Data Science,
Data Engineering,
Machine Learning.

Freelancer based in Berlin, Germany

About me

Experienced machine learning engineer and software developer specializing in deep learning applications. Proficient in computer vision, medical device development, data mining and natural language processing. With expertise to take a project from the proof of concept all the way through to production, ensuring high-quality and effective solutions.

Experience

CARIAD (Volkswagen Group)

Data Analyst (contract), March - December 2022

  • Performing data analysis of the company-wide risk-related data and automating report generation.
  • Creating data pipelines to process and centralize data from multiple sources (Airflow).
  • Building visual tools to enhance insight and facilitate early detection of threats (PowerBI, Dash).
Data Analysis
Business Intelligence
Python
PowerBI
Docker
Azure

Machine Learning Engineer (contract), June 2021 - February 2022

  • Developed a semantic segmentation computer vision model for automatic evaluation of advanced driver-assistance systems (ADAS).
  • Researched and evaluated the state of the art models (based on convolutional neural networks and vision transformers) and techniques to optimize semantic segmentation maps.
  • Ported a Tensorflow based machine learning pipeline to OpenMMLab (PyTorch based) for the use on the local machines and on the cloud.
  • Developed high-performance algorithms for post-processing of semantic segmentation maps.
  • Assisted the acquisition of the driving dataset (images and LIDAR data) and built algorithmic and visual tools for optimizing the data selection.
Machine Learning
Computer Vision
Convolutional Neural Networks
Vision Transformers
Cython/C++
Python
PyTorch
OpenMMLab
Tensorflow
Airflow
Docker
Azure

OpenDress GmbH

Machine Learning Engineer (contract), April - May 2021

  • Consulted on architecture improvements to the convolutional neural network-based deep learning model (PyTorch) and the pipeline for sustainable development and deployment in the production environment.
  • Designed a REST API for client access to the model.
  • Deployed the model as a service accessible through a REST API.
Machine Learning
Convolutional Neural Networks
Python
PyTorch
FastAPI

Berlin Institute of Health/Deutsches Herzzentrum Berlin

Machine Learning Engineer/Senior Data Scientist, May 2019 - December 2020

  • Performed analysis and processing of large quantities of continuous patient data and conducted research on predicting severe outcomes in the intensive care setting.
  • Developed a recurrent neural network based model for predicting post-operative complications.
  • Designed the software architecture incorporating the machine learning model.
  • Led and conducted the development in accordance with processes for the product to be certified under Medical Device Regulation.
  • Integrated the product with the hospital’s infrastructure and deployed it
Machine Learning
Time Series
Recurrent Neural Networks
Python
PyTorch
SQL
Linux
Docker

Merantix/MX Healthcare

Data Engineer/Machine Learning Engineer, June 2018 - March 2019

  • Led the effort to build a vast dataset of medical mammography images in collaboration with multiple healthcare sites in Europe.
  • Anonymized and processed hundreds of thousands of images for use in a machine learning project.
  • Developed the backend for an online platform for X-ray image annotation.
  • Participated in development of a convolutional neural network based deep learning model for detecting and classifying abnormalities in mammography images.
Machine Learning
Deep Learning
Convolutional Neural Networks
Medical Imaging
Computer Vision
Python
Tensorflow
Linux
Google Cloud Platform
Docker

Vanderbilt University Medical Center

/Machine Learning Engineer/Research Programmer, November 2013 - May 2018

  • Conducted research on computational representation learning and its application to electronic medical records.
  • Developed supervised models using recurrent neural networks, noisy medical data to predict multi-label targets.
  • Designed and developed a web application for visualization of medical history employing semantic embedding for medical concepts.
  • Compared efficacy of different data formats and common predictive models for medical outcome prediction.
  • Implemented algorithms for statistical modeling in Python and C optimizing for speed and API simplicity.
  • Configured and maintained a GNU/Linux based computation server.
Machine Learning
Deep Learning
Convolutional Neural Networks
Recurrent Neural Networks
Natural Language Processing
Python
Keras
SQL
Lua
C
Linux

Software Developer, September 2012 - November 2013

  • Developed and maintained several web applications for human genetic research data management and collaboration.
  • Designed and developed mobile applications for iOS and Android including a computer vision program for genetic sample management.
  • Configured and maintained a GNU/Linux based web and database servers.
Computer Vision
Web Development
Mobile App Development
Python
Ruby
Java
Objective-C
SQL
Linux

University of Virginia

Software Developer/Research Assistant, September 2010 - September 2012

  • Developed large structural biology oriented databases and web applications for research collaboration and communicating results to the public.
  • Configured and administered a network of highly utilized GNU/Linux based servers.
  • Expanded the web-based laboratory information management system, by providing unified data storage, improving data visualization and sharing capabilities in structural genomics laboratories.
  • Developed a high-throughput pattern recognition system, which automatically scans images in search of protein crystals.
Computer Vision
Web Development
Python
Ruby
Linux