I/UCRC: Center for Hybrid Multicore Productivity Research (CHMPR) - Rutgers Site

作为NSF I/UCRC混合多核生产力研究(CHMPR)的研究站点，罗格斯数据科学、学习和应用研究所(I-DSLA)的使命是推动大数据管理和分析领域的研究和教育。这项与行业合作伙伴合作的多学科研究计划侧重于解决医疗保健、电子政务和电子商务以及社区弹性和公共安全等应用领域的研究和开发挑战。这个项目的一个关键目标是通过提供学生与行业合作伙伴研究现实世界问题的机会来整合研究和教育。对实际问题的重视特别适合于吸引来自不同背景的个人，扩大对计算机科学和信息学研究的参与。罗格斯I-DSLA网站的研究议程与CHMPR的研究议程是互补和协同的。I-dsla的研究项目跨越几个主题(数据分析、机器学习、数据管理、信息安全和隐私、社交媒体、Web服务和语义网)和领域。在医疗保健领域，来自罗格斯大学新泽西医学院癌症中心、罗格斯I-DSLA和罗格斯信息管理、集成和连接中心(CIMIC)的研究人员参与了这项多学科研究计划。该计划利用团队成员的互补专业知识来开发基于数据分析的方法，从而能够发现最佳治疗方案，并识别允许对特定治疗组合和方式做出反应的患者和疾病特征。在电子政务和电子商务领域，研究工作涉及安全信息共享、业务流程组合和管理以及隐私保护数据分析等基本问题。在社区复原力和公共安全领域，研究工作集中在灾害管理、关键基础设施保护和智慧城市。

As a research site of the NSF I/UCRC for Hybrid Multicore Productivity Research (CHMPR), the mission of the Rutgers Institute for Data Science, Learning, and Applications (I-DSLA) is to advance research and education in the area of Big data management and analytics. The multidisciplinary research program in collaboration with the industry partners, focuses on addressing research and development challenges in application domains that span healthcare; e-government and e-commerce; and community resilience and public safety. A key objective of this project is to integrate research and education by providing student opportunities to work on real world problems with industry partners. The emphasis on real problems is particularly suited to attracting individuals from diverse backgrounds, broadening participation in computer science and informatics research.The research agenda of the Rutgers I-DSLA site is complementary and synergistic to that of CHMPR. The research projects at I-DSLA span several themes (data analytics, machine learning, data management, information security and privacy, social media, Web services, and semantic Web) and domains. In the healthcare domain, the multidisciplinary research program involves researchers from the Rutgers New Jersey Medical School Cancer Center, Rutgers I-DSLA, and Rutgers Center for Information Management, Integration, and Connectivity (CIMIC). The program leverages the complementary expertise of the team members to develop data analytics-based approaches that enables discovery of optimal treatment regimens and identification of patient and disease characteristics that permit responses to specific therapeutic combinations and modalities. In the e-government and e-commerce domains, the research work addresses fundamental problems related to secure information sharing, business process composition and management, and privacy-preserving data analysis. In the community resilience and public safety domain, the research work focuses on disaster management, critical infrastructure protection, and smart cities.