange of scientific knowledge and fostering new connections among participants. By offering support to students from EPSCoR jurisdictions and underrepresented groups in STEM, the workshop will contribute to equality, diversity, and inclusion while preparing the next generation of the STEM workforce.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.

该项目将支持有关机器学习应用用于分析高能宇宙颗粒的研讨会。该研讨会将由特拉华大学主持，并将桥接主题：“宇宙窗户”和“利用数据革命”。宇宙中尚不清楚的天然物体加速粒子，远远超出了人类技术能力。粒子天体物理学的主要目的是定位和理解这些宇宙颗粒的来源。为此，已经部署了专门的Astroparticle观察者来收集潜水员的数据范围。该领域的科学进步显着取决于数据分析的质量，这受益于机器学习的最新进展，包括人工神经元网络。除了交换用于高能粒子天体物理学的机器学习中的结果和思想外，该研讨会还将增强该领域的科学能力，并实现培训未来的劳动力，以熟练应用机器学习技术。将特别关注公平，多样性和包容性，并具有混合格式，可以广泛参与，包括面对面和远程与会者。 To maximize its impact, the workshop will involve co-organizers and participants from several EPSCoR states.The organizers will host a hybrid workshop with a conference-like format Focusing on the application of machine learning for analyzing cosmic particles, including cosmic rays, high-energy gamma rays, and ultra-high-energy neurons—integral components of multi-messenger astronomy. EPSCOR司法管辖区的机构已经开始从事这一努力，并预计在NSF实验中将扮演着重要的未来角色，例如南极Icecube。认识到面对面会议的有效讨论和网络的价值，该混合动力研讨会将在2025年初将大约50名面对面的参与者带到特拉华大学，同时也支持其他在线参与者的参与。研讨会的组织建立在通过“ NSF ICECUBE EPSCOR计划：ICECUBE和数据革命”建立的成功的多机构合作的基础上，并将进一步鼓励Epscor机构参与该研究领域。智力优点将通过研讨会期间的科学交流提供，从长远来看，通过以可提取的方式在开放访问平台上发布研讨会产品。该研讨会以各种方式支持NSF EPSCOR任务，将通过支持科学知识的交流并促进参与者之间的新联系，从而产生更广泛的影响和刺激研究计划。通过为STEM中EPSCOR司法管辖区和代表性不足的群体的学生提供支持，该研讨会将在准备下一代STEM Workforce的同时为平等，多样性和包容性提供贡献。该奖项反映了NSF的法定任务，并通过使用该基金会的知识分子优点和广泛的影响来评估NSF的法定任务，并被认为是珍贵的支持。