ExpandAI Program Reviewer Volunteer survey Dear Review Volunteer, This survey is being conducted to ensure a high-quality review process for proposals submitted to the ExpandAI program. Volunteers recruited will have the opportunity for direct engagement, and better acquaintance with the ExpandAI program. Questions with an * require an answer. Question Title * Please enter your contact Information: First name: Last name: Question Title * Please enter your email address: Question Title * Please enter your institution name : Question Title * Please indicate your organizational affiliation here: Alaska Native Serving Institutions (ANSI) Hispanic Serving Institutions (HSI) Historically Black Colleges and Universities (HBCU) Predominantly Black Institutions (PBI) Native Hawaiian Serving Institutions (NHSI) Native American-serving Non-Tribal Institutions and Tribal Colleges and Universities(TCU) Other Minority-Serving Institutions (MSI) Other Question Title * If you have indicated ‘Other’, or ‘MSI Other’, please specify here: Question Title * Job title: (e.g., Assistant Professor, Research Scientist, etc.) Question Title * Please enter your homepage URL if available, otherwise leave blank: Question Title * Are you an investigator or senior personnel on an ExpandAI award? Yes No Question Title * If you answered "yes" in the above question, please specify the project title: Question Title * Are you an investigator or senior personnel on an AI Institutes award? Yes No Question Title * If you answered "yes" in the above question, please specify the project title: Question Title * Do you plan to submit a proposal to the ExpandAI Capacity Building Pilots (CAP) track in the next year? Yes No Not sure Question Title * Do you plan to submit a proposal to the ExpandAI Partnerships (PARTNER) track in the next year? Yes No Not sure Question Title * As a volunteer reviewer in ExpandAI, NSF may select you to review proposals on an “ad hoc” basis, meaning that you would be assigned a single proposal at a time, and be asked to return your review normally within two weeks. This review opportunity will start no earlier than mid-January 2023 when our first proposal submission window opens. Over a 12-month period, how many ad-hoc assignments are you willing to accept? More than 4 4 3 2 1 Not Ready to Review If you have any other preferences about ad hoc review invitations, please enter that here. Otherwise, leave blank: Question Title * NSF may also recruit you to review proposals in a “review panel”, meaning that you would be assigned several proposals to review and would meet with other reviewers and NSF staff virtually. Panels would make funding recommendations to the agencies. This review opportunity will be infrequent. No reviewer would be asked to serve on a panel in the program more than once in a year. Would you like to be contacted about opportunities to serve on an ExpandAI panel? Yes No thanks, don’t contact me about panels If you have any other preferences about panel review invitations, please enter that here. Otherwise, leave blank: Question Title * Please indicate the areas in which you are willing and qualified to review proposals. Establishing or administering education programs in colleges and universities Establishing or administering research programs in colleges and universities Establishing or administering research/computing infrastructure in colleges and universities Establishing or administering administrative infrastructure in colleges and universities Establishing or administering programs that increase participation of underrepresented minorities in education or research programs Other areas of specialty relevant to ExpandAI program - please specify below (e.g. research, teaching, administration) Question Title * Please provide a brief paragraph (3-4 sentences) summarizing your broad areas of disciplinary expertise as they relate to the ExpandAI program and your potential service as a reviewer. A sample paragraph is provided below as a guide to the types of content that should be included. Sample Faculty Expertise: Jane Doe holds a Ph.D. in Computer Science and has served as a faculty member in the Electrical Engineering & Computer Science department for ten years. Dr. Doe has managed several NSF-funded projects with a focus on data analytics and machine learning. She has published numerous conference papers and journal articles on the application of machine learning to the analysis of data in domains such as gene expression, biomedical implant design and emotions behind social media content. Done