Copy
View this email in your browser
 
Math and Statistics

 

Collection and analysis of data on Earth's subsurface have been important throughout U.S. history for developing the nation's energy, mineral, and water resources, and for monitoring potential environmental hazards. However, ownership of these datasets is dispersed across private industry, government, academic researchers, and others, each with different use cases and approaches to data collection and processing. The lack of data sharing and common data collection, curation, and analysis standards presents a serious barrier to improved scientific understanding of the subsurface. 

Advances in machine learning and artificial intelligence are creating opportunities for examining rich subsurface datasets to improve scientific and public understanding of the subsurface and to support development, stewardship, and management of subsurface resources in an economically and environmentally sound way. Join us for a meeting and webcast on June 6, 2019 from 10am to 4:30pm ET where participants will discuss progress, challenges, and opportunities in machine learning and artificial intelligence as applied to subsurface datasets. 
 
Register to Attend In Person or Online


AI and Machine Learning to Advance Environmental Health Research and Decisions: Workshop and Webcast on June 6-7


This June 6-7 workshop will explore emerging applications of AI and machine learning in environmental health research - characterizing sources of pollution, predicting chemical toxicity, estimating human exposures to contaminants, and identifying health outcomes.  Through the lens of social trust, workshop participants will examine questions about transparency, data availability, bias, and reproducibility, among several others interrelated topics. Participants will also discuss the advantages and barriers to using AI and machine learning to inform environmental and public health policies and regulations. Held in Washington, DC and webcast live, the meeting will feature presentations, panel discussions, and a hands-on learning sessions to engage scientists and decision makers in these important, cross-disciplinary issues. 
 
Register to Attend In Person or Online


Symposium on Data, Modeling, and Policy Making to Address the Opioid Epidemic


Opioid use disorder is one of the biggest public health challenges facing the United States, and local and national policy makers are striving to develop interventions to mitigate its impact. Robust data and analyses are fundamental to understanding the extent of the epidemic and to developing, evaluating, and improving policy responses. However, there are many challenges related to data collection (e.g., completeness, timeliness) and modeling for local and national policy interventions. Join the Committee on Applied and Theoretical Statistics on June 10, 2019 from 1-5pm ET for a half-day discussion exploring current practices, challenges, and opportunities for using data, modeling, and policy making to address the opioid epidemic.
 
Register to Attend In Person or Online

Next Mathematical Frontiers Webinar on June 11:
The Mathematics of Transportation


Join the National Academies of Sciences, Engineering, and Medicine for a webinar series featuring exciting and upcoming mathematics research across an array of topics.  In the next webinar on June 11 at 2pm ET, Professors Alain Kornhauser and Pascal Van Hentenryck will discuss mathematical approaches that inform transportation policies and improve transportation networks.  For more information and a complete list of all upcoming webinars, please visit our registration page.
 
Register for a Math Frontiers Webinar

Roundtable on Data Science Postsecondary Education:
Data Science Education at Two-Year Colleges


The National Academies of Sciences, Engineering, and Medicine will host a half-day virtual workshop focusing on data science education at two-year colleges on June 12, 2019 from 12-5pm ET. This online meeting will bring together data scientists and educators in academia, government, and industry to discuss: (1) current efforts in developing data science curricula and programs at two-year colleges, (2) opportunities for professional development in data science education, (3) strategies for building partnerships with nearby four-year and Master’s granting institutions, and (4) techniques for understanding the needs of local employers.

Learn more about the roundtable and watch past meetings at nas.edu/dsert.
 
Register to Attend Online


About Math and Statistics at the National Academies


The Board on Mathematical Sciences and Analytics (BMSA) leads activities in the mathematical sciences at the National Academies in topic areas including from applied mathematics, scientific computing, and risk analysis. 

The Committee on Applied and Theoretical Statistics (CATS) organizes studies and events focusing on the statistical sciences, big data and data science, statistical education, the use of statistics, and issues affecting the field. CATS occupies a pivotal position in the statistical community, providing expertise in methodology and policy formation.

 
Copyright © 2019 National Academy of Sciences, All rights reserved.


Want to change how you receive these emails?
You can update your preferences or unsubscribe from this list.