Tag Archive: CRA-W

Articles relevant to the CRA Committee on the Status of Women in Computing Research (CRA-W).

Expanding the PipelineExpanding the Pipeline

Expanding the Pipeline: The Participation and Challenges of Community College Students in Undergraduate Research

Convention tells us that research involves a selection of topic, literature review, framework development, refining/defining your research question, developing a design, collecting data, analyzing data, and drawing conclusions, but at a community college the formality cannot always be used as a rule, but as a guideline for developing a realistic, learning opportunity. Community college participation in undergraduate research is an important part of education, but can easily fall by the wayside to address life challenges often faced by community college students. However, given the opportunity to participate, research can be a rewarding and valuable skill that should be afforded to more students.


Expanding the Pipeline: CRA-W Expands Research Mentoring at the 2018 Grace Hopper Celebration of Women in Computing

The 2018 Grace Hopper Celebration of Women in Computing (GHC) broke its attendance records again, with more than 20,000 participants gathering in Houston, Texas, from September 26th through September 28th, and CRA-W also broke its attendance records with a variety of programs for GHC attendees interested in research. From talks, panels, and mentoring circles to the CRA-W Research Scholars Program to poster presentations and sponsorship of other sessions, CRA-W played an important role at the conference.

CERP InfographicCERP Infographic

Participants in the CRA Grad Cohort for Underrepresented Minorities + Persons with Disabilities Report Stronger Professional Skills After Attending the Workshop

In 2018, CRA launched the Grad Cohort for Underrepresented Minorities + Persons with Disabilities (Grad Cohort URMD) workshop. CERP found that compared to before the workshop, participants reported stronger knowledge about a number of professional skills after attending Grad Cohort URMD. Applications for the 2019 workshop will open October 2018.


Expanding the Pipeline: iAAMCS Releases Guidelines for Successfully Mentoring Black/African-American Computing Sciences Doctoral Students

These guidelines were established to articulate successful strategies for mentoring African-American doctoral students in Computing Sciences (CS). iAAMCS defines “student mentoring” as the process of supporting, encouraging and guiding students’ academic and social progress with the goal of facilitating career and personal development. Grounded in project-based results and similar empirical research, the following guidelines emerged: (1) recruit strategically, (2) establish community, (3) foster a research culture, (4) provide holistic advising, (5) provide funding and (6) promote professional development. iAAMCS hopes that institutions, departments and faculty use these guidelines to bolster the participation of African-American students pursuing doctoral degrees in CS.

Although the iAAMCS Guidelines serve as best practices for mentoring African-American students in computing, these strategies are useful for optimal mentoring all students.

Ayanna HowardAyanna Howard

Congratulations to Ayanna Howard – 2018 Richard Tapia Award Winner

CRA and CRA-W Board Member Ayanna Howard was recently named the recipient of the 2018 Richard A. Tapia Achievement Award for Scientific Scholarship, Civic Science and Diversifying Computing from the Center for Minorities and People with Disabilities in Information Technology (CMD-IT). “The Richard A. Tapia Award is awarded annually to an individual who demonstrates significant research leadership and strong commitment and contributions to diversifying computing.

Carla BrodleyCarla Brodley

CRA Board Member Highlight: Carla Brodley

For the past 30 years I have had two passions – machine learning (ML) that makes a difference in the real world and increasing diversity in computer science (CS).  For the first 26 years, I focused on my first passion and developed new approaches to ML though applications to remote sensing, neuroscience, digital libraries, astrophysics, content-based image retrieval of medical images, computational biology, chemistry, evidence-based medicine, detecting lesions in the MRIs of epilepsy patients, and predicting disease progression for MS patients. For the last four years, my focus has been on my second passion: increasing diversity in CS.