NSF CISE Advisory Committee

Photo of Rutenbar

I currently co-chair the National Science Foundation’s Advisory Committee (AC) for the Directorate on Computer, Information Science & Engineering (CISE). As noted on the CISE AC website, the AC “provides advice on the impact of NSF support policies and programs on the CISE community; provides oversight on program management and performance; and provides advice to the Assistant Director for CISE on special issues, forming ad hoc subcommittees to carry out needed studies as necessary.” One such committee that I co-chaired with Dr. Francine Berman of Rutgers, looked at the ways to realize the potential of Data Science across all fields of NSF.  This led to a CACM article, and feature story.


APLU Committee on Research (COR)

Photo of Rutenbar lecturing in front of a projection screen. The slide on the projection screen reads, "Responding to Undue Influence and Security Concerns on Campus".


I’m currently an elected member of the Association of Public & Land Grant Universities (APLU) Council on Research (COR). As noted on the APLU COR website, COR “monitors government rules and regulations affecting campus scientific and technical research, and those concerning graduate education.” I currently co-lead an ad hoc advisory group focused on Research Security, with particular focus on managing foreign collaborations and engagements, with Dr. Susan Martinis, the VCR at the University of Illinois at Urbana Champaign.

National Academies Work

I’ve participated in various roles in US National Academies studies, notably involving computer science and data science, and issues around education. Below are a few contributions to these studies:

  • talk about the rising Illinois CS+X program was delivered at the 2016 US National Academies Workshop on the Growth of CS Undergrad Enrollments.
  • I served on a National Academies study focused on “Envisioning the Data Science Discipline: The Undergraduate Perspective”. The charge was to “… set forth a vision for the emerging discipline of data science at the undergraduate level. It will emphasize core underlying principles, intellectual content, and pedagogical issues specific to data science, including core concepts that distinguish it from neighboring disciplines.” Learn more by reading the resulting report.