Machine learning is one of the fastest growing areas of computer science research. Search engines, face recognition, DNA sequence analysis, speech and handwriting recognition, credit card fraud detection, premature baby monitoring and autonomous locomotion are just some of the applications in which machine learning is routinely used.
Despite the variety of machine learning techniques and applications, 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.
This one-day workshop, which is co-located with the Grace Hopper Celebration of Women in Computing, gives female faculty, research scientists and graduate students in the machine learning community an opportunity to meet, exchange ideas and learn from each other, while providing women in other areas of computer science an opportunity to learn about cutting-edge research in a growing field.
Bringing together women from different stages of their careers gives established researchers the opportunity to act as mentors, and enables junior women to find female role models in the field of machine learning. Additionally, the workshop provides a forum for establishing new connections and research collaborations, thereby advancing the state-of-the-art.
