Planning Grant: I/UCRC for Center for Dynamic Data Analytics Site at the University of Virginia

弗吉尼亚大学（UVA）计划加入动态数据分析中心，这是一个现有的多大学行业/大学合作研究中心（I/UCRC），目前由罗格斯大学（牵头机构）和斯托尼布鲁克大学组成。该奖项为UVA提供了NSF的支持，以探索建立这个新网站的可行性。规划补助金将用于规划行业和大学的联合研究议程，组织和参加与潜在行业成员和现有网站的会议，并举办规划会议，这将是向潜在成员阐明网站愿景的努力的中心点。UVA/CDDA研究的主要行业领域是：（1）金融和银行业，包括金融市场和电子交易，系统性风险和监管机构的数据分析;（2）互联网分析，包括营销和物联网;（3）先进制造业，包括数据驱动的自动化方法，人为因素，流程改进和自动化;（4）网络物理系统，包括物理系统和自主系统的网络安全。这些领域共同构成了经济的一部分，既可观又不断增长。CDDA UVA网站的主要使命是进行数据分析研究，以支持行业和政府的决策。重点是分析数据集，这些数据集以其速度，多样性，数量，复杂性和其他与大数据相关的特征来区分。CDDA的UVA网站将追求一个研究议程，补充现有网站的研究议程，并将控制，决策和系统建模概念与统计方法，机器学习和模式识别相结合。集中的领域包括行为和偏好建模，基于状态的模型，强化学习，安全计算和数据隐私，以及数据驱动的网络安全方法。UVA网站研究议程的一个主要特点是强调规范建模和理解复杂系统决策背景下的数据收集和使用。

The University of Virginia (UVA) is planning to join the Center for Dynamic Data Analytics, an existing multi-university Industry/University Cooperative Research Center (I/UCRC) which is currently comprised of Rutgers University (lead institution) and Stony Brook University. This award provides UVA with the support from the NSF for exploring the feasibility of establishing this new site. The planning grant will be used to plan a joint industry and university research agenda, to organize and attend the meetings with potential industry members and the existing sites, and to host a planning meeting that will be the center point of the effort to articulate the vision for the site to potential members. The principal industry domains for UVA/CDDA research are: (1) Finance and banking, including financial markets and electronic trading, systemic risk, and data analytics for regulators; (2) Internet analytics, including marketing and the Internet of Things; (3) Advanced manufacturing, including data-driven approaches to automation, human factors, process improvement, and prognostics; (4) Cyberphysical systems, including cybersecurity of physical systems and autonomous systems. Together these domains constitute a portion of the economy that is both substantial and increasing. The primary mission of the UVA site of CDDA is to perform research on data analytics to support decision making in industry and government. The focus is on analysis of data sets distinguished by their velocity, variety, volume, complexity, and other features commonly associated with Big Data. The UVA site of CDDA will pursue a research agenda that complements that of the existing sites and features an integration of control, decision, and systems modeling concepts with statistical methods, machine learning and pattern recognition. Areas of concentration include behavioral and preference modeling, state-based models, reinforcement learning, secure computation and data privacy, and data-driven approaches to cybersecurity. A principal distinguishing characteristic of the UVA site research agenda is an emphasis on prescriptive modeling and understanding the collection and use of data in the context of decision making in complex systems.