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The goal of the interagency Smart and Connected Health (SCH): Connecting Data, People and Systems program is to accelerate the development and integration of innovative computer and information science and engineering approaches to support the transformation of health and medicine. Approaches that partner technology-based solutions with biomedical and biobehavioral research are supported by multiple agencies of the federal government including the National Science Foundation (NSF) and the National Institutes of Health (NIH). The purpose of this program is to develop next-generation multidisciplinary science that encourages existing and new research communities to focus on breakthrough ideas in a variety of areas of value to health, such as networking, pervasive computing, advanced analytics, sensor integration, privacy and security, modeling of socio-behavioral and cognitive processes and system and process modeling. Effective solutions must satisfy a multitude of constraints arising from clinical/medical needs, barriers to change, heterogeneity of data, semantic mismatch and limitations of current cyberphysical systems and an aging population. Such solutions demand multidisciplinary teams ready to address issues ranging from fundamental science and engineering to medical and public health practice.

Computer systems support a broad range of applications and technologies that seamlessly integrate with human users. While many key building blocks of computer systems are today commercial technologies, the challenge ahead is to envision new technologies, as well as to combine existing technologies, software, and sensing systems into the computer systems of the future that will span wearable computing, the Internet of Things (IoT), "Smart Cities," intelligent transportation systems, personalized healthcare, and beyond. Such computer systems will require new, innovative, and visionary approaches to hardware, wired and wireless communications, consideration of human-computer interactions, and new programming languages and compilers that are limited only by the imagination. They will need to be reliable in the presence of unreliable components, adaptive to changing environments, capable of supporting high-throughput applications and large-scale data storage and processing, and able to meet performance and energy objectives for applications ranging from very low-power embedded systems to large high-performance computing systems. Furthermore, computer systems of the future will need to provide mechanisms for ensuring security and privacy.

In today's increasingly networked, distributed, and asynchronous world, cybersecurity involves hardware, software, networks, data, people, and integration with the physical world. However, society's overwhelming reliance on this complex cyberspace has exposed its fragility and vulnerabilities: corporations, agencies, national infrastructure and individuals have been victims of cyber-attacks. Achieving a truly secure cyberspace requires addressing both challenging scientific and engineering problems involving many components of a system, and vulnerabilities that arise from human behaviors and choices. Examining the fundamentals of security and privacy as a multidisciplinary subject can lead to fundamentally new ways to design, build and operate cyber systems, protect existing infrastructure, and motivate and educate individuals about cybersecurity.

In today's increasingly networked, distributed, and asynchronous world, cybersecurity involves hardware, software, networks, data, people, and integration with the physical world. Society's overwhelming reliance on this complex cyberspace, however, has exposed its fragility and vulnerabilities that defy existing cyber-defense measures; corporations, agencies, national infrastructure and individuals continue to suffer cyber-attacks. Achieving a truly secure cyberspace requires addressing both challenging scientific and engineering problems involving many components of a system, and vulnerabilities that stem from human behaviors and choices. Examining the fundamentals of security and privacy as a multidisciplinary subject can lead to fundamentally new ways to design, build and operate cyber systems, protect existing infrastructure, and motivate and educate individuals about cybersecurity.

The Microsoft Foundation is inviting applications for its Dissertation Grants program. The program supports PhD students at North American universities who are underrepresented in the field of computing and pursuing research aligned to the research areas carried out by Microsoft Research. Through the program, recipients will receive funding of up to $25,000 for the 2020-21 academic year as well as an invitation to the PhD Summit, a two-day workshop in the fall held at one of Microsoft Research's labs where fellows will meet with Microsoft researchers and other top students to share their research. Fellows must be aligned in research areas as defined by Microsoft Research, which include artificial intelligence; audio and acoustics; computer vision; graphics and multimedia; human-computer interaction; human language technologies; search and information retrieval; data platforms and analytics; hardware and devices; programming languages and software engineering; security, privacy, and cryptography; systems and networking; algorithms; mathematics; ecology and environment; economics; medical, health, and genomics; social sciences; and technology for emerging markets.

Social science research on many topics has often been hampered by the limitations of survey data. However, the digital age has rapidly increased access to large and comprehensive data sources such as public and private administrative databases, and unique new sources of information from online transactions, social-media interactions, and internet searches. New computational tools also allow for the extraction, coding, and analysis of large volumes of text. Advances in analytical methods for exploiting and analyzing data have accompanied the rise of these data. The emergence of these new data also raises questions about access, privacy and confidentiality. The Russell Sage Foundation's initiative on Computational Social Science (CSS) supports innovative social science research that brings new data and methods to bear on questions of interest in its core programs in Behavioral Economics, Future of Work, Race, Ethnicity and Immigration, and Social Inequality. Limited consideration will be given to questions that pertain to core methodologies, such as causal inference and innovations in data collection.

Pandemics have far reaching consequences that range from deaths to shutting down the economy as we have witnessed during the recent COVID19 crisis. Hence there is a need to be better prepared for such pandemics. We need to solve problems ranging from predictive analytics innovative devices for saving lives to technology for devising voting machines. The social and economic impact for the above areas is huge and some of the work can be transformative and save lives. Areas of interest to us include, but are not limited to: - Mathematical models for spread and the impact of pandemics. - Scalable simulation techniques for pandemics (e.g. with multi agents). - Biomedical/Nano sensor devices for detecting symptoms and agents. - Algorithms for rapid exploration of the drug screening and discovery workflows (e.g. use reinforcement learning) - Advanced computational biology techniques for sequencing, detecting viral evolution (e.g. in COVID-19). - Algorithms and systems for contact tracing (with privacy preserving). - Algorithms and recommendation systems for curating media and news. - Collaboration techniques for more effective health, and efficiency during pandemics. Improved identity and security techniques. - Distributed Ledgers, their applications and their governance for and during pandemics. - Pandemic data science - understanding the patterns and the impact of a pandemic like COVID-10. Creation of curated data sets. We are interested in both the science and technology aspects of these problem sets, and, particularly, in the intersections between them.