GENDiR Seminar Series: Transfer Learning for Robots and for Humans

Digital flyer for event. Picture of Tabitha and GENDiR logo. No additional information.

Transfer learning — how information that is learned in one context can be transferred for use in a different setting — has far-reaching consequences for agents operating under domain shifts. This talk will present lessons learned in transfer learning for robots and for humans. First, the methodology of structural sim-to-real transfer for robots will be presented, which aims to learn the causal structure of a robot manipulation policy or skill in simulation first before deployment on a real robot system. This section of the talk will summarize two algorithms in this area, CREST and SCALE, that were recognized by NCWIT as a Collegiate Award Honorable Mention. I will then draw parallels to how transfer learning can empower navigation of domain shifts in humans using my gender and physical disability transitions as examples. This section will identify human attributes and characteristics, such as empathy, compassion, understanding, and appreciation of differences, that bolster other humans experiencing life transitions. Lastly, I will summarize work done towards teaching such attributes for first-year Ph.D. students at Carnegie Mellon University through the development and launch of 15-996: Introduction to Justice, Equity, Diversity and Inclusion in Computer Science.

Zoom link

Diversifying the STEM pipeline: Evidence from STEM summer programs for underrepresented youth

Dr. Silvia Robles

Underrepresentation of Black and Hispanic workers in STEM fields contributes to racial wage gaps and reduces innovation and economic growth. Billions of dollars a year are spent on “pipeline” programs to increase diversity in STEM, but there is little rigorous evidence of their efficacy. We fielded a randomized controlled trial to study a suite of such programs that are targeted to underrepresented high school students hosted at an elite, technical institution. Students offered seats in the STEM summer programs are more likely to enroll in, persist through, and graduate from college. The programs also increase the likelihood that students graduate with a degree in a STEM field, with the most intensive program increasing four-year graduation with a STEM degree by 33 percent. The shift to STEM degrees increases potential earnings by 2 to 6 percent. Program-induced gains in college quality fully account for the gains in graduation, but gains in STEM degree attainment are larger than predicted based on institutional differences.

From the speaker’s bio

Silvia Robles is an economist and researcher at Mathematica. Prior to joining Mathematica in August 2019 Silvia worked at the Ford School of Public Policy at the University of Michigan, both as a postdoctoral fellow, and as an affiliate of Poverty Solutions. She earned her PhD in economics in 2016 from Harvard University. Her previous research has focused on underserved populations in education, including low-income and minority students. Specifically, she has studied outreach models to encourage the transition from high school to selective universities and STEM careers, as well as the impact of oversubscribed courses in community colleges, and the effectiveness of for-profit charter schools.

Registration link