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Joel Dierkes

Joel Dierkes

Computer Scientist
dierkesjoel@gmail.com
German, English

Background

About

About

I am a Computer Scientist with a passion for programming.

Work Experience

Work Experience

  • Werkstudent, Vector Informatik GmbH

    Nov, 2024 - Mar, 20255 months

    Working Student in the embedded field.

    • Build a subsecond vector document retrieval platform for Jira issues used by 20+ people

    • Worked with Rust and AUTOSAR

  • Assistant Scientist, Part-Time, Otto von Guericke University Magdeburg

    Dec, 2022 - Oct, 20241 year 11 months

    Independent Researching and Publishing Papers in the field of Computer Visualization

    • Working with Julia and Python (Numpy, Matplotlib)

    • Main author of one paper and one more in review

  • Tutor 'Introduction to Computer Science for Engineers', Otto von Guericke University Magdeburg

    Sep, 2022 - Jan, 20235 months

    Designing excercise sheets and supporting students.

    • Topics: OOP, searching, sorting, BNF, complexity and correctness of algorithms

  • Software Dev Engineer, Technical Student, Full-Time, CERN

    Oct, 2021 - Sep, 20221 year

    Full time developer working on the Rucio data management project.

    • Full-Stack development in Python

    • Main focus on testing and documentation.

    • Example Commits: 1a3fc55b0, 947060e10, and 6ce71ed66

  • Software Dev Engineer, Intern, Full-Time, Amazon Development Center - AWS

    Jun, 2021 - Aug, 20213 months

    Working on the Nitrogen Hypervisor.

    • Using Python, C and Bash

    • Working with Elastic Search and the AWS infrastructure

  • Assistant Scientist, Part-Time, Otto von Guericke University Magdeburg

    Mar, 2021 - May, 20213 months

    Part time Programmer at the SwarmLab of the Chair of Computational Intelligence.

    • Using Ros2 with Pyhton and Pandas

    • Working on data aggregation

  • Tutor 'Introduction to Computer Science for Engineers' and 'Algorithms and Data-Structures', Otto von Guericke University Magdeburg

    Apr, 2019 - Jan, 20211 year 10 months

    Part time exercise leader for 4 semesters.

    • Topics: OOP, searching, sorting, BNF, complexity and correctness of algorithms, graphs, trees, linked lists, and combinatorial optimization

  • Developer, Eudemonia Solutions AG (now BMS CS), Part-Time

    Nov, 2018 - Dec, 20202 years 2 months

    Part time Programmer as front-end and back-end developer.

    • Programming in Java and Javascript

    • Using agile project management

Projects Experience

Projects Experience

  • λ-DBSCAN

    Aug, 2023 - Oct, 20211 year 9 months

    λ-DBSCAN is an exension of the popular cluster algorithm DBSCAN. It allows to include local density information in contrast to only using global settings.

    • Published our results at IDA 2024

Skills

Skills

  • Programming Languages

    Python

    Java

    Rust

    C/C++

  • Software

    Linux

    Docker

    Git

    GitHub/GitLab

    SQL

    AWS

    Jira

Education

Education

  • Computer Science, Master, KIT University

    Oct, 2024 - Present

    Focus on Data Processing and Software Development

  • Computer Science, Bachelor, Otto-von-Guericke University Magdeburg

    Oct, 2018 - Jul, 2024

    Various areas including ML, Deep Learning, Databases, Computer Graphics, Mathematics, Programming, Project Management

  • Software Development, Student Study - Bachelor, University

    Oct, 2014 - Sep, 2018

    Introduction to CS, Math, Seminars

  • , High School, Burger Roland Gymnasium

    Sep, 2010 - May, 2018

Volunteer Work

Volunteer Work

  • Orga, RoboCup

    Oct, 2020 - Sep, 2021

    RoboCup Organization Team

    • Volunteering as member of the RoboCup Organization Team

  • Participant, Hochbegabtenförderung e.V.

    Jun, 2011 - May, 2017

    Course Computer-Science Robot-Technology

    • Developer and Engineer with technology like NXT, EV3 and Arduino

    • Learning key competencies like teamwork, problem and solution based thinking, and planning.

    • Participated several times in the RoboCup Rescue Line competition.

Publications

Publications

  • λ-DBSCAN: Augmenting DBSCAN with Prior Knowledge , Springer Nature Switzerland

    Published on: Apr 16, 2024

    State-of-the-art density based cluster algorithms offer remarkable speed and robustness. However, they do not allow the user to make local changes without affecting the global outcome. The user thus has to choose between clustering a local region well or keeping the global result.
    We present a new approach, λ-DBSCAN, which augments the DBSCAN algorithm to include local a priori knowledge. The parameters can be specified per observation, rather than globally, which enables the user to include local knowledge about the data without modifying other regions. Furthermore, we define regions in the data that should be affected by certain parameter choices, to reduce the workload for a user.