Learning To Design Robots
Join us for an engaging session exploring how AI, robotics, and wireless innovation are converging to transform the physical world. This hybrid event will be held at 370 Jay St Room 1201 and online. Mark your calendars and don't miss this opportunity to connect with leading researchers shaping the future of intelligent machines. Whether you're a student, professional, or enthusiast, this talk offers a front-row seat to the breakthroughs redefining how robots sense, learn, and act.
About the Talk
Title: Learning to Design Robots
Robots are starting to integrate into manufacturing, healthcare, and our daily lives. However, their development remains largely an iterative and intuition-driven process. Robot structures are typically designed, fabricated, and tested manually, followed by the development of control policies to achieve desired behaviors. This separation between design and control often leads to suboptimal performance and repeated manufacturing iterations.
This talk aims to overcome these challenges with a unified, data-driven co-design framework for robots — integrating simulation, optimization, and machine learning to automatically generate and evaluate robot designs along with their corresponding control policies. With an end-to-end approach, we can not only optimize for single tasks, but also uncover physically intelligent designs that simplify the control problem, enabling robust performance across varying use cases. This computational approach yields robots that are not only customizable but fundamentally more generalizable than human-designed baselines, paving the way to unlocking capabilities previously thought to be infeasible.
About the Speaker
Sha Yi is a Postdoctoral Scholar at the University of California San Diego, co-advised by Xiaolong Wang and Michael T. Tolley. She received her Ph.D. in Robotics from Carnegie Mellon University, where she was advised by Katia Sycara and Zeynep Temel. Her research interests include using computational methods to design and control novel robotic systems. She is a recipient of the CMU Presidential Fellowship and MIT EECS Rising Star 2025, and has industry experience with Amazon Robotics, Microsoft, and early-stage startups.
Visitor Information
This event is open to NYU students, faculty, and staff.
📍 Location: NYU Tandon School of Engineering, 370 Jay St Room 1201
📍 Zoom Link: https://nyu.zoom.us/j/94679794904?pwd=VzOlQraRGla3jW5QbWE6Y51SWIrP8v.1
Meeting ID: 946 7979 4904
Passcode: 266975