Taylor Howell 🐪

I am an engineer and researcher working on embodied intelligent systems. My expertise and interests include: robotics, control theory, physics simulation, numerical optimization, and machine learning.

I completed my PhD at Stanford University, working with Zachary Manchester in the Robotic Exploration Lab on optimization-based tools for robotics applications including: simulation, planning, and control for drone coordination, legged locomotion, and dexterous manipulation.

In industry, I worked as a research scientist intern at DeepMind with Yuval Tassa where I led development of MuJoCo MPC, an interactive tool for real-time robot behavior generation using predictive control that runs on a laptop. Prior to that I was a research intern at Google Brain with Vikas Sindhwani working on planning with differentiable dynamical systems and related experiments with JAX.

As an undergraduate at the University of Utah, I worked on: control for magnetically actuated microrobots and fabricated scaled swimmers for experimentation with Jake Abbott at the Telerobotics Lab; wireless power transfer for aerial robots for my senior team project; developed mechatronics as part of a personalized medicine system for ovarian-cancer treatments with Bruce Gale at the State of Utah Center of Excellence for Biomedical Microfluidics. I also spent the summer after finishing my bachelor's degree sharing my love for programming and robotics by teaching kids at the University of Utah GREAT camp.

I love traveling (+35 countries so far!), films (anything from arthouse to romantic comedies to classics), coffee (always black), and sometimes I go for runs.