This is the first Business, Industry and Government (BIG) MRC Conference: Graph and hypergraph models are powerful tools for understanding the kinds of critical systems studied at the National Laboratories, including computer networks, critical infrastructure systems, systems biology, and social networks. This MRC will focus on developing models and analytical methods to enable data-driven exploration and analysis of such systems through the lens of graphs and hypergraphs by addressing several challenges. One such challenge we will address is developing rigorous sparse models that can reproduce with high probability known features of realistic data sets. Most existing random graph models either cannot capture the simultaneous sparsity and connectivity of real world data sets or they are too specialized to a single application and not generalizable. A concurrent challenge that we will address in the workshop is to generalize graph theoretic concepts to higher order hypergraphs, and develop native hypergraph analytical methods, without sacrificing computational tractability. To mimic the organization of research teams at Business, Industry, and Government (BIG) organizations we will strive to have interdisciplinary teams in which team members will have different strengths that come together to solve a problem. For example, some team members will be solving theoretical challenges while others implement algorithms efficiently. This workshop will also include interactive sessions on preparing for BIG careers.
Read the organizers’ article in the February Notices of the AMS for more information.
Please note that you may apply to more than one MRC conference if they match your research interests. A separate application is needed for each one. However, you can only be selected as a participant in one conference.
Applications were accepted on MathPrograms with a deadline of February 15, 2022. No new applications are being accepted at this time.
For questions about the application process, please contact the Programs Department at the AMS.