He Lie
Development Engineer at Mercedes-Benz AG
Germany
Summary
🤩
Rockstar🎓
Top SchoolHe Lie is a Development Engineer based in Germany with 10 years of experience applying simulation, data-driven modeling and machine learning to automotive systems. Currently at Mercedes‑Benz he focuses on energy consumption prediction and e‑range estimation for e‑mobility, building on earlier roles owning steering wheel and driver airbag development and chassis dynamics simulation. His background blends classical vehicle dynamics (ADAMS, MATLAB/Simulink, LMS) with hands-on ML experiment work—contributing a random-walk lab and matrix-completion experiments to an EPFL optimization-for-ML course. Trained with a Master’s in Automotive Engineering from TU Braunschweig and dual bachelor experience at Tongji, he bridges international engineering practice and academic rigor. He is comfortable moving between low-level physical modeling and applied ML prototypes, which helps translate complex vehicle behavior into actionable prediction models. Quietly, he pairs production responsibility with an experimental mindset, often validating algorithms with the same rigor he applied to vehicle component validation.
10 years of coding experience
1 year of employment as a software developer
Bachelor's Degree, Automotive Engineering, Bachelor's Degree, Automotive Engineering at Technische Hochschule IngolstadtMaster of Science, Automotive Engineering, Master of Science, Automotive Engineering at Technische Universität BraunschweigDouble Bachelor, Automotive Engineering, Double Bachelor, Automotive Engineering at 同济大学
English, German, Chinese
Github Skills (11)
machine-learning10
python10
numpy10
matplotlib10
data-analysis10
algorithms9
optimization9
data-structure9
jupyter-notebook9
algorithm9
data-structures9
Programming languages (9)
Github contributions (5)
epfml/OptML_course
Mar 2021 - Apr 2021
EPFL Course - Optimization for Machine Learning - CS-439
Role in this project:
ML Engineer
ML EngineerContributions:10 commits, 8 pushes in 1 month
Contributions summary:He primarily contributed to the development of a random walk lab for an optimization for machine learning course. Their work involved implementing and testing a random walk algorithm on a torus graph, which included setting up the graph, running the walk, and estimating the probability distribution. The user also worked on generating and plotting errors to determine the algorithm's convergence speed and created a solution for an experiment involving matrix completion. This shows a focus on hands-on, applied machine learning concepts.
optimizationmachine-learningepfl
epfml/cola
Aug 2018 - Nov 2021
Contributions:10 commits, 6 pushes in 3 years 3 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.