Marvin Kastner, M.Sc.
Adresse
Technische Universität Hamburg
Institut für Maritime Logistik
Am Schwarzenberg-Campus 4 (D)
21073 Hamburg
Kontaktdaten & Profile
Büro: Gebäude D Raum 5.007
Tel.: +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
Forschungsschwerpunkte
- simulationsgestütztes Planen von Container-Terminals
- Optimierung der Ablaufplanung im Yard von Container-Terminals
- technologiegestützte Verbesserung der maritimen Sicherheit
- Maschinelles Lernen in der maritimen Logistik
- Optimierung multivariater Black-box Funktionen
Vorträge und Workshops (Auszug)
- 25.01.2023 ein Vortrag auf dem 7. Suderburger Logistik-Forum: "KI-unterstützte Planung von Güterumschlaganlagen am Beispiel von Containerterminals"
- 15.09.2022 ein Vortrag bei den MLE-Days 2022: "Synthetische Daten für das Reinforcement-Learning bei Container-Terminal-Steuerungen"
- 28.06.2022 ein Workshop an der Graduiertenakademie der TUHH: "Einführung in Jupyter Notebooks" [mehr]
- 02.07.2021 ein Workshop bei den MLE-Days 2021: "Methoden des Maschinellen Lernens in der Maritimen Logistik" [zip]
- 16.03.2021 ein Workshop an der Graduiertenakademie der TUHH: "Einführung in Jupyter Notebooks" [mehr]
- 30.11.2020 im Rahmen der Vortragsreihe "Train Your Engineering Network" der MLE-Initiative: "How to Talk About Machine Learning with Jupyter Notebooks" [mehr]
- 22.11.2019 auf der DISRUPT NOW! AI for Hamburg: "Künstliche Intelligenz in der maritimen Wirtschaft" [mehr]
- 29.10.2019 im Rahmen der forschungsbörse: "Maritime Logistik - Ein Rundumschlag" [mehr]
- 23.10.2019 bei der Open Access Week 2019 an der TUHH: "Datenanalyse - Offener Workshop: Daten auswerten und visualisieren mit Jupyter Notebooks" [mehr] [git]
- 16.11.2018 beim GI DevCamp Hamburg: "Mobility Research and GDPR"
- 27.09.2018 beim SGKV AK zum Thema Lkw-Ankünfte: "Prognoseverfahren und neuronale Netze – Was ist möglich?"
Veröffentlichungen (Auszug)
2024
| [182398] |
| Title: MaLiTuP: Machine Learning in Theory and Practice: Poster. |
| Written by: Kastner, Marvin and Scheidweiler, Tina |
| in: <em>All-Hands-Meeting Machine Learning 2019</em>. (2019). |
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| URL: http://hdl.handle.net/11420/6482 |
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Note: malitup projectpresentation
Abstract: Increasing digitalization, rapid developments in machine learning and exponentially growing accumulation of data lead to new jobs in the areas of data science. In the field of (maritime) logistics, digitalization is becoming increasingly important, resulting in an ever-increasing demand for trained personnel in the field of machine learning
2023
| [182398] |
| Title: MaLiTuP: Machine Learning in Theory and Practice: Poster. |
| Written by: Kastner, Marvin and Scheidweiler, Tina |
| in: <em>All-Hands-Meeting Machine Learning 2019</em>. (2019). |
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| URL: http://hdl.handle.net/11420/6482 |
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Note: malitup projectpresentation
Abstract: Increasing digitalization, rapid developments in machine learning and exponentially growing accumulation of data lead to new jobs in the areas of data science. In the field of (maritime) logistics, digitalization is becoming increasingly important, resulting in an ever-increasing demand for trained personnel in the field of machine learning
2022
| [182398] |
| Title: MaLiTuP: Machine Learning in Theory and Practice: Poster. |
| Written by: Kastner, Marvin and Scheidweiler, Tina |
| in: <em>All-Hands-Meeting Machine Learning 2019</em>. (2019). |
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| URL: http://hdl.handle.net/11420/6482 |
| ARXIVID: |
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Note: malitup projectpresentation
Abstract: Increasing digitalization, rapid developments in machine learning and exponentially growing accumulation of data lead to new jobs in the areas of data science. In the field of (maritime) logistics, digitalization is becoming increasingly important, resulting in an ever-increasing demand for trained personnel in the field of machine learning
2021
| [182398] |
| Title: MaLiTuP: Machine Learning in Theory and Practice: Poster. |
| Written by: Kastner, Marvin and Scheidweiler, Tina |
| in: <em>All-Hands-Meeting Machine Learning 2019</em>. (2019). |
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| URL: http://hdl.handle.net/11420/6482 |
| ARXIVID: |
| PMID: |
Note: malitup projectpresentation
Abstract: Increasing digitalization, rapid developments in machine learning and exponentially growing accumulation of data lead to new jobs in the areas of data science. In the field of (maritime) logistics, digitalization is becoming increasingly important, resulting in an ever-increasing demand for trained personnel in the field of machine learning
2020
| [182398] |
| Title: MaLiTuP: Machine Learning in Theory and Practice: Poster. |
| Written by: Kastner, Marvin and Scheidweiler, Tina |
| in: <em>All-Hands-Meeting Machine Learning 2019</em>. (2019). |
| Volume: Number: |
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| URL: http://hdl.handle.net/11420/6482 |
| ARXIVID: |
| PMID: |
Note: malitup projectpresentation
Abstract: Increasing digitalization, rapid developments in machine learning and exponentially growing accumulation of data lead to new jobs in the areas of data science. In the field of (maritime) logistics, digitalization is becoming increasingly important, resulting in an ever-increasing demand for trained personnel in the field of machine learning
2019
| [182398] |
| Title: MaLiTuP: Machine Learning in Theory and Practice: Poster. |
| Written by: Kastner, Marvin and Scheidweiler, Tina |
| in: <em>All-Hands-Meeting Machine Learning 2019</em>. (2019). |
| Volume: Number: |
| on pages: |
| Chapter: |
| Editor: |
| Publisher: |
| Series: All-Hands-Meeting Machine Learning 2019 |
| Address: All-Hands-Meeting Machine Learning 2019 |
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| how published: All-Hands-Meeting Machine Learning 2019 |
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| Type: |
| DOI: |
| URL: http://hdl.handle.net/11420/6482 |
| ARXIVID: |
| PMID: |
Note: malitup projectpresentation
Abstract: Increasing digitalization, rapid developments in machine learning and exponentially growing accumulation of data lead to new jobs in the areas of data science. In the field of (maritime) logistics, digitalization is becoming increasingly important, resulting in an ever-increasing demand for trained personnel in the field of machine learning