Travel: Workshop for Women in Machine Learning
- Institution
- Smith College, MA
- Principal investigator
- Katherine Kinnaird
- Funding
- $50K
- Duration
- 2023–2025
Moonbase score
Still being scored
Abstract
This grant supports the annual workshop for Women in Machine Learning (WiML). This one-day workshop brings together female researchers in industry and academia, postdoctoral fellows, and graduate students from the machine learning community to exchange research ideas and build mentoring and networking relationships. It will foster collaboration within the machine learning community, featuring not only cutting-edge ideas from established researchers but also from students, who will present their own research and receive valuable feedback from both senior researchers and their peers. We expect that new connections and research collaborations will be established, and will help to advance the state-of-the-art of the field. This workshop will provide a forum for female graduate students, postdoctoral fellows, junior and senior faculty, and industry and government research scientists to exchange research ideas and establish networking and mentoring relationships. Undergraduates, particularly those who are interested in pursuing graduate school or industry positions in machine learning, are also welcome to attend. 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 working in the field of machine learning. The workshop will also benefit the wider machine learning community: The WiML website includes a directory of over 400 women for organizations looking for female invited speakers. Co-locating with a major machine learning conference (a) enhances the visibility of the participants in the broader community and (b) facilitates travel for WiML attendees to stay on for the main conference. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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