Daniel Siegel

I'm a computer engineer and robotics researcher based in San Francisco. Last summer, I left Tufts University to work on robotics full-time. At , I researched human motion data and built hardware that measures movement accurately so robots can learn from it. I also run Robonia warehouse in San Francisco.

I believe imitation depends on the quality of the examples. Better sensors can capture the motion data robots need to learn. I'm interested in building those tools to be accurate and still practical to deploy at scale.

Previously, I built humanoid robots at and worked on ML for low-power AI hardware at .

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.

Featured Projects

I've also worked on ML for DSP, drones/RF, warehouse automation, physical and industrial design, DFMA/DFAM, and materials research. For more info, email me! daniel@integralmimetics.com

Academics

LaTeX Notes  -  Calculus II / Embedded Systems

Clubs & Societies - Tufts IEEE, Jumbo Juggling / Fire & Flow Club, Mitre eCTF, Tufts Solar Vehicle Project (TSVP), Music Production Club, Society of Physics Students

Lab Affiliations

Tufts IDEALab (Prof. James Intriligator), Harvard Innovation Labs, Nolop FAST Facility, Stanford Pyramidal Lab (Prof. Mark Schnitzer), Stanford Biomechatronics Lab, De Anza Additive Manufacturing Lab

  • Emerging Tech Winner - JumboHack Hackathon
  • OctoGrasp
    • Grand Award - International Science and Engineering Fair (2nd Place in Biomedical Engineering)
    • Grand Prize - Best of Championship (Physical Sciences) - Synopsys Silicon Valley Science and Technology Championship
    • 1st Award, Physical Science and Engineering Category - Synopsys Silicon Valley Science and Technology Championship
    • IBM Award
    • Office of Naval Research - United States Navy / US Marine Corps Award
    • IEEE Electro-Technology Award
    • 2nd Place, California Science and Engineering Fair
  • Silicon Valley Engineering Council Award (dinner w/ Jensen Huang lol)
  • Surround3
    • Castro Family Award for Best Physical Science Projects - Synopsys Silicon Valley Science and Technology Championship
    • 1st Award, Physical Science and Engineering Category - Synopsys Silicon Valley Science and Technology Championship
    • Synopsys Outreach Foundation n+1 Prize
    • Nominated to compete - Broadcom MASTERS
    • Honorable Mention, California Science and Engineering Fair
  • Weights & Biases Award - WeaveHacks
  • 3rd Place - Tufts Robot-a-thon
  • Honorable Mention - Code Metal Smart Cities Hackathon
  • ONR Medallion, United States Navy and Marine Corps
  • Video Design Award - First Robotics Competition (FRC)
Contact

"The best way to predict the future
is to invent it." - Alan Kay