Personel Data
Name: Dipl.-Phys. Adrian Eisenmeier
Day of birth: 1985.06.13
Nationality: deutsch
Language Skills: German (native), English (fluent), Dutch (beginner)
Programming languages: Python, R, C# , C++, Java Script
Skills
Various methods of Machine Learning, Neural Networks with Keras/Tensorflow and
Data Science Frameworks (Jupyter Lab, Scikit-Learn, H2O, pyramid Auto-ARMIA,
SciPy, ML.NET, etc.), image processing OpenCV, SkiaSharp, Knime, R Shiny, Grafana
Dashboards, Linux Server Administration, Docker, Kubernetes, Apache Impala Hadoop,
Apache Kafka, Xamarin Forms, Xamarin.Android, Xamarin.iOS, Xamarin.UWP, ASP.NET
Core, Entity Framework Core, Identity Core, Penetration testing and IT Security (Kali,
Tails Linux, Metasploit Framework, NMap, etc.), Bluetooth, agile development, test
driven development, Scrum, Redmine, Jira, Mantis, Confluence, Doxygen LaTeX, Azure
Cloud Ressources (TSI, Functions FaaS, SQL, Cosmos DB), AWS Cloud (EC2, ECS, S3,
Lambdas) GitLab, Subversion, REST API’s, Swagger, automated deployment processes
with Continuous Integration (CI), Reverse Proxys with Caddy, Nginx, Apache, SSL
certificates with Let’s Encrypt
Education
2007 – 2016 Academic studies: Physics, Meteorology,
Albert-Ludwigs-Universität Freiburg, Deutschland.
Job experience
2011 Scientific Assistant, Pharmacy industry, Freiburg, Germany.
Technologies: R, Knime
- Analysis of synergistic effects in mixtures of various cancer drugs
- Implementation of Chou Combination Index (CI) in R as Knime Node
2011 Scientific Assistant, Optics industry, Freiburg, Germany.
Technologies: Mathematica, Python
- Development of a software to determine the astigmatism and the focal length of
eye lenses using machine learning. - Implementation of the patent specification (2814916) of the Rodenstock company
- Implementierung der Patentschrift (2814916) der Firma Rodenstock.
- Aspheric lense approximation by use of cubic B-splines
- Estimation of metric tensors and numerical solutions of the curvature differential
equations
2012 – 2015 Scientific Assistant, Institute of Physical Chemistry, Albert-Ludwigs-University of Freiburg, Germany.
Technologies: MATLAB, TurboMol, ORCA, Gromacs MD
- QM/MM simulations of ESR parameters (g-tensor, hyperfine coupling tensor) for flavo-proteins, solved in an aqueous environment
- Use of CHARMM force fields for the molecular dynamics simulations.
2016 Scientific Assistant, Institute of Physics, Albert-Ludwigs-University of Freiburg, Germany.
Technologies: C++, Python, R
- Development and analysis of various recurrent neural networks for pattern matching
Unsupervised learning:
- Pattern recognition with Boltzmann nets
- Pattern recognition with LSTM nets
- Pattern recognition with Hopfield nets and analysis of the recognition rate
- by use of different learning rules (Hebbian, Oya, STDP)
- by use of different activations (linear, heavyside, sigmoid)
- by use of different encodings of the neural activity
- by use of energy optimization criteria
- by use of algebraic relations of neural activities to each other
- Comparison of classical Kohonen maps with game theoretical Kohonen maps
Supervised learning:
- Trained neural networks for baseline corrections in magnetic resonance spectra
2015 – 2017 System Administrator, IT Gruppe des Instituts für Physik, Albert-Ludwigs-Universiät Freiburg, Deutschland.
- Setup and maintenance of Linux and Windows images with ESXI and XEN
- Configuration of dhcp, and cups server, configuration of NFS data storage LDAP authentifications,
- KISS-systems, USV-configurations, FOG-cloud backups
- Development of an automatized penetration testing system
2017 - 2023 Data Science and Software Development, Dr. Hornecker Softwareentwicklung and IT Services, Freiburg, Germany
Finance (B2B): September 2022 - Today
Role: Teachnical Lead/Scrum Master, Software Developer, Software Architect.
Technologies: R, Python, Reticulate, Docker, Camunda, Fusion Registry, Fame.
Lead role in the development of an R library for generating statistical reports of financial data. Translating existing logic from Fame to R and Python. Incorporate logic into process workflows of Camunda using Reticulate. Plan, coordinate and evaluate sprints embedded with 10 other teams.
Finance (B2B): May 2021 - August 2022
Function: Software Developer, Software Architect
Technologies: C#, C++, Matlab
Rewriting of a software written in Matlab for valuation, and management of financial assets in C#. Calculation of market values and cash flows for bonds, mortgages, swaps, swaptions, callable bonds, floaters, and steepeners. Design, conception and implementation of software interfaces, and software architecture. Planning and implementation of database modeling with Entity Framework, as well as administration of SQLite and SQL Server databases. Creating CI/CD processes via Azure DevOps pipelines, and deploying release artifacts. Creating software documentation via DoxyGen. Connecting C++ frameworks (QuantLib, Boost) to the C# solution via C++/CLI. Upgrading all C# components to .NET6, and upgrading all C++ components to C++20. Writing unit tests and integration tests to validate technical and business logic.
Printing industry (B2B): May 2019 - February 2021
Role: Projekt Manager, Data Scientist, Software Developer
Technologies: Xamarin Forms, Camera2, Entity Framework Core, OpenCV,
SkiaSharp, Pillow, Docker, REST, Flask AP
Lead role in the development of a cross-platform mobile app for fraud detection,
as well as for the calculation of a robust fingerprint, within the scope of
a patented process for security ettiquetes. Investigation, evaluation and
implementation of image processing methods such as SIFT, SURF, ORB.
Implementation of Laplace and Fourier transforms, as well as signal-to-noise
analyses. Planning and execution of the CI deployment process. Connection to
the cloud via a Flask REST API. Implementation of a heartbeat service for the
Flask controllers, as well as a response system in case of failures.
Energy industry (B2C): February 2020 - June 2020
Role: Data Scientist
Technologies: verschiedene Azure Services (Azure TSI, Azure Cosmos DB,
Azure SQL Datenbank, Azure Functions (FaaS), Azure Key Vault), verschiedene
Zeitreihen- und KI-Frameworks (pyramid ARIMA, SciKit-Learn, Tensorflow-
Keras), Confluence, Jira
Data Scientist, Forcast of used electrical consumption, based on historical
data and the actual weather prediction. Investigation of the contribution of
meteoroloical parameters (temperature, cloud cover, precipitation probability,
etc.) and comparison of different forcasting methods (ARIMA, Random Forests,
LSTM Neural Networks) in terms of calculational costs, planning qualities, and
accuracies (mase, nmae, nrmse). Reading and writing data with Azure services,
and implementing the predictive model with Azure functions (FaaS) in Python.
Implementation of a daily validation logic for the reporting. With the help of
this implementation, the customer received value from the data, analyzed by
machine learning, for future forecasts. The provision of the data as well as the
processing is realized via various Azure services in an Azure cloud infrastructure.
Documentation written with Confluence.
eCommerce (B2B): September 2019 - January 2020
Role: Projekt Manager, Data Scientist,Software Developer
Technologies: Docker, MySQL, .NET Core, Swagger, R Shiny dashboard, ShinyProxy, Caddy
Lead role in the development of a full dockerzied system to upload data of
online market shops into a database, and visualize them. Upload API with
ASP .NET Core implemented, and with Swagger documentated. Dashboard
implemented with R Shiny. Implementation of a secure passwordless access by
use of Json Web Tokens (JWT), reverse proxy with Caddy.
Telecommunication industry (B2C): May 2018 - June 2019
Role: Data Scientist, Software Developer
Technologies: Knime, Impala Hadoop, Docker, R Shiny, ShinyProxy, Random
Forests with Scikit-Learn, Neural Networks with Tensorflow
Data Scientist, Elaborating of complex business processes with the responsible
group leaders to get a mapping from the processes to the corresponding data in
the hadoop cluster. Implementing a R logic to calculate KPI’s and development
of a Shiny dashboard for controllable visualizations of the KPI’s. Implementation
of a data interface to give the controlling group access to the data.
Big Data, for the defined KPI’s all phone calls between customer and service, out
of last 4 years, were analysed by the use of methods from language processing
(NLP), to understand the reasons for complaints and disturbances.
Development of a predictive model to forcast individual working times of
telecommunication techniquans in the field, based on historical data. This
required the analysis of customer-specific developments by using machine
learning and statistical models with the aim of improving customer acquisition
and customer retention in the B2C area.
Setup of a compliance conform server for production. Implementation of a
release pipeline (Continuous Integration CI), that orchestrates docker containers
for data access, model prediction, data transfer, and validation . Implementation
of a daily reporting logic and visualization of planning qualities and accuracies.
IoT industry (B2C): April 2017 - May 2018
Role: Software Developer
Technologies: Xamarin Forms, .NET, Bluetooth Low Energy
Development of a cross-platform mobile, and a WPF PC app to program and
control smart time switches. Cross-platform implementation of the bluetooth
stack with Robotics libraries. Programming an automated rollout mechanism
for Google and Apple store. Maintenence of Apple developer and app store
connect.