Travel: NSF Student Travel Grant for the Seventh Conference on Machine Learning and Systems (MLSys 2024)
- Institution
- Carnegie Mellon University, PA
- Principal investigator
- Phillip Gibbons
- Funding
- $25K
- Duration
- 2024–2025
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Still being scored
Abstract
The 2024 Machine Learning and Systems (MLSys) conference is the seventh in an established series of symposia that brings together industry, faculty, and student researchers working on machine learning and computer systems. The conference is held at the Santa Clara Convention Center in California, United States, May 13th to 16th, 2024. The program includes research papers from academia and industry, three keynote talks by internationally recognized leaders in the field, and a day-long young professionals symposium. This award provides funding to help cover the travel costs for U.S.-based graduate and undergraduate students to attend the conference. Students receiving travel support benefit from the opportunity to engage in technical, professional, educational and social exchanges. The conference serves as an open forum to exchange research results and develop new ideas, as well as an educational platform to expose students to new research methodologies, tools, and infrastructures, and as a social event to network and prepare students as future researchers and leaders. The conference targets research at the intersection of machine learning and systems, which historically has not been particularly well addressed by existing Machine Learning or Computer Systems focused conferences. The conference elicits new connections amongst these fields, including identifying best practices and design principles for learning systems, as well as developing novel learning methods and theory tailored to practical machine learning workflows. The award will enable the participation of students who would otherwise be unable to attend, particularly students under-represented in the machine learning and computer systems fields. Moreover, the undergraduate students who are supported gain valuable exposure to the forefront of research in these areas, encouraging them to further their education by continuing on to graduate school. 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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