Christopher Mower
Senior Research Scientist at Huawei Technologies Research & Development (UK) Ltd
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolChristopher Mower is a senior research scientist based in London with 11 years of experience bridging academic rigor and industrial R&D across robotics, numerical methods, and visual information processing. He holds a PhD in Informatics from The University of Edinburgh and has moved from surgical robot control in academia to applied research roles at Huawei, bringing practical experience deploying algorithms in industry settings. Earlier work includes numerical software development at NAG, where he implemented a Fortran routine for correlation matrix regularization in collaboration with leading numerical analysts. Christopher combines strong mathematical foundations with hands-on systems implementation, making him adept at turning theoretical methods into robust, production-oriented solutions.
11 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Informatics, Doctor of Philosophy (Ph.D.), Informatics at The University of EdinburghMaster of Science (MSc), Applied Mathematics with Numerical Analysis, Master of Science (MSc), Applied Mathematics with Numerical Analysis at The University of ManchesterMaster of Science (MSc), Computing (Visual Information Processing), Master of Science (MSc), Computing (Visual Information Processing) at Imperial College LondonBachelor’s Degree, Mathematics, Bachelor’s Degree, Mathematics at The University of Sheffield
Github Skills (145)
webots10
apriltags10
python10
toolbox10
null-safety10
cvxpy10
multi-objective-optimization10
specification10
fairness-ml10
ros10
autonomous-driving10
optimization10
nonlinear10
fiducial-markers10
robotics10
Programming languages (8)
Github contributions (5)
lbr-stack/lbr_fri_ros2_stack
Nov 2022 - Jan 2023
ROS 2 integration for KUKA LBR IIWA 7/14 and Med 7/14
Contributions:7 reviews, 26 commits, 12 PRs in 2 months
ignitionroboticsros1ros2webots
cmower/optas
Apr 2022 - Mar 2023
OpTaS: An optimization-based task specification library for trajectory optimization and model predictive control.
Contributions:34 reviews, 746 commits, 128 PRs in 10 months
task-and-motion-planninggurobispecificationoptimizationmotion
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