Marten Borchers

Photo: Marten Borchers
Research Associate
Information Systems, Socio-Technical Systems Design (WISTS)
Address
Office
Office hours
Office hours by arrangement (e-mail).
Contact
Research Profile
Marten Borchers started working for the Department of Information Systems, esp. Socio-Technical Systems Design (WISTS) at the Department of Computer Science at the University of Hamburg in September 2021. He completed his dual Master's degree at the University of Bremen where he focused on Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), IT Management, and IT Strategy Development. He also studied at the University of Tartu (Estonia) for one semester and worked in IT consulting (Public Service Consultant) for more than four years. His research interests are in the following areas:
- Smarty City
- Urban Planning
- KI, ML und NLP
- Collaboration Engeeniering
- Virtual- und Mixed-Reality
- E-Government
Publikationen
Conference Proceedings
2023
Borchers, M., Tavanapour, N. & Bittner, E.A.C. (2023). Designing Mobile Applications for Citizen Participation in Urban Planning In: 56th Hawaii International Conference on System Sciences (HICSS). Nominated for best Paper Award. Link
Borchers, M., Tavanapour, N. & Bittner, E.A.C. (2023). Exploring AI supported Citizen Argumentation on Urban Participation Platforms In: 56th Hawaii International Conference on System Sciences (HICSS). Link
2022
Borchers, M., & Tavanapour, N., & Bittner, E.A.C. (2022). Toward Intelligent Platforms to Support Citizen Participation in Urban Planning. In: Pacific Asia Conference on Information Systems (PACIS). Link. (accepted)
Projects
Toward intelligent Assistance Systems for the smart Utilization of Participation Data for Urban Planning and Design
- Urbanization is leading to major population growth in cities and metropolitan regions worldwide, and many statistics and forecasts predict that this trend will continue in the coming decades. This development is generating new social and societal conflicts and intensifying existing ones. This affects, for example, the housing market, recreational areas, green spaces, cultural facilities, educational institutions, sustainable jobs, and innovative business models. In the project Toward intelligent Assistance Systems for the smart Utilization of Participation Data for Urban Planning and Design, innovative approaches for the implementation of citizen participation are examined and developed. For this purpose, different (intelligent) prototypes are implemented and evaluated using new technologies such as machine learning.
- Duration: 01.09.2022 - 31.08.2024
- Website: Toward intelligent Assistance Systems for the smart Utilization of Participation Data for Urban Planning and Design
Data-driven Solutions for the Smart City Hamburg (D²S²C Hamburg)
- In the project Data-driven Solutions for the Smart City Hamburg (D²S²C Hamburg) real existing challenges in the field of Smart City are analyzed by students in the course and prototypical solutions are developed. For this purpose, the students will cooperate with HOCHBAHN, HSV/Future Dock, and Landesbetrieb Geoinformation und Vermessung, thus enabling a transfer between theory and practice.
- Duration: 01.04.2022 - 31.03.2024
- Website: D²S²C Hamburg
Innovation by Legal Design Thinking – Studentisches Digitalisierungslabor (StudDigiLab)
- The StudDigiLab addresses law and computer science students who are to digitize and optimize real, internal processes of the cooperation partner Die Caritas (Niedersachsen) in the seminar. Confronted with the creative design task, which is open-ended, the concept of legal design thinking is introduced and iterated as a basis for the development of innovative approaches to solutions.
- Duration: 01.04.2022 - 31.03.2023
- Website: StudDigiLab
Data-driven Optimization of electric Bus Operations (D2eBus)
- The aim of this project is to optimize the deployment of electric buses in public transportation. To achieve this, sensor data from these buses, as well as data on urban traffic, are leveraged to develop machine learning models for reliable range prediction. These models are integrated into an executable web prototype and evaluated to demonstrate requirements and potentials for the transition towards sustainable transportation and the necessary systems to control and optimize the deployment of electric buses. The project involves collaboration with HOCHBAHN to facilitate knowledge transfer between theory and practice.
- Duration: 01.07.2023 - 17.12.2023
Lectures
Lectures in the winter semester 2023/24
- Data-driven Solutions for the Smart City Hamburg (D²S²C Hamburg)
- Applicable for all students of the MIN-faculty
- Workload: 4 SWS / 6 ECTS
- Description: STiNE
- Innovation by Legal Design Thinking – Student Digitalization Lab (StudDigiLab)
- Applicable for all students of law and MIN-faculty
- Workload: 4 SWS / 6 ECTS
- Description: STiNE
Lectures in the summer semester 2023
- Data-driven Solutions for the Smart City Hamburg (D²S²C Hamburg)
- Applicable for all students of the MIN-faculty
- Workload: 4 SWS / 6 ECT
- Description: STiNE
Lectures in the winter semester 2022/23
- Data-driven Solutions for the Smart City Hamburg (D²S²C Hamburg)
- Applicable for all students of the MIN-faculty
- Workload: 4 SWS / 6 ECTS
- Description: STiNE
- Innovation by Legal Design Thinking – Student Digitalization Lab (StudDigiLab)
- Applicable for all students of law and MIN-faculty
- Workload: 4 SWS / 6 ECTS
- Description: STiNE
Lectures in the summer semester 2022
- Data-driven Solutions for the Smart City Hamburg (D²S²C Hamburg)
- Applicable for all students of the MIN-faculty
- Workload: 4 SWS / 6 ECTS
- Description: STiNE
- Innovation by Legal Design Thinking – Student Digitalization Lab (StudDigiLab)
- Applicable for all students of law and MIN-faculty
- Workload: 4 SWS / 6 ECTS
- Description: STiNE
- Internship Application Development for AI-based Collaboration
- Applicable for all students of computer science
- Workload: 4 SWS / 6 ECTS
- Description: STiNE
- Internship Drones in Hamburg
- Applicable for all students of computer science
- Workload: 4 SWS / 6 ECTS
- Description: STiNE
Lectures in the winter semester 2021/22
- Project Software Development for the Digital City
- Applicable for all students of computer science
- Workload: 6 SWS / 9 ECTS
- Description: STiNE