课题基金 / 基金详情

NRT-HDR: Interdisciplinary Graduate Training in the Science, Technology, and Applications of Augmented and Virtual Reality

NRT-HDR: Interdisciplinary Graduate Training in the Science, Technology, and Applications of Augmented and Virtual Reality
NRT-HDR:增强和虚拟现实科学、技术和应用的跨学科研究生培训
批准号:
1922591
负责人:
Mujdat Cetin
金额:
$156.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2024-08-31

项目摘要

项目成果

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中文摘要
翻译
增强现实和虚拟现实(AR/VR)有望成为21世纪最具颠覆性的技术之一,彻底改变我们与他人、与环境、与设备和系统的互动方式。VR使用先进的显示和沉浸式音频技术来创建一个交互式的三维(3D)环境。AR使用数字技术将虚拟物体覆盖到物理世界上,以提供信息并美化我们的体验。当前和预期的应用领域包括教育、医疗保健、专业培训、架构和产品设计、远程交互以及娱乐。AR/VR这一新兴领域的持续发展需要具有博士学位和研究经验的研究人员跨越多个学科,包括电子和计算系统、感知和认知神经科学、光学和成像、计算机视觉、声学和音频以及人机界面。为了满足这一需求并实现AR/VR技术的变革潜力,罗彻斯特大学获得的国家科学基金会研究培训(NRT)奖将促进AR/VR领域结构化、多学科博士培训计划的发展。该项目预计将培养62名博士生,其中包括12名获得资助的受训者,他们来自电子与计算机工程、光学、生物医学工程、大脑与认知科学、计算机科学和神经科学。此外,该项目将使约300名其他STEM研究生受益,他们将参与培训和专业发展的各个方面。学员将获得推进AR/VR技术的愿景和技能,以及对这些技术更广泛的文化和社会影响的欣赏。该项目将培养具有包容性的科学家和工程师队伍,使他们成为工业界、学术界和政府的技术领袖,为社会做出贡献。该项目将培养一批在AR/VR领域具有独特能力的博士生。它将有助于塑造未来科学家和工程师的培训方式,不仅是在AR/VR方面,而且更广泛地在人-数据系统接口方面。该项目将以创新的主题推进跨学科研究:将人类感知-认知过程的定量模型整合到跨层设计方法中,以创建和定量评估新的AR/VR技术和应用。以交叉方式整合培训计划的研究重点将推进AR/VR系统的科学基础,并影响下一代AR/VR系统的设计。这些研究重点对应于AR/VR问题领域的四个层面,分别是:(1)AR/VR平台和计算,(2)AR/VR设计的感知-认知方面,(3)AR/VR系统的机器智能,以及(4)AR/VR接口和应用。培训计划包含三个新的创新课程,以解决新学员的不同背景,使他们接触到AR/VR挑战,并提供在多学科团队中从事AR/VR项目的能力,以及各种结构化的专业发展活动。此外,培训还将包括行业实习和与行业领袖的沉浸式专业发展接触。研究生培训模式及其成果将通过有组织的活动和网络向更广泛的学术界广泛传播。美国国家科学基金会研究实习生(NRT)计划旨在鼓励开发和实施大胆的、具有潜在变革性的STEM研究生教育培训新模式。该项目致力于通过创新、循证、适应不断变化的劳动力和研究需求的综合培训模式,在高优先级跨学科或融合研究领域对STEM研究生进行有效培训。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。
英文摘要
Augmented and virtual reality (AR/VR) promises to become one of the most disruptive technologies of the 21st century, revolutionizing how we interact with each other, with our environment, and with devices and systems. VR uses advanced display and immersive audio technologies to create an interactive, three-dimensional (3D) environment. AR uses digital technology to overlay virtual objects onto the physical world to provide information and embellish our experiences. Current and envisioned application areas include education, healthcare, professional training, architectural and product design, remote interaction, and entertainment. Continued progress in the burgeoning field of AR/VR requires researchers with Ph.D. training and research experience spanning multiple disciplines including electronic and computing systems, perceptual and cognitive neuroscience, optics and imaging, computer vision, acoustics and audio, and human-computer interfaces. To address this need and realize the transformative potential of AR/VR technologies, this National Science Foundation Research Traineeship (NRT) Award to the University of Rochester will facilitate the development of a structured, multi-disciplinary Ph.D. training program on AR/VR. The project anticipates training 62 PhD students, including 12 funded trainees, from Electrical and Computer Engineering, Optics, Biomedical Engineering, Brain and Cognitive Sciences, Computer Science, and Neuroscience. In addition, the project will benefit approximately 300 other STEM graduate students who will participate in aspects of the training and professional development. Trainees will gain the vision and skills to advance AR/VR technologies as well as an appreciation for the broader cultural and societal implications of these technologies. The project will train inclusive cohorts of scientists and engineers to contribute to society as technical leaders in industry, academia, and government.The project will train a new cohort of Ph.D. students with a unique set of competencies in the AR/VR domain. It will help shape how future scientists and engineers will be trained not only in AR/VR but more broadly in human-data-system interfaces. The project will advance interdisciplinary research with an innovative theme: integration of quantitative models of human perceptual-cognitive processes into cross-layer design approaches to create and quantitatively evaluate new AR/VR technologies and applications. Research thrusts integrated with the training program in a cross-cutting manner will advance the scientific foundations of AR/VR systems and impact the design of next-generation AR/VR systems. These research thrusts, corresponding to four layers of the AR/VR problem domain, are: (1) AR/VR platforms and computation, (2) perceptual-cognitive aspects of AR/VR design, (3) machine intelligence for AR/VR systems, and (4) AR/VR interfaces and applications. The training program contains three new innovative courses addressing the diverse backgrounds of incoming trainees, exposing them to AR/VR challenges and providing competency to work on AR/VR projects within multi-disciplinary teams as well as a variety of structured professional development activities. In addition, the training will include industry internships and immersive professional development encounters with industry leaders. Both the graduate training model and its outcomes will be widely disseminated to the broader academic community through organized events and a web presence. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.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.
期刊论文(30)
专著(0)
科研奖励(0)
会议论文
Method for minimizing lens breathing with one moving group
用一个移动组最小化镜片呼吸的方法
DOI: 10.1364/oe.457420
发表时间: 2022
期刊: Optics Express
影响因子: 3.8
作者: [Goodsell, Jeremy, Blahnik, Vladan, Rolland, Jannick P.]
通讯作者: Rolland, Jannick P.
DOI: --
发表时间: 2020
期刊:
影响因子: --
作者: [Nan Jiang;Sheng Jin;Z. Duan;Changshui Zhang]
通讯作者: Nan Jiang;Sheng Jin;Z. Duan;Changshui Zhang
DOI: 10.1109/icassp39728.2021.9413652
发表时间: 2021-03
期刊: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
影响因子: --
作者: [N. Mohammadi;M. Doyley;M. Çetin]
通讯作者: N. Mohammadi;M. Doyley;M. Çetin
DOI: 10.1109/embc46164.2021.9629628
发表时间: 2021-11
期刊: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
影响因子: --
作者: [Shadi Sartipi;Mastaneh Torkamani-Azar;Müjdat Çetin]
通讯作者: Shadi Sartipi;Mastaneh Torkamani-Azar;Müjdat Çetin
共 26 条
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    • 负责人:
      Mujdat Cetin
    • 依托单位:
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