This blog entry was reposted from the RSE stories and combines two posts.
Marina Kraeva is a Senior Research Computing Systems Analyst at Iowa State University and this year’s Early Career Program Subcommittee Chair. In this episode, Marina tells us about the history of the Early Career Program (ECP) at Supercomputing, the overarching goals of ECP, and what potential participants can expect to learn this year!
She encourages all professionals in their early career to apply for the program this year, taking place in Dallas, TX, as part of Supercomputing 2022. To apply, go to the Early Career Program page and click “Application Details.”
Members, allies and friends gathered together for the 13th Annual WHPC Workshop at ISC, as well as celebrated Early Career Research in HPC and the return of Diversity Day.
After two years online, the volunteers for Women in High Performance Computing (WHPC) were pleased to return in-person to ISC22 in Hamburg, Germany to present their thirteenth annual international workshop. Focused on providing a platform for the HPC community to discuss diversity and inclusivity issues, this year’s half day event was able to explore professional skills development, highlight women who are early in their careers of research, and engage with leaders and managers in the HPC to improve the inclusion and retention of diverse teams.
Having just earned her PhD in computer science from Georgia Tech University in 2021, Thaleia Dimitra Doudali was ready to embark on the next phase of her career.
At the urging of her advisor, Ada Gavrilovska, she applied for and was accepted into the Early Career Program for SC21 in St. Louis. The series of workshop-style sessions, pre-conference webinars and mentoring opportunities with experienced HPC professionals made a major impact on Thaleia during a transformative moment in her career.
Amador Valley High School Girls Who Code club (AVHS GWC) is a chapter of the national GirlsWhoCode organization. Through introducing girls to coding, they hope to inspire girls to pursue careers in STEM and close the gender gap in technology. For my third interview in my CS Students Interview Series, I talked with Anusha Maheshwari from AVHS GWC about their award winning GWC Summit.
When did you host the first GWC Summit and what inspired you to host the summit?
We first hosted the GWC Summit in March 2020, and we were motivated by patterns in the statistics when it comes to girls in STEM, particularly in the tech sector. Studies show that girls tend to be interested in STEM at around age 11 but drop off at 15 due to a lack of opportunities to further this interest. In today’s workforce, women make up only 25% of the computing workforce, so we wanted to do something to give younger girls the opportunity to explore tech in a supportive environment.
What are your major goals in hosting this summit?
The main goal of the summit is to develop younger girls’ interest in STEM and to show them how fun coding can be! We hope to encourage the next generation of coders to pursue their dreams and to instill in them the confidence that they can succeed in a STEM-based career.
Hello! For my second interview in my CS Students Interview Series, I talked to Audrey Ha, a winner of the 2020 Congressional App Challenge (CAC). The CAC is a prestigious prize that students can win by designing, creating, and coding an app that fits the district-specific challenge. The CAC was created by members of the US House of Representatives with the goal of teaching middle and high school age students how to code. For more information, check out the CAC website: https://www.congressionalappchallenge.us/about/.
Audrey Ha heard about this challenge through her local high school’s AP Java teacher. For the challenge, she focused her app on hurricane relief for two main reasons, the first being that the 2020 hurricane season was a record breaking one. Second, she thought that the speed and accuracy of machine learning could help the US organize relief efforts for natural disasters. Her award-winning app, SurveyHurricane, uses artificial intelligence to accurately and quickly detect damaged houses on aerial imagery of storm-impacted regions. Her app uses object detection and image classification neural networks to locate these damaged houses.