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Chang Chang is a robotics researcher passionate about mechanical design, control systems, and medical applications. His recent work focuses on image-guided flexible needle manipulation and FEM-based motion planning in ROS2 environments. He has published in IEEE RA-L, ISMR, and Micromachines, and led award-winning RoboMaster teams bridging mechanics and AI-based perception.
M.S.E. in Mechanical Engineering
Johns Hopkins University
B.Eng. in Mechanical Design, Manufacturing & Automation
Huazhong University of Science and Technology
Use this area to speak to your mission. I’m a research scientist in the Moonshot team at DeepMind. I blog about machine learning, deep learning, and moonshots.
I apply a range of qualitative and quantitative methods to comprehensively investigate the role of science and technology in the economy.
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scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license.
We propose a CT-registered, EM-tracked, FE-based flexible needle manipulation system achieving 0.4 mm targeting accuracy for spinal injections.
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