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5th Annual Learning for Dynamics & Control Conference
University of Pennsylvania
June 14-16, 2023

Over the next decade, the biggest generator of data is expected to be devices that sense and control the physical world.

The explosion of real-time data that is emerging from the physical world requires a rapprochement of areas such as machine learning, control theory, and optimization. While control theory has been firmly rooted in the tradition of model-based design, the availability and scale of data (both temporal and spatial) will require rethinking the foundations of our discipline. From a machine learning perspective, one of the main challenges going forward is to go beyond pattern recognition and address problems in data-driven control and optimization of dynamical processes. Our overall goal is to create a new community of people who think rigorously across the disciplines, ask new questions, and develop the foundations of this new scientific area. We are happy to welcome you to the University of Pennsylvania for the 5th annual L4DC.

Important Notes


Thank you to everyone who attended, tuned in, and participated this week! Take a look at the photo albums: Tutorials, Day 1, Day 2

Keynote Speakers

Aaron Ames (Caltech)

Rose Yu (UC San Diego)

Vikas Sindhwani (Google Brain)


Gold Sponsors

Silver Sponsors

Bronze Sponsors

Previous L4DC conferences

2022 4th L4DC at Stanford University, USA
2021 3rd L4DC at ETH Zurich, Switzerland (virtual)
2020 2nd L4DC at UC Berkeley, USA (virtual)
2019 1st inaugural L4DC workshop at MIT, USA

Code of Conduct

At the L4DC conference, we aim to create a safe, welcoming, and positive environment that facilitates exchanging ideas and forming professional connections. We expect all participants to be respectful towards each other. The conference will not tolerate harassment, discrimination, or personal attacks. Participants must stop any problematic behavior immediately. If you have concerns about problematic behavior, please notify the L4DC organizers at If you would like to notify the organizers anonymously, please use this form:

It is important to note that problematic communication can occur even without an explicit intent to offend or harass. Hence, we ask that all participants be mindful of how their comments can be interpreted, and err on the side of caution during formal and informal interactions.

Building the L4DC Community:

L4DC is interdisciplinary, bringing together researchers from control, robotics, machine learning, and optimization. One of the goals of L4DC is to build strong ties between these disciplines and enable active collaboration. Please consider taking on the constructive role of contributing to the community, instead of taking on a critical role to pinpoint flaws and weaknesses in the works of others during the conference. Focusing on weak points could cause others to retreat back to places where they feel comfortable, and instead of interdisciplinary interaction, we could end up with separate sub-clusters of people only interacting within their own fields. So please help us create a positive tone so that it is easy for the participants to leave their comfort zones, gain new perspectives, and form new collaborations