Communities of Practice

This group is working to understand how the human brain controls and learns to control behavior, and how disease impacts these processes. The group includes faculty, postdocs and senior graduate students in brain imaging, sensing of brain chemistry and motor behavior, data analysis and computational modeling. 

For more information, please get in touch with Andrew Fagg at andrewhfagg@gmail.com.

The OU Community Engagement Community of Practice is sponsored by the Center for Faculty Excellence and Data Institute for Societal Challenges. This community of practice emphasizes community-engaged OU researchers, educators, and scholars across campuses and disciplines. This Community of Practice has met monthly since May of 2021 and held meetings throughout the fall 2021 semester to provide opportunities for faculty and staff to interact with community partners (primarily in the Norman and OKC areas) who have a variety of data, service learning, and infrastructure needs.

If you are interested in community-engaged research or service-learning and have questions about this program or other opportunities, please contact Joy Pendley at Pendley@ou.edu.

This group works to bring people together who work in Digital Humanities or would like to engage in Digital Humanities work to foster collaboration. Furthermore, this group will also be used to discuss the future steps of the Digital Humanities program at OU. Our goal is to get faculty and staff to work on or become interested in Digital Humanities. In addition to this, we also wish to link our Digital Humanities sector with that of the Arts and Humanities Forum. Dr. Sam Huskey, Dr. Carrie Schroeder, and Dr. Kimberly Marshall will be the co-facilitators of these endeavors.

For more information, please contact Dr. Kimberly Marshall at kjm@ou.edu, Dr. Carrie Schroeder at ctschroeder@ou.edu or Sam Huskey at huskey@ou.edu.

One of the OU VPRP’s strategic research verticals is Environment, Energy and Sustainability (ESS). Within this EES vertical, the strategic plan identifies the focus area of Earth system observation and prediction. Developing research ideas that fall into this category is the goal of this group that meets on a semi-regular basis. More specifically, this group brings together researchers working on understanding processes in the biosphere, geosphere, hydrosphere, atmosphere, and their linkages. In our conversations we apply a systems approach, identify synergies and shared research interests around the broader topics of Earth systems science, observation and prediction of the Earth system, and work towards describing these ideas and synergies in 1-page summaries. One of the underlaying motivations is to be prepared for emerging funding opportunities and for reaching out to program managers of potential funding agencies.

If you would like to join this Community of Practice, please contact Michael Wimberly at mcwimberly@ou.edu.

This group will bring together a multidisciplinary group of researchers from the undergraduate to faculty level, who want to explore how machine learning can be used in conjunction with traditional statistical methods for data analysis of datasets that span the social and natural sciences. This CoP will also facilitate joint research with the use of big data techniques to improve our understanding of social structures as they relate to OU's strategic verticals - from climate and the environment, to social injustice (including intrinsic data science bias), and other dynamic challenges to our quality of life.

For more information, please contact Heather Bedle at hbedle@ou.edu, Martin Piotroski at piotrow@ou.edu, and Chris Garneau at cgarneau@ou.edu. 

Neuroscience is a broad research area that ranges from intracellular mechanisms of neurotransmitter receptor production, to systems of brain regions that collaborate in sensorimotor activity, and to population-level effects of disease and injury.  Our ability to collect tremendous amounts of data is outpacing our ability to analyze and model these data.  We seek to connect clinicians and other researchers in the neuroscience / neurosurgery community with data science and machine learning researchers to solve these large-scale problems.

For more information, please get in touch with Andrew Fagg at andrewhfagg@gmail.com.

This group has approximately 90 members consisting of faculty, staff, and graduate students across all OU campuses interested in research to address the opioid crisis in Oklahoma and the US. The goal of the group is to keep abreast of opportunities for opioid-related funding, share ongoing research to foster collaboration and expansion of the research, and, ultimately, to use research to develop and implement solutions. The group hosts events a couple of times a year and is open to member feedback about new directions. We hope in 2022 to design and participate in a community service project—building the relationship between OU and the broader community.

For more information, please contact Erin Maher at erin.maher@ou.edu.

This Community of Practice is working to enhance the understanding, design, and resilience of supply chains and supply-demand networks. In today’s world, supply chains are highly interconnected and their proper operation is affected by diverse types of hazards, both natural (e.g., pandemics, earthquakes, floodings, climate-change induced events) and anthropogenic (e.g., attacks to physical and/or cyber infrastructure). Maintaining resilient supply chains is critical for societies and their well-being, having direct impact on the economy, healthcare, food, water, and energy supply, as well diverse defense-related and military functions.  

For more information, please contact Andrés González at andres.gonzalez@ou.edu.

This Community of Practice aims to bring researchers from Economics, Finance, Business, Artificial Intelligence, Machine Learning, Visual Analytics, and various related domain sciences to find elegant solutions that break down computational and analytical barriers in understanding complex Economics, Finance, and Business challenges. This CoP responds to McKinsey’s vision that the new era of AI is rapidly transforming roles and enhancing the performance of various aspects of modern Economics, Finance, and Business, such as forecasting, marketing, sales, customer servicing, and software development. This CoP will form research groups and discussion panels with participants to share research interests and emerging funding opportunities to foster long-term interdisciplinary research collaborations.

For more information, please contact Yifu Li at liyifu@ou.edu

This group works to bring people together who work with 3D data. The group's efforts will focus on connecting professionals from disparate departments to support and augment current 3D work and to generate new projects that support the University’s strategic vision. The group will endeavor to connect experts and novices to develop a framework of understanding around 3D workflows in order to establish knowledge scaffolding useful to all skill-levels. In addition, the group will work together establish review boards and guidelines for ethical concerns around the use of 3D data, reduce the duplication of digital preservation efforts on campus while developing centralized, robust storage solutions and unify requests for external dollars around 3D technologies at a campus level rather than duplicating requests and purchases in multiple departments.

For more information, please contact Kristi Wyatt at kwyatt@ou.edu or Asa Randall at ar@ou.edu.

The Human-Centered Trustable AI Community of Practice brings together researchers from OU Norman, OU HSC, and ORMF with a shared mission to develop reliable, trustable AI systems centered around human involvement in their processes, decisions, and improvements. Our community fosters collaboration across multiple disciplines, including AI and Machine Learning, Visualization and Visual Analytics, Generative AI, Information Science, Data Communication, Social Science, Psychology, and related domain sciences. Together, we aim to advance state-of-the-art techniques, solve computational challenges, and design systems that effectively address human-centered issues in AI. We host formal seminars and organize informal gatherings to showcase ongoing work, promote interdisciplinary collaboration, initiate grant proposals, and engage prospective student researchers, creating a vibrant space for innovation and research excellence.

Machine learning experiments involving large-scale models and/or data sets require substantial storage, communication, and computational resources.  This CoP focuses on the unique ML challenges that arise at these scales.  Topics will include efficient use of Graphical Processing Units, pipelining data from slow storage to CPU and GPU RAM, experiment design and monitoring, and ML models (including Deep Neural Networks).

For more information, please contact Andy Fagg at andrewhfagg@gmail.com

This Community of Practice aims to integrate expertise in artificial intelligence, machine learning, and visual analytics with domain sciences in ecology and hydrology to find elegant solutions that break down analytical barriers in understanding complex ecological and hydrological problems. It directly addresses the vision of the DOE Office of Biological and Environmental Research and the Climate and Environmental Science (CESD) division on improving our systems-level understanding and predictability through integrative theory, modeling, and experiment over various spatial and temporal scales. During the CoP, we will form research groups and discussion panels with participants to share research interests and emerging funding opportunities to foster long-term interdisciplinary research collaborations.

For more information, please contact Pierre Kirstetter at pierre-emmanuel.kirstetter@ou.edu

AI/Machine Learning and Cancer