Conference: Artificial Intelligence Summer School for Computer Science and Operations Research Education; College Park, Maryland; 19-24 May 2024

这笔赠款提供资金，以支持计算机科学和运筹学教育人工智能暑期学校的召开;学院公园，马里兰州; 2024年5月19日至24日。为来自运筹学（OR）和计算机科学（CS）领域的学生和研究人员开设的暑期学校，旨在帮助弥合OR和CS之间的差距，以推进人工智能（AI）研究。优化方法是许多支持AI的技术的核心。 一般来说，OR社区从基础操作挑战中开发优化方法，从基于模型的角度开始，而CS社区则从计算，数据驱动的角度开始，以应对海量数据集可用性的增加。 这两种观点都有很多东西可以相互借鉴和学习，但到目前为止，它们已经各自发展。暑期学校旨在突出这两种观点，并指导研究生在推进人工智能研究时理解这两种观点的价值。该补助金为来自美国各地的早期博士生提供支持，参加由OR和CS社区AI领域的学术研究人员组织的为期一周的暑期学校。暑期学校的主题将集中在强化学习和公平/平等，特别是由OR和CS研究人员团队联合开发的教程材料。其目的是扩大学生的知识和意识到这两个领域，并在这两个领域的接口种子未来的研究。组织者将广泛宣传暑期学校，并将目标在两个领域的平等出勤率。这个奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

This grant provides funding to support the convening of Artificial Intelligence Summer School for Computer Science and Operations Research Education; College Park, Maryland; 19-24 May 2024. A summer school for students and researchers from the fields of operations research (OR) and computer science (CS) to assist in bridging the gap between the OR and CS perspectives on advancing artificial intelligence (AI) research. Optimization methods are at the core of many techniques that support AI. Generally speaking, the OR community, where optimization methods developed from foundational operational challenges, begins from a model-based perspective, while the CS community, responding to the rise in availability of massive data sets, begins from a computational, data-driven perspective. Both perspectives have much to teach and learn from each other, but to date, they have evolved separately. The Summer School is intended to highlight both perspectives and to guide graduate students in understanding the value of both perspectives as they advance AI research. This grant provides support for early-phase PhD students from across the US to attend a week-long summer school organized by academic researchers in the field of AI from both OR and CS communities. The topics for the summer school will focus on reinforcement learning and fairness/equity, with tutorial material developed especially for the occasion jointly by teams of OR and CS researchers. The intent is to broaden the knowledge and awareness of the students to both fields and to seed future research at the interface of both fields. The organizers will advertise the summer school widely and will target equal attendance across both fields.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.