Daniel Siegel
"The best way to predict the future is to invent it." - Alan Kay
update (fall 2025) - I've dropped out of Tufts University to work on robotics full-time. I'm at 
focused on reliable robot motion and perception in everyday settings.
I'm a computer engineer and robotics researcher based between Woodside, Palo Alto, and San Francisco. Previously I worked on ML for low-power AI hardware at FemtoAI, designed quantum circuits at Katmai Computing, and built humanoid robots with Tangible.
I am curious about implicit feedback loops, especially in biomimetic systems. I'm especially interested in René Girard's Mimetic Theory and what it looks like when you extend mimetic dynamics to complex systems.
Mimetics is learning by imitation, the oldest way any creature or thing has ever learned, and now applied to the newest learners. The bottleneck is the quality of the data we use to teach. So I design the hardware and software that captures signals with enough fidelity for complex systems to learn from them.
At Stanford, I contributed to the Biomechatronics Lab's self-steering cane project and designed adjustable manipulator fixtures for Dr. Mark Schnitzer's Lab. I also developed several projects with Tufts' IdeaLAB.
