• Geared toward novice REDCap users, this class answers what REDCap is, why you want to use it, and goes through the entire lifecycle of a REDCap project – from initial setup to data entry and exporting your data.

    Biology, Medicine, Public Health, Research, Training, Professional Development
  • This workshop will cover the ins & outs of using REDCap for electronically consenting research participants and provide a guided demonstration of the e-Consent template. Participants will learn how to design and customize e-Consent surveys and learn best practices and common pitfalls to avoid.

    Biology, Medicine, Public Health, Research, Training, Professional Development
  • A challenge for mathematical modeling, from toy dynamical system models to full weather and climate models, is applying data assimilation and dynamical systems techniques to models that exhibit chaos and stochastic variability in the presence of coupled slow and fast modes of variability. Recent collaborations between universities and government agencies in India and the United States have resulted in detailed observations of oceanic and atmospheric processes in the Bay of Bengal, the Arabian Sea, and the Indian Ocean, collectively observing many coupled modes of variability. One key target identified by these groups was the improvement of forecasts of variability of the summer monsoon, which significantly affects agriculture and water management practices throughout South Asia. The Monsoon Intraseasonal Oscillation is a northward propagating mode of precipitation variability and is one of the most conspicuous examples of coupled atmosphere-ocean processes during the summer monsoon. Simulating coupled atmosphere-ocean processes present mathematical challenges spanning numerical methods, data assimilation, stochastic modeling, dynamical systems and chaos, and uncertainty quantification. Predicting monsoon variability is one of the hardest, most important forecasting problems on earth due to its impact on billions of people, a key aspect of the desire to push weather forecasts into the management-actionable “medium-range” horizon of weeks to seasons. Addressing this challenge requires an interdisciplinary effort to combine observations, computation, and theory. A better understanding of these processes and how they can be represented in a variety of coupled ocean-atmosphere simulations and models (including statistical and dynamical approaches) and forecast systems (including data assimilation techniques and uncertainty quantification) is the primary topic of this workshop. While the set of observations to be discussed will emphasize this region, the mathematical and computational aspects of the program will be significantly broader, covering: coupled ocean-atmosphere modeling for weather models, climate models and idealized models; theory of the atmospheric and oceanic boundary layers, and waves on the interface; data assimilation in coupled modeling systems; and numerical methods for coupled systems.

    Mathematics, Art, STEM, Research, Mathematics, Technology, Engineering
  • Holistic Design of Time-Dependent PDE Discretizations

    The workshop aims to spur a holistic approach to the design of time-dependent PDE discretizations, particularly in terms of developing time integration techniques that are intertwined with spatial discretization techniques, focusing on: generalized ImEx methods, asymptotic-preserving and structure-preserving methods, methods that exploit low-rank dynamics, analysis of order reduction, parallel in time methods, and performant, maintainable, extensible software implementations.

    Recent decades have seen increasing use of first-principles-based simulations via time-dependent partial differential equations (PDE), with applications in astrophysics, climate science, weather prediction, marine science, geosciences, life science research, defense, and more. Growing computational capabilities have augmented the importance of sophisticated high-order and adaptive methods over “naive’” low-order methods. However, there are fundamental challenges to achieving truly high order and full efficiency in space-time that are yet to be overcome.

    Many advances in temporal and spatial discretization methods have been made independently, by employing techniques in which each part can be developed and analyzed in isolation. However, as spatial discretization methods have become more sophisticated, accurate, efficient, and specialized, computational scientists are finding that temporal integration, in particular, the interface between temporal and spatial discretization, is a source of bottlenecks that limit practical applications. As a response, myriad problem-specific time-stepping approaches have been devised in recent years, but with little feedback to or from the time integration community. This isolated development has led to a “bag of tricks” situation that will benefit from a more systematic perspective. The workshop will address these challenges by bringing together time integration specialists with numerical PDE specialists and experts in high-performance numerical computing.

    Mathematics, Art, STEM, Research, Mathematics, Technology, Engineering

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Decoding Pandemic Data:  A Series of Interactive Seminars:

These are lunchtime short talks by experts directly engaged in COVID-related data-driven research activities, with plenty of time for question and answer. Details here.

Faculty for Faculty Research Talks:

Informal opportunities for faculty to present their data science–related research to other faculty. Our goal is to provide a networking venue that promotes research collaborations between faculty across all disciplines; awareness of the breadth of data science–related research at Brown; and a forum for faculty to share their expertise with one another. Details here.

Data Wednesdays:

Our weekly seminar, hosted by DSI, CCMB, COBRE, 4-5 pm, at 164 Angell, 3rd floor

Data Science, Computing and Visualization Workshops:

[On hiatus] Weekly at noon on Fridays; see previous topics.