Lars Klein

Education
2004-2013 Abitur
Advanced courses in English and Math. Final Grade: 1.0
WS13/14 - SS17 Bachelor in computational engineering science (RWTH Aachen)
Final Grade: 1.3, passed with excellence.
WS17/18 - today Master in computational engineering science (RWTH Aachen)
Foreign Semester in WS17/18 at EPFL Lausanne.
Following up with a master’s thesis at EPFL in WS18/19.
WS13/14 - today Scholarship (Studienstiftung des deutschen Volkes)


Work experience
WS15/16 Group project (AVT RWTH Aachen)
Expansion of the functionality of a Modelica to C cross-compiler.
Analyzing and extending a custom grammar, automatic C code generation.
WS15/16 - SS16 Student assistant (indurad, Aachen)
Designing a framework for data integration and analysis.
Creating tailormade data formats, integrating into existing workflow.
SS16 Student assistant (CCES RWTH Aachen)
Contribution to a two-phase flow simulation tool.
Algorithm prototyping in Python and high performance implementation in C++.
WS16/17 Student intern (GE Global Research, Munich and Bangalore)
Application of machine learning to computer vision tasks.
Design of custom neural network architectures.
Contributing to the development of data-centric machine learning framework.
SS17 Computer Vision specialist (ÉcurieAix, Aachen)
Developing a real-time capable system for object detection.
Integrating with a C++ / ROS environment.
WS17/18 Machine Learning engineer (GreenScan GmBH, Burbach and Bremen)
Research and Development of computer vision algorithms for medical data.
Collaboration with Mevis Medical Solutions GmBH.

IT Skills
Programming Fluency in a variety of programming languages
C: Embedded programming for Arduino and Atmel.
C++: High performance architectures, parallel computing.
Experience with build tools such as CMake.
Java, C#: Design patterns, OOP.
Python, Matlab: Developing numerical algorithms.
Web-Dev: Experience in the Javascript Ecosystem, Typescript.
Technologies: Optimization theory, Machine Learning
Interest in research and development of cutting-edge machine learning solutions.
Practical experience in design, implementation and deployment.
Strong theoretical background in optimization theory and numerical programming.
Frameworks: Proficiency in key development tools
Tensorflow, Keras: Deep experience in leading ml frameworks.
Scipy Ecosystem: Algorithm design in a variety of scientific fields,
physical modeling, ODEs, PDEs,
OpenCV: Applying high-performance computer vision algorithms,
in both python and C++.
Qt Application design with C++
Android App development with Java
Misc LATEX, git, ...
OS: Windows, Linux, Android
Experience in management and development for a variety of operating systems.

 

Language Skills
German: native
English: highly proficient
French: proficient
Spanish: high-school knowledge
Interests
Cycling, Hiking, Badminton
Piano, Reading, Cooking, Learning French

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© Prof. Dr. med. Hans-Martin Klein