Theses

Key Words:

Disaster Management, Preventive Citizen Participation, Information Management, Mobile App Development, Storm Surges & Flooding, Prototyping, Artificial Intelligence, and Machine Learning

Background:

Within the research project Rescue-Mate, the challenge of creating situational awareness and optimizing information flows in the security scenario of a storm surge in Hamburg is being investigated. This challenge arises against the backdrop of rising sea levels, more frequent extreme weather events, and a growing number of residents who may need to be evacuated and provided for in the event of a disaster. The key stakeholders in this scenario include government agencies and their affiliated units such as the fire department, police, the harbor authority, and various relief organizations. Comprehensive situational awareness and an informed and prepared population are particularly relevant for disaster response planning in situations like a storm surge, which involves aspects such as drowning individuals, drifting ships, and blocked roads.

It is possible to write theses that contribute to the content and objectives of the Rescue-Mate project, exploring selected subject areas and developing and testing prototypes. Through the project consortium, access to experts can also be provided.

Research Objectives:

Depending on the academic level (bachelor's or master's), specific areas of focus, and interests, various tasks and research questions can be addressed. Collaborations with organizations and/or companies are also possible but not mandatory. The following thematic areas are of particular interest and can be explored:

• Analysis and development of concepts and mobile prototypes for informing and proactively educating citizens in urban areas, particularly in Hamburg-Mitte, as well as their involvement in crisis situations to efficiently collect data and support crisis-relevant stakeholders.
• Development of AI-based prototypes for the automated evaluation of data from mobile crisis applications, such as aggregating automatically collected data, including locations, and presenting them to crisis management teams in the form of interactive maps or similar tools.

These topics are especially suitable for students majoring in computer science, business informatics, human-computer interaction, software system development, IT management and consulting, and intelligent adaptive systems. Theses can be written in either German or English.

University-Industry Collaboration (UIC) provides a platform for knowledge exchange, collaborative research, and the practical application of AI in partnership with companies. Through this collaboration, students can benefit from expert knowledge and hands-on experiences to develop their competencies in data analysis, machine learning, neural networks, and other AI technologies.

The impact of this collaboration on students' employability is multifaceted. On the one hand, practical training in cooperation with companies enables students to acquire relevant knowledge and skills increasingly demanded by employers. This can enhance their employability and give them a competitive advantage in the job market.

Furthermore, University-Industry Collaboration can also promote students' entrepreneurial skills and entrepreneurship. Through direct interaction with companies and involvement in AI solution development projects, students are encouraged to develop and implement innovative ideas. This contributes to fostering entrepreneurial thinking and action and may inspire them to start their own businesses or drive innovative AI applications within existing companies.

Task assignment:

Depending on the chosen degree program (bachelor or master), academic focus, and individual interests, there are various opportunities for assignments and research questions. There is also the option to collaborate with external organizations and/or companies, although this is not mandatory. Students have the flexibility to either work with organizations/companies they have acquired themselves or utilize the existing partners of DDLitLab for potential collaborations. The following are some areas of particular interest that can be explored as research topics:

• The role of University-Industry Collaboration in developing AI competencies and its impact on students' employability.
• Analysis of best practices in University-Industry Collaboration in the field of AI to identify the relevant skills and competencies for graduates' employability.
• Examining the impact of University-Industry Collaboration on closing competency gaps in the field of AI and promoting graduates' employability.
• Identifying AI-based tools and technologies that can be utilized in University-Industry Collaboration to enhance skills development and students' employability.
• Researching industry needs and expectations regarding graduates with AI competencies and their influence on curricula and programs in higher education.
• Developing measures and strategies for assessing and validating AI competencies acquired in University-Industry Collaboration to enhance students' employability and facilitate their transition into the job market.
• The impact of University-Industry Collaboration on the development of AI skills and their contribution to sustainable innovation in companies and organizations.
• The effectiveness of University-Industry Collaboration in developing AI competencies and its contribution to the sustainable development of companies and organizations.

Theses can be written in either German or English.