Title: The power of gradients in inverse dynamics problems Abstract: Traditionally, inverse dynamics refers to the problem of reconstructing the forces in a dynamic system from its kinematic motion and has wide applications in robotics, biomechanics, and computer graphics. This talk considers a more broadened definition of inverse dynamics that infers various computational design parameters of rigid-body, deformable-body, and fluidic dynamic systems. To solve this challenging problem, we develop a series of computational tools that unleash the full power of analytical gradients from a physics simulator in many non-traditional ways. First, we demonstrate the usage of gradients in exploring the shape and controller design space of rigid and soft robots. Next, we discuss transferring these computational designs to hardware and show the power of gradients in constructing digital twins of two such real-world robots: a rigid-body quadrotor and a deformable-body underwater robot. We end this talk by envisioning future opportunities for physics simulation gradients in computational fabrication, robotics, and machine learning. Bio: Tao Du is a Postdoctoral Associate at MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), working with Professor Wojciech Matusik and Professor Daniela Rus. His research aims to combine physics simulation, machine learning, and numerical optimization techniques to solve real-life inverse dynamics problems. Some of his representative works include building differentiable simulation platforms for graphics and robotics research, developing computational design pipelines for real-world robots, and understanding the simulation-to-reality gap of dynamic systems. His work has been published in top-tier graphics, learning, and robotics journals and conferences and has been featured by major technical media outlets. Before continuing at MIT as a Postdoctoral Associate, Tao Du obtained his Ph.D. in Computer Science from MIT in 2021 and his Master's in Computer Science from Stanford in 2015.