Personal Data


David Luis Wiegandt


16.09.1993 in Berlin



Azure DevOps


10/2016 — present

Master's Studies of Computer Science, Humboldt-Universität zu Berlin
Current average grade of 1.1

Thesis: “Distributed Instance-Optimal Join Processing” (in progress)

10/2012 — 06/2016

Bachelor's Studies of Computer Science, Humboldt-Universität zu Berlin
Bachelor of Science (2.2)

Thesis: “Local Graph Patterns for Scientific Workflow Similarity Search” (graded 1.0)

08/2004 — 06/2012

Primo-Levi-Gymnasium, Berlin
Abitur (2.2)

Work Experience

04/2020 — 03/2021

Department of Neurology, Charité — Universitätsmedizin Berlin
Automated report generation for outpatient deep brain stimulation visits and development of a web app for domain-specific patient information management

06/2015 — 12/2019

Knowledge Management in Bioinformatics, Humboldt-Universität zu Berlin
Collaboration in various research projects and work as a tutor in different courses at the chair of “Knowledge Management in Bioinformatics” led by Prof. Ulf Leser

08/2016 — 11/2016

PSI Metals GmbH, Berlin
Implementation of an automated release history update in the internal wiki upon a new software release

01/2016 — 07/2016

interactive tools GmbH, Berlin
Enhancements to the CI/CD workflows and participation in web development projects

10/2013 — 05/2015

PSI Metals GmbH, Berlin
Automation and parametrisation of various build, installation and test workflows and maintenance of the internal GUI framework

02/2013 — 06/2013

kantiko GmbH, Berlin
Collaboration in the development of a web application providing small and medium-sized businesses with a simple means to perform their accounting



German (native speaker), English (fluent in spoken and written)


TypeScript/JavaScript, HTML, CSS, Java, Erlang, Python, SQL, C, C#, …


Node.js, Angular, React, Lucene, Hibernate, …



Wiegandt, David Luis, et al. “Graph n-grams for Scientific Workflow Similarity Search.” LWDA. 2016.


Habibi, Maryam, et al. “PatSeg: A Sequential Patent Segmentation Approach.” Big Data Research 19-20 (2020): 100133.

Ševa, Jurica, et al. “VIST - A Variant-Information Search Tool for precisiononcology.” BMC bioinformatics 20.1 (2019): 429.

Pallarz, Steffen, et al. “Comparative Analysis of Public Knowledge Bases for Precision Oncology.” JCO Precision Oncology 3 (2019): 1-8.

Habibi, Maryam, et al. “Deep learning with word embeddings improves biomedical named entity recognition.” Bioinformatics 33.14 (2017): i37-i48.

Habibi, Maryam, et al. “Recognizing chemicals in patents: a comparative analysis.” Journal of cheminformatics 8.1 (2016): 59.

Habibi, Maryam, et al. “Performance of Gene Name Recognition Tools on Patents.” SMBM. 2016.