The World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022); The Fourth

Abstract

ONR Combined Proposal Abstract (AIM2022, DMMM4, and Hansson Symposium):The Minerals, Metals, and Materials Society (TMS) has a stron,g history of developing specialty meetings and conference symposia to support the advancement of technical sub-disciplines and areas, of cultural significance within the overall field of materials science and engineering (MSE). Both emerging and established topical, areas, such as Artificial Intelligence use within MSE and/or the study of environmental resistance materials, are critical to the p,rogression of the field as is the development of a diverse and skilled community of practitioners. In the vein, the following three,conferences/symposia look to advance the MSE community in each of the aforementioned areas by providing forums to share and dissemin,ate the latest research advances and case studies broadly. The inaugural World Congress on Artificial Intelligence in Materials and,Manufacturing (AIM 2022) is the first in a series of cross-disciplinary technical forums centered around the areas of materials mode,ling and simulation, experim,ld at Omni William Penn Hotel in Pittsburgh, Pennsylvania on April 3?6, 2022 with the goal of assembling AI and material/manufacturi,ng contributors to capture the current state-of-the-art, identify current gaps/barriers impeding optimized AI-assisted materials and, manufacturing efforts, and to set the stage for the future growth and application of AI within the materials and manufacturing disc,iplines worldwide. To address the deficiencies in diversity, equity, and inclusion that affect all of STEM as well as those unique t,o the MSE community, TMS has organized an ongoing series of Summit on Diversity in the Minerals, Metals and Materials Professions (D,MMM), previously held in 2014, 2016 and 2018. The fourth iteration (DMMM4) builds on the knowledge sharing, network development, and,ting & Exhibition (TMS2022) at the at the Anaheim Convention Center & Anaheim Marriott in Anaheim, California on March 2-3. Moreover,, TMS is launching this ?Resisting Degradation from the Environment: A Symposium Honoring Carolyn M. Hansson?s Research and Pioneeri,ng Experiences as a Woman in STEM? event to convene materials degradation stakeholders ? including researchers, educators, engineers,, and students ? for this cross-disciplinary, technical forum designed to share the latest research advances in the areas of corrosi,on, erosion, and wear of materials; durability of construction materials; corrosion and electrochemical techniques; techniques for m,easuring the amount of degradation; rust-resistant reinforcing materials; sustainable materials; cement and concrete; and materials,to maintain the integrity of structures. In addition, the participation of underrepresented groups (especially women) in the above m,aterials-related discipline will also be highlighted. Networking opportunities at all three events will offer attendees a chance to,informally discuss the latest developments in each respective area, while also making valuable professional connections. Student par,ticipation is greatly encouraged to give students exposure to recent advances in this field. This grant will support student, postdo,c, and young faculty participation; the student poster session; and other administrative costs. Each meeting is open to all interest,ed individuals and will attempt to provide the most advanced technical meeting possible, with a mixture of attendees from research a,nd development, industry, and education professions, representing both senior and junior investigators, post-doctoral trainees and s,tudents

Document Details

Document Type
DoD Grant Award
Publication Date
Sep 08, 2022
Source ID
N000142212710

Entities

People

  • Michael Rawlings

Organizations

  • Minerals, Metals & Materials Society
  • Office of Naval Research
  • United States Navy

Tags

Readers

  • Academic Conference Management
  • STEM Education

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy