Marvin Kastner, M.Sc.
Address
Hamburg University of Technology
Institute of Maritime Logistics
Am Schwarzenberg-Campus 4 (D)
21073 Hamburg
Contact Details & Profiles
Office: building D room 5.007
Phone: +49 40 42878 4793
E-mail: marvin.kastner(at)tuhh(dot)de
ORCiD: 0000-0001-8289-2943
LinkedIn: https://www.linkedin.com/in/marvin-kastner/
ResearchGate: https://www.researchgate.net/profile/Marvin-Kastner
Google scholar: https://scholar.google.de/citations?user=lAR-oVAAAAAJ&hl=de&oi=ao
Scopus: https://www.scopus.com/authid/detail.uri?authorId=57221938031
Research Focus
- Simulation-based Design of Container Terminals
- Optimization of Yard Operations at Container Terminals
- Data-driven Improvement of Maritime Security
- Machine Learning in Maritime Logistic
- Optimization of Multivariate Black-box Functions
Presentations and workshops (Excerpt)
- 25.01.2023 a talk at the 7. Suderburger Logistics Forum: "AI-assisted planning of cargo handling facilities with the example of container terminals" (title translated)
- 15.09.2022 a talk at the MLE-Days 2022: "Synthetic data for reinforcement learning in container terminal control systems."
- 28.06.2022 a workshop at the Graduate Academy of TUHH: "Introduction to Jupyter Notebooks" (title translated) [more]
- 02.07.2021 a workshop at the MLE-Days 2021: "Machine Learning in Maritime Logistics" (title translated) [zip]
- 16.03.2021 a workshop at the Graduate Academy of TUHH: "Introduction to Jupyter Notebooks" (title translated) [more]
- 30.11.2020 in the lecture series "Train Your Engineering Network" of the MLE initiative: "How to Talk About Machine Learning with Jupyter Notebooks"
- 22.11.2019 at DISRUPT NOW! AI for Hamburg: "Artificial Intelligence in Maritime Economy" (title translated) [more]
- 29.10.2019 in the context of forschungsbörse: "Maritime Logistics - an all-round cover" (title translated) [more]
- 23.10.2019 at the Open Access Week 2019 at TUHH: "Data Analysis - Describe and Visualize Data with Jupyter Notebooks" (title translated) [more] [git]
- 16.11.2018 at the GI DevCamp Hamburg: "Mobility Research and GDPR"
- 27.09.2018 at SGKV WG regarding truck arrivals: "Forecasting and Neural Networks – What is possible?" (title translated)
2024
| [182401] |
| Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em> |
| Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna |
| in: <em>DELFI 2020</em>. (2020). |
| Volume: Number: |
| on pages: 365-366 |
| Chapter: |
| Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.) |
| Publisher: Gesellschaft für Informatik e.V.: |
| Series: Lecture Notes in Informatics (LNI) - Proceedings |
| Address: Bonn |
| Edition: |
| ISBN: 978-3-88579-702-9 |
| how published: |
| Organization: |
| School: |
| Institution: |
| Type: |
| DOI: |
| URL: https://api.ltb.io/show/BMRWS |
| ARXIVID: |
| PMID: |
Note: malitup
Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks
2023
| [182401] |
| Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em> |
| Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna |
| in: <em>DELFI 2020</em>. (2020). |
| Volume: Number: |
| on pages: 365-366 |
| Chapter: |
| Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.) |
| Publisher: Gesellschaft für Informatik e.V.: |
| Series: Lecture Notes in Informatics (LNI) - Proceedings |
| Address: Bonn |
| Edition: |
| ISBN: 978-3-88579-702-9 |
| how published: |
| Organization: |
| School: |
| Institution: |
| Type: |
| DOI: |
| URL: https://api.ltb.io/show/BMRWS |
| ARXIVID: |
| PMID: |
Note: malitup
Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks
2022
| [182401] |
| Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em> |
| Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna |
| in: <em>DELFI 2020</em>. (2020). |
| Volume: Number: |
| on pages: 365-366 |
| Chapter: |
| Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.) |
| Publisher: Gesellschaft für Informatik e.V.: |
| Series: Lecture Notes in Informatics (LNI) - Proceedings |
| Address: Bonn |
| Edition: |
| ISBN: 978-3-88579-702-9 |
| how published: |
| Organization: |
| School: |
| Institution: |
| Type: |
| DOI: |
| URL: https://api.ltb.io/show/BMRWS |
| ARXIVID: |
| PMID: |
Note: malitup
Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks
2021
| [182401] |
| Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em> |
| Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna |
| in: <em>DELFI 2020</em>. (2020). |
| Volume: Number: |
| on pages: 365-366 |
| Chapter: |
| Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.) |
| Publisher: Gesellschaft für Informatik e.V.: |
| Series: Lecture Notes in Informatics (LNI) - Proceedings |
| Address: Bonn |
| Edition: |
| ISBN: 978-3-88579-702-9 |
| how published: |
| Organization: |
| School: |
| Institution: |
| Type: |
| DOI: |
| URL: https://api.ltb.io/show/BMRWS |
| ARXIVID: |
| PMID: |
Note: malitup
Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks
2020
| [182401] |
| Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em> |
| Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna |
| in: <em>DELFI 2020</em>. (2020). |
| Volume: Number: |
| on pages: 365-366 |
| Chapter: |
| Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.) |
| Publisher: Gesellschaft für Informatik e.V.: |
| Series: Lecture Notes in Informatics (LNI) - Proceedings |
| Address: Bonn |
| Edition: |
| ISBN: 978-3-88579-702-9 |
| how published: |
| Organization: |
| School: |
| Institution: |
| Type: |
| DOI: |
| URL: https://api.ltb.io/show/BMRWS |
| ARXIVID: |
| PMID: |
Note: malitup
Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks
2019
| [182401] |
| Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em> |
| Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna |
| in: <em>DELFI 2020</em>. (2020). |
| Volume: Number: |
| on pages: 365-366 |
| Chapter: |
| Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.) |
| Publisher: Gesellschaft für Informatik e.V.: |
| Series: Lecture Notes in Informatics (LNI) - Proceedings |
| Address: Bonn |
| Edition: |
| ISBN: 978-3-88579-702-9 |
| how published: |
| Organization: |
| School: |
| Institution: |
| Type: |
| DOI: |
| URL: https://api.ltb.io/show/BMRWS |
| ARXIVID: |
| PMID: |
Note: malitup
Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks