Matthew S
Research Intern at Stanford University
Menlo Park, California, United States
Summary
👤
Senior🎓
Top SchoolMatthew S is a CS PhD student at Stanford and a research intern at Applied Intuition with eight years of experience building robotics, autonomy, and AI systems. His work spans dexterous manipulation, tactile Gaussian Splatting, and large-scale 4D in-the-wild pretraining for autonomy, blending hands-on robotics (Franka Panda, ROS) with ML research. Previously he shipped analytics and AI services at Microsoft’s Customer Experience Platform and contributed to publishable research on GANs for building energy modeling and proximity perception for human-robot interaction. He co-founded a drone delivery startup and has a track record of turning research prototypes into deployed systems and open-source artifacts, including a large release of EnergyPlus building models. Based in Menlo Park, he pairs rigorous academic training and a perfect undergraduate GPA with practical system-building across industry and lab settings.
8 years of coding experience
6 years of employment as a software developer
4.26 GPA, 4.26 GPA at Legacy High SchoolBachelor of Science - BS, Computer Science, Minor in Chinese, 4.00 GPA, Bachelor of Science - BS, Computer Science, Minor in Chinese, 4.00 GPA at University of Colorado BoulderDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Stanford University
Chinese, Spanish, German
Stackoverflow
3reputation
196reached
0answers
2questions
Github Skills (170)
robotics10
neural-rendering10
jetson-xavier10
3d-reconstruction10
classification10
cooperation10
robot10
interaction10
openmmlab9
mask-rcnn9
actor-critic9
object-detection9
computer-vision9
magenta9
toolbox9
Programming languages (11)
Github contributions (5)
peasant98/MSResume
Mar 2018 - Oct 2023
Contributions:63 pushes, 1 branch in 5 years 7 months
watakandai/pfrl
Aug 2020 - Aug 2021
PFRL: a PyTorch-based deep reinforcement learning library
Contributions:71 reviews, 338 commits, 48 PRs in 1 year
pytorchactor-criticdeep-learningreinforcement-learningdeep-reinforcement-learning
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