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Reducing the Impact of Infectious Diseases by Supporting Trans-Disciplinary Academic Research


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Gerard Learmonth

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Gerard P. Learmonth Sr. is Research Professor in the Frank Batten School of Leadership and Public Policy. He is the founding director of the Center for Leadership Simulation and Gaming and the Center for Large-Scale Computational Modeling, a Data Science Institute Center of Excellence. His work involves the modeling and simulation of large, global environmental, economic, and social challenges. These comprehensive, data-driven simulation models may be linked with role-playing interfaces to create serious games for learning. His current effort is the design and development of a Global Food Security Game. In conjunction with the UVA Center for Global Health, Dr. Learmonth conducted in-country research on the effects of poor water quality on the growth and development of children in Limpopo Province, South Africa. The research involved a mobile phone-based census of several villages in Limpopo and the subsequent development of a simulation model used to test the efficacy of proposed water quality interventions using a virtual population developed from the census data. He holds a secondary appointment in the Department of Public Health Sciences in the School of Medicine and a courtesy appoint in the Department of Systems and Information Engineering in the School of Engineering and Applied Science.

Manuel Lerdau

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Manuel Lerdau is a Professor in the Environmental Sciences Department with a joint appointment in the Biology Department. He specializes in evolutionary and community ecology, with a special interest in competitive, mutualistic, and reproductive relationships among organisms and how these relationships mediate population and community dynamics. He has used both evolutionary and ecological models to explore the links among diversity and functional traits. His recent efforts include studies of reproductive flexibility, population dynamics and biodiversity; genome-scale evolutionary change and the origin of functional traits; and competitive interactions in the face of environmental stress. These approaches are relevant for studies of competition and community dynamics among pathogenic and non-pathogenic microbes, the maintenance (or degradation) of microbial community diversity, and the evolution of novel traits (e.g., hyper-pathogenicity) among microbes. Lerdau is particularly interested in examining how two types of ecological interactions, competition and mutualism, affect community structure. For example, in the case of gut communities, how might some taxa compete for similar resources while others use degradation products as energy sources. Lerdau’s initial theoretical work in this area suggested that secondary metabolic products would be the loci of interesting interactions at the community and system scale, and this idea could be relevant also for microbial systems. In terms of infectious diseases, those that emerge from complex communities such as gut-based illnesses will be very amenable to the above ideas.

Bryan Lewis

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I am a computational epidemiologist with 20 years of experience in crafting, analyzing, and interpreting the result of computational models in the context of public health problems.  My research has focused on understanding the transmission dynamics of infectious diseases within specific populations through both analysis and simulation.  Throughout my career I have acted as a liaison between computer scientists and mathematicians developing new software tools and decision makers demanding answers to their pressing public health policy and response questions.  I draw on my experiences in rural Africa as a Peace Corps Volunteer and epidemiologist at the California department of health to keep experiments and analyses grounded in the real-world. Recent projects span infectious disease forecasting, real-time infectious disease outbreak support, complex disaster planning and response, and realistic synthetic data generation. These areas of research are driven by a constant stream of supporting specific case studies for decision makers at the federal level.

Jundong Li

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Jundong Li is an Assistant Professor at the University of Virginia with appointments in the Department of Electrical and Computer Engineering, Department of Computer Science, and School of Data Science. His research interests span several areas, including data mining, machine learning, social media mining, and artificial intelligence. In particular, He is interested in developing innovative learning algorithms to glean actionable patterns from big, noisy, dynamic, heterogeneous, and networked data to address the pressing challenges in various high-impact domains, including social media, bioinformatics, environmental/computational health, online education, and industrial manufacturing. Currently, his team is focusing on knowledge-guided causal inference frameworks and corresponding theoretical understandings to analyze observational data to improve the existing data-driven decision-making process.

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Garrick Louis

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Garrick Louis is an Associate Professor of Systems & Information Engineering, with courtesy appointments in the Departments of Civil & Environmental Engineering and Engineering and Society, in the School of Engineering and Applied Sciences. His research goal is to build local capacity for sustained access to safe, reliable, and affordable water and sanitation services to under-served communities. The work develops methods for needs assessment, performance evaluation/gap analysis, and strategic resource allocation for sustainable (small) infrastructure and disseminates examples of best practice in these methods. The work is pursued through a consortium of collaborators from academia, the service industries, government agencies, grassroots organizations and funding agencies.