NYU and NYU Abu Dhabi researchers are working on user-centric gender rewriting in NLP, especially for Arabic. They are building an Arabic Parallel Gender Corpus and developing models for gender rewriting tasks. The work aims to address representational harms caused by NLP systems that don't account for user preferences regarding grammatical gender. Why it matters: This research promotes fairness and inclusivity in Arabic NLP by enabling systems to generate gender-specific outputs based on user preferences, mitigating biases present in training data.
A panel discussion on women in biology was held as part of the 2016 Fall Enrichment Program at KAUST. Jasmeen Merzaban, Ashwag Abdullah Albukhari, Bettina Berger and Peiying Hong were the speakers. The event featured successful female scientists sharing their experiences. Why it matters: Showcases KAUST's commitment to promoting women in STEM fields and providing a platform for their voices.
KAUST hosted a regional Women in Data Science (WiDS) conference, part of a global event held at over 100 regional institutions led by Stanford University. The KAUST event featured exclusively female speakers and aimed to highlight data science research and applications. KAUST is launching a 'Women in Data Sciences and Technology' initiative to support women's education and careers in the field. Why it matters: This initiative can help address the underrepresentation of women in data science in Saudi Arabia and the broader region.
KAUST celebrates 15 years since its establishment as the first mixed-gender university in Saudi Arabia, highlighting its role in championing women in science. Numerous KAUST female graduates have achieved success in academia, government, and entrepreneurship. Programs like KGSP and the Ibn Rushd fellowship have been instrumental in nurturing talent and empowering women in STEM. Why it matters: KAUST's focus on gender equality and STEM education serves as a model for advancing women's contributions to technological and economic development in the region.