Presentation #102.07 in the session Community & Profession.
In recent years, NASA has sought to expand its pool of potential proposal reviewers in an effort to incorporate a new generation of diverse astrophysicists. In response to the Astro2020 Decadal, survey we collected 10+ years of institutional data across many ROSES calls. To improve the diversity of the scientific merit review panels, we have developed a Python-based routine to query NASA ADS API (via a third-party ADS package) and determine the expertise of potential NASA reviewers. Focusing on researchers at Minority Serving Institutions (MSI) and smaller research institutions (“R2s”), we query their names and affiliations. The resultant publication data is processed through a series of customizable filters (e.g. publication years, type, and journal names). Through the relevant paper metadata we extract the author’s collection of abstracts and create a series of n-grams that can then be scrutinized to determine the astronomical expertise of the author for consideration by NASA program scientists. The code is made publicly available and has been also modified to run on other user-determined lists (e.g. NHFP, NPP Fellows).