I/UCRC CGI: Center for Dynamic Data Analytics (CDDA)

I/UCRC CGI：动态数据分析中心 (CDDA)

• 批准号: 1069147
• 负责人: Arie Kaufman
• 金额: $ 27.5万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-03-15 至 2017-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1069147&HistoricalAwards=false
• 关键词: UCRC; CGI; Center; Dynamic; Data

1069258 Rutgers University; Dimitris Metaxas 1069147 Arie Kaufman; SUNY at Stony Brook The Center for Dynamic Data Analysis (CDDA) will focus on conducting innovative research and applications based on the collaborative efforts between the two universities and member companies in the emerging field of dynamic data analysis. The end result will be novel science, algorithms and applications that transform chaos into knowledge. Rutgers University (RU) and SUNY at Stony Brook are collaborating to establish the proposed center, with RU as the lead institution. The proposed Center will investigate algorithms and potential solutions to analyze and visualize massive, complex, multidimensional and multi-scale dynamic data. The algorithm design will be tested, validated and improved based on the close collaboration and research between the two participating universities and industry. The participating universities have research and education programs whose strengths cover the technical scope of the center. The proposed research projects will be useful to industry and homeland security, and the proposed Center will transform traditional research in computer science. Analysis and visualization of large-scale dynamic data will also become a new area of research for many graduate students. CDDA plans to have students spend time with the industrial affiliates in the form of summer internships and during the academic year so they can improve their skills. The participating universities also plan to leverage existing outreach programs at their institutions, and programs sponsored by the NSF, to encourage the participation of under-represented groups in the research..

1069258 罗格斯大学；迪米特里斯·梅塔克萨斯 1069147 阿里·考夫曼；纽约州立大学石溪分校动态数据分析中心（CDDA）将基于两所大学和成员公司在动态数据分析新兴领域的合作，重点开展创新研究和应用。最终结果将是新颖的科学、算法和应用程序，将混沌转化为知识。罗格斯大学 (RU) 和纽约州立大学石溪分校正在合作建立拟议的中心，其中罗格斯大学作为牵头机构。拟议的中心将研究分析和可视化海量、复杂、多维和多尺度动态数据的算法和潜在解决方案。算法设计将基于两所参与大学和行业之间的密切合作和研究进行测试、验证和改进。参与大学的研究和教育项目的优势涵盖了该中心的技术范围。拟议的研究项目将对工业和国土安全有用，拟议的中心将改变计算机科学的传统研究。大规模动态数据的分析和可视化也将成为许多研究生的新研究领域。 CDDA 计划让学生以暑期实习和学年期间的形式与工业附属公司共度时光，以便提高他们的技能。参与的大学还计划利用其机构现有的外展项目以及美国国家科学基金会赞助的项目，鼓励代表性不足的群体参与研究。

项目成果

Transfer Function-Guided Saliency-Aware Compression for Transmitting Volumetric Data

用于传输体积数据的传递函数引导显着性感知压缩

• DOI: 10.1109/tmm.2017.2757759
• 发表时间: 2017-09-28
• 期刊: IEEE Transactions on Multimedia
• 影响因子: 7.3
• 作者: Ji Hwan Park;Ievgeniia Gutenko;A. Kaufman
• 通讯作者: A. Kaufman

Classification of Pancreatic Cysts in Computed Tomography Images Using a Random Forest and Convolutional Neural Network Ensemble

使用随机森林和卷积神经网络集成对计算机断层扫描图像中的胰腺囊肿进行分类

• DOI: 10.1007/978-3-319-66179-7_18
• 发表时间: 2017-09
• 期刊: Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
• 作者: Dmitriev K;Kaufman AE;Javed AA;Hruban RH;Fishman EK;Lennon AM;Saltz JH
• 通讯作者: Saltz JH