Julia Baasch
Referentin Der Geschäftsführerin Technik at BEW Berliner Energie und Wärme GmbH
Berlin, Germany
Summary
👤
Senior🎓
Top SchoolJulia Baasch is an industrial engineer with 11 years of experience who blends technical analysis, strategic planning and hands-on Python tooling to drive decarbonization of urban heat systems. In roles at Vattenfall and BEW she led portfolio optimization, investment appraisal and Berlin’s hydrogen roadmap, translating complex system-wide tradeoffs into actionable decisions for senior management. She pairs energy-systems modeling and PowerBI/Python tool development with practical implementation experience in district heating and investment processes. An active open-source contributor to neuroinformatics projects like SpikeInterface and Neo, she brings rigorous test automation and containerization expertise that speaks to her focus on reproducible, portable analysis pipelines. Beyond technical delivery, she facilitates workshops and co-leads BEW’s Diversity Network, reflecting a commitment to empowerment and inclusive leadership. Based in Berlin, she combines academic training from TU Berlin and RWTH Aachen with international research experience in Aix-Marseille and Shanghai.
11 years of coding experience
4 years of employment as a software developer
Master of Science - MS, Industrial Engineering, 1,4, Master of Science - MS, Industrial Engineering, 1,4 at Technische Universität BerlinBachelor of Science - BS, Industrial Engineering, 2,9, Bachelor of Science - BS, Industrial Engineering, 2,9 at RWTH Aachen UniversitySemester Abroad in Shanghai, Industrial Engineering, Semester Abroad in Shanghai, Industrial Engineering at 同济大学
German, English, Chinese, French
Github Skills (18)
unit-testing10
docker10
pytest10
python10
singularity10
testing10
dockers10
numpy10
neo4j10
scientific-computing10
data-structure9
github-ci9
cicd9
data-analysis9
githubaction-workflow9
Programming languages (11)
Github contributions (5)
NeuralEnsemble/python-neo
Apr 2015 - Dec 2022
Neo is a package for representing electrophysiology data in Python, together with support for reading a wide range of neurophysiology file formats
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:1 release, 336 reviews, 524 commits in 7 years 9 months
Contributions summary:Julia made multiple contributions related to the `AnalogSignalArray` class, enhancing its functionality to accept `None` as arguments for time slicing. They implemented changes to the `AnalogSignalArray` class itself, alongside the development of unit tests within `neo/test/coretest/test_analogsignalarray.py` to validate the new functionality and ensure that data were being correctly handled during operations. The user also added new methods and functionality for Epoch, Events and SpikeTrains data structures, including adding a duplicate with new data feature.
neurosciencepythonneofile-formatscomputational-neuroscience
SpikeInterface/spikeinterface
Nov 2021 - Oct 2022
A Python-based module for creating flexible and robust spike sorting pipelines.
Role in this project:DevOps Engineer & Test Automation Engineer
DevOps Engineer & Test Automation EngineerContributions:17 reviews, 52 commits, 8 PRs in 11 months
Contributions summary:Julia contributed to the project by adding and refining tests, specifically focusing on Docker and Singularity containerization. They implemented and tested singularity runs within the existing codebase and integrated these tests. The user also worked on improving the handling of datasets within the environment to allow for proper access within the containers. The commits show the user's focus on ensuring robust testing and the portability of the spike sorting pipelines.
neurosciencepythonspike-sortingsortingelectrophysiology
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