Xinyi Chen, Erin Grant, Kristy Choi, Krystal Maughan, Xenia Miscouridou, Judy Hanwen Shen, Raquel Aoki, Belén Saldías (Lab for Social Machines), Mel Woghiren, Elizabeth Wood
Machine learning is one of the fastest-growing areas of computer science research. Search engines, text mining, social media analytics, face recognition, DNA sequence analysis, speech and handwriting recognition, and healthcare services are only some of the applications in which machine learning is routinely used.
Despite the wide reach of machine learning and the branches of theory and variety of applications it covers, the percentage of female researchers is lower than in many other areas of computer science. Most women working in machine learning rarely get the chance to interact with other female researchers, making it easy to feel isolated and hard to find role models.
The annual Women in Machine Learning Workshop is the flagship event of Women in Machine Learning. This technical workshop gives female faculty, research scientists, and graduate students in the machine learning community an opportunity to meet, network and exchange ideas, participate in career-focused panel discussions with senior women in industry and academia, and learn from each other. Underrepresented minorities and undergraduates interested in machine learning research are encouraged to attend. We welcome all gender identities at the workshop; however, all formal presentations (e.g., talks or posters) are given by women and/or nonbinary people. We strive to create an atmosphere in which participants feel comfortable to engage in technical and career-related conversations.
Now in its 15th year, the 2020 workshop is co-located with the virtual NeurIPS 2020 conference and will take place on December 9th, 2020.