Open House: AI In Robotics

Virtual Open House for AI in Robotics

Title: AI in Robotics: Learning Algorithms, Design and Safety
Date: Friday, April 26, 2024
Time: 12 PM EDT
Duration: 60 minutes
Instructors: Pulkit Agrawal and ChuChu Fan

The advancement of generative AI is revolutionizing robotics. Task planning, simulator design and reward design look much different today thanks to progress in large language models, diffusion models, and other generative AI tools. To continually optimize robotics safety and efficiency, engineers must have a deep understanding of the latest advancements in machine learning methods.

AI in Robotics: Learning, Algorithms, Design, and Safety is a three-day on-campus course led by MIT Assistant Professors Pulkit Agrawal and ChuChu Fan. Participants will acquire hands-on experience applying generative AI, large language models, simulators for training control policies, and more to better optimize their robotics efforts to solve their organization’s objectives.

At this virtual open house, you will:

Meet Pulkit Agrawal, assistant professor of electrical engineering and computer science at MIT
Explore the learning outcomes, such as how to apply LLMs and generative AI to robotics, optimizing the robot design process, multi-agent control, and more.
Envision how this course, tours of MIT labs, and the accomplished peers you network with during the week can bolster your understanding of robotics and solve your unique work challenges
Ask your questions during a live Q&A session

Not able to make the live Open House?

Register today

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About the Faculty

Pulkit Agrawal is assistant professor of electrical engineering and computer science at MIT and leads the Improbable AI Lab, part of the Computer Science and Artificial Intelligence Lab at MIT and affiliated with the Laboratory for Information and Decision Systems. Agrawal also co-founded SafelyYou, an organization that builds fall prevention technology, and the AI Foundry, an incubator for AI startups.

Chuchu Fan is an Assistant Professor in the Department of Aeronautics and Astronautics (AeroAstro) and Laboratory for Information and Decision Systems (LIDS) at MIT. Before that, she was a postdoc researcher at Caltech and got her Ph.D. from ECE at the University of Illinois at Urbana-Champaign. She earned her bachelor’s degree from Tsinghua University, Department of Automation.

Why MIT Professional Education?

MIT Professional Education delivers timely, relevant programs to a global audience of scientists, engineers, technicians, managers, consultants, and others from industry, government, the military, non-profit, and academia. The MIT Professional Education mission is to provide a gateway to renowned MIT research, knowledge and expertise for those engaged in science and technology worldwide, through advanced education programs designed for working professionals. The programs are delivered by MIT faculty and promote technical excellence through ongoing educational engagement with communities of practice. Under the leadership of the School of Engineering, MIT Professional Education supports the development of creative leaders equipped to address complex problems.

For more information visit professional.mit.edu