Junsheng Fu
Technical Expert In Localization And Road Estimation
Gothenburg, Sweden
Summary
👤
Senior🎓
Top SchoolJunsheng Fu is a technical expert in localization and road estimation for autonomous vehicles with nine years of industry experience, currently at Zenseact in Gothenburg. He holds a Doctor of Technology in Computer Vision and an MSc in Signal Processing, combining deep academic rigor with practical self-driving engineering skills. Junsheng has produced 21 patents, 8 publications, and maintains 13 open-source projects, including a notable EKF-based multisensor tracker that fuses lidar and radar for robust pedestrian and vehicle tracking. His work spans camera, lidar, radar, and HD maps, and he focuses on solving corner cases in mapping and state estimation that directly improve on-road safety. Colleagues describe him as a hands-on problem solver who refactors complex algorithms into reliable, testable code. He brings a rare blend of research-grade modeling and production-focused implementation to autonomous perception stacks.
9 years of coding experience
Master of Science, Information Technology - Signal Processing, GPA: 4.45/5, Master of Science, Information Technology - Signal Processing, GPA: 4.45/5 at Tampere University of TechnologySelf-Driving Car Engineer Nanodegree, Self-Driving Car Engineer Nanodegree at UdacityBachelor of Engineering, Communication Engineering, GPA: 85/100, Bachelor of Engineering, Communication Engineering, GPA: 85/100 at Hangzhou Dianzi University
English, Chinese, Finnish
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (5)
object-tracking10
eigen10
lidar10
c-language8
cprogramming-language8
Programming languages (4)
Github contributions (5)
JunshengFu/tracking-with-Extended-Kalman-Filter
Apr 2017 - Sep 2021
Object (e.g Pedestrian, vehicles) tracking by Extended Kalman Filter (EKF), with fused data from both lidar and radar sensors.
Role in this project:
Data Scientist
Data ScientistContributions:54 commits, 50 pushes, 1 branch in 4 years 5 months
Contributions summary:Junsheng contributed significantly to the project by implementing and refining core functionalities related to object tracking using an Extended Kalman Filter (EKF). Their work includes adding pedestrian tracking using lidar data, implementing RMSE calculation and Jacobian matrix computations, and refactoring code for handling fused data from lidar and radar sensors. The user also addressed issues related to angle normalization and initialization, improving the accuracy and reliability of the tracking system.
extended-kalman-filterslidarradar
JunshengFu/junshengfu.github.io
Apr 2017 - Nov 2024
Contributions:58 pushes, 1 branch in 7 years 7 months
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