Broadening Student Participation to the 7th Annual Learning for Dynamics and Control Conference (L4DC25); Ann Arbor, Michigan; 4-6 June 2025

This grant fosters excellence and promotes student engagement and participation at the 7th Annual Learning for Dynamics and Control (L4DC) Conference, an event fostering interdisciplinary research at the intersection of machine learning, dynamical systems, control theory, and reinforcement learning. L4DC is committed to expanding the boundaries of model-based design through the integration of massive real-time data, both temporal and spatial, prompting a necessary reevaluation of established disciplinary foundations.

L4DC 2025 will feature an array of presentations, including keynote addresses, oral presentations, and poster sessions, with a special emphasis on contributions that bridge multiple research domains. By facilitating these intersections, the conference not only advances the scientific area but also fosters a vibrant community where students and seasoned researchers collaboratively push the frontiers of knowledge in dynamics and control.

The objective of this NSF-funded initiative is to substantially broaden student involvement in L4DC and enrich their academic and professional development, with a particular focus on students from underrepresented backgrounds. This grant will provide comprehensive support through several targeted initiatives. First, 25 to 40 travel grants will be offered to ensure broad student participation from across the country.

These grants are aimed at students who might otherwise be unable to afford attendance, thus fostering a more inclusive academic environment. Additionally, the conference will host Industry Booths and facilitate networking events, providing critical career insights and networking opportunities that students can use to bridge the gap between their academic pursuits and future professional roles.

By aligning with NSF's broader goals, this award supports the integration of education and research, preparing a new generation of researchers equipped to tackle emerging challenges at the crossroads of learning, dynamics, and control.

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.