Lars Klein, B. Sc. CES

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.
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.

September 2019 Ph.D. studies and scientific researcher EPFL Lausanne/CH

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