Marcus Greiff
Research Scientist at Toyota Research Institute
Sunnyvale, California, United States
Summary
👤
Senior🎓
Top SchoolMarcus Greiff is a research scientist with 11 years of experience applying control theory, numerical analysis, and Bayesian sensor fusion to real-world robotics and automotive problems. Currently at Toyota Research Institute, he develops perception, localization, and control algorithms for vehicles operating at the limits, building on a PhD in control theory from Lund University. His work spans academia and industry—from marginalized particle filters and multi-receiver GNSS research at MERL to embedded sensor-fusion and Kalman-filter integration for the Crazyflie open-source quadrotor firmware. Marcus combines rigorous theoretical foundations with production-minded C and MATLAB implementations, and has a track record of improving robustness through principled noise and multipath models. Based in Sunnyvale, he brings both deep algorithmic insight and hands-on embedded experience to safety-critical autonomy challenges.
10 years of coding experience
3 years of employment as a software developer
Master of Science (M.Sc.) in Engineering Physics Automatic control, Master of Science (M.Sc.) in Engineering Physics Automatic control at The Faculty of Engineering at Lund UniversityDoctor of Philosophy (PhD) Control Theory - Mathematics, Doctor of Philosophy (PhD) Control Theory - Mathematics at Lund University
Github Skills (9)
c1710
firmware10
embedded10
c1110
sys10
kalman-filter10
iot-devkit9
iot9
quad8
Programming languages (5)
Github contributions (5)
bitcraze/crazyflie-firmware
Nov 2016 - Dec 2016
The main firmware for the Crazyflie Nano Quadcopter, Crazyflie Bolt Quadcopter and Roadrunner Positioning Tag.
Role in this project:
Embedded Systems Engineer / IoT Developer
Embedded Systems Engineer / IoT DeveloperContributions:6 commits, 3 PRs, 12 comments in 3 days
Contributions summary:Marcus's contributions primarily revolve around integrating a VL53L0X time-of-flight (ToF) sensor into the Crazyflie firmware, enabling elevation measurements for the drone. They added the necessary drivers, data structures, and Kalman filter integration to process the ToF data, refining the implementation across several iterations. The user also implemented a measurement noise model to improve the robustness and accuracy of the elevation estimates.
boltfirmwarecrazyfliezeroquadcopter
mgreiff/crazyflie-project
Mar 2016 - Jan 2017
Contributions:95 commits, 98 pushes, 1 branch in 11 months
quadcoptercrazyfliesimulation
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