REU Site: Computing for Health and Well-being

这个本科生研究经验（REU）网站解决了美国医疗保健系统由于短期挑战（如COVID-19爆发所带来的挑战）以及长期趋势（如人口老龄化）而面临的持续压力。为了解决这些问题和其他问题，下一代计算机科学家应该接受培训，与计算机科学家和卫生专业人员一起在跨学科的、以问题为中心的团队中工作。REU学生将(1)学习跨学科研究；(2)将计算思维应用于现实问题；(3)熟悉不同学科的文化和研究方法；(4)参加有关研究方法、科学传播和职业发展的研讨会；(5)发展自己的第一个专业网络，同时增强对自己技能和能力的自信。特别侧重于为来自非研究机构的学校的学生、缺乏综合性医疗中心提供的跨学科研究机会的学校和/或来自代表性不足群体的学生（包括特别强调第一代学生）提供研究经验。其目标是帮助培养一支有才华的年轻科学家队伍，帮助保持国家在科学和技术方面的竞争优势。REU的参与者将学习和应用计算和数据科学中的算法方法来增强健康和福祉。解决社会相关问题和参与专业发展将为学生提供智力挑战和引人入胜的经历，同时培养对计算机科学和科学研究的热情。每个学生都被纳入一个已建立的研究小组，在导师的直接监督下，研究健康和福祉领域的前沿跨学科挑战。利用最新的技术和计算工具，以及来自建模、仿真、人工智能、机器学习和人机交互的先进算法方法，学生将研究传染病建模、疾病风险评估、先进的助听器技术、评估情绪或情绪的筛选工具，以及用于通过游戏吸引神经多样性儿童的沉浸式技术等领域的问题。学生还将通过与其他REU参与者、研究生、领域专家和导师的互动来学习。接触不同的研究项目将进一步加深参与者对自己项目的理解，同时拓宽他们对不同研究方法的欣赏。同时，导师发展活动将帮助早期职业教师和高级研究生学习如何与年轻科学家有效地合作。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。

This Research Experiences for Undergraduates (REU) site addresses the ongoing strains faced by the U.S. healthcare system due to short-term challenges, such as those posed by the COVID-19 outbreak, as well as long-term trends, such as aging population. To tackle these and other problems, the next generation of computer scientists should be trained to work with both computer scientists and health professionals on interdisciplinary, problem-focused teams. REU students will (1) learn about interdisciplinary research;(2) apply computational thinking to real-world problems; (3) become familiar with the culture and research methods of different disciplines; (4) participate in workshops on research methods, scientific communication, and career development; and (5) develop their first professional network while boosting self-confidence in their own skills and abilities. The special focus is on providing research experiences to students from schools that are not research institutions, schools that lack the interdisciplinary research opportunities afforded by the presence of a comprehensive medical center, and/or students from underrepresented groups, including a special emphasis on first-generation students. The goal is to help prepare a workforce of talented young scientists who will help maintain the nation's competitive advantage in science and technology. The REU participants will learn and apply algorithmic methods from computing and data science to enhance health and well-being. Tackling socially relevant problems and participating in professional development will provide students with an intellectually challenging and engaging experience, while fostering a passion for computer science and scientific research. Each student is integrated into an established research group working under a mentor's direct supervision on cutting-edge interdisciplinary challenges in health and well-being. Using the latest technology and computational tools, as well as advanced algorithmic methods from modeling, simulation, artificial intelligence, machine learning, and human-computer interaction, students will work on problems in areas such as infectious disease modeling, disease risk assessment, advanced hearing aid technology, screening tools to assess mood or emotion, and immersive technologies used to engage neurodiverse children through gameplay. Students will also learn through their interactions with other REU participants, graduate students, domain experts, and mentors. Exposure to a collection of diverse research projects within their cohort will further participants’ understanding of their own projects while broadening their appreciation of different research methods: at the same time, mentor development activities will help early-career faculty and advanced graduate students learn how to work effectively with young scientists.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.