CORE: Machine Learning and Cognitive Software

Our research group explores the intersection of artificial intelligence, cognitive computing, and software engineering. Our work focuses on developing machine learning models that enhance cognitive software systems, enabling adaptive, efficient, and interpretable AI solutions. We investigate topics such as neural network architectures, reasoning in language models, and AI-driven decision-making. By bridging theoretical insights with practical applications, our research aims to advance the capabilities of intelligent software systems in diverse domains, from natural language processing to complex decision support systems.

Members

Prof. Dr. Christian Bartelt
Kristian Kolthoff
Tobias Sesterhenn
Janis Zenkner
Jannik Brinkmann
Patrick Knab

Teaching

We are excited to offer a variety of courses and projects in the field of Machine Learning. Whether you’re looking to gain foundational knowledge, work on hands-on projects, or engage in research, our teaching program provides valuable opportunities for students at all levels.

Our Course Offerings:

• European AI Team Projects – available as a Bachelor project (6 ECTS), Master project (8 ECTS), or DigiTec project (10 ECTS)

• Lecture: Introduction to Artificial Intelligence (B.Sc.)

• Research Project (M.Sc.) – 20 ECTS

• Proseminar Machine Learning (B.Sc.) and Seminar Machine Learning (M.Sc.) (ECTS according to module catalog)

• Bachelor and Master Theses

If you are interested in thesis topics, projects, or seminars, feel free to reach out to Patrick Knab at [patrick.knab@tu-clausthal.de]. We look forward to hearing from you!

    1. European Master Team Projects - Collaborate Across Borders! 

    The European Master Team Project offers an exciting opportunity for students to collaborate internationally while working on real-world challenges. This unique program is a long-standing partnership between the Technical University of Clausthal and Babeș-Bolyai University in Cluj-Napoca, Romania, building on a successful collaboration between Prof. Dr. Christian Bartelt and the Romanian university.

    Students from both universities work together in interdisciplinary teams, bringing their diverse skills and perspectives to tackle innovative projects in computer science and engineering. The project runs from March 14, 2025, to June 20, 2025, during which teams will collaborate online, with regular meetings, milestone reviews, and mentoring sessions.

    While much of the collaboration happens online, the program also includes two in-person project weeks:

    • A trip to Cluj-Napoca, Romania (April 5–12, 2025)

    • A project week in Goslar, Germany (exact dates TBD)

    During these weeks, students meet their teammates in person, participate in workshops, refine their projects, and enjoy cultural and social events. All travel, accommodation, and social event costs are covered, making this a fantastic opportunity to gain international experience at no personal expense.

    The projects vary each year, covering topics at the intersection of AI, digitalization, software engineering, and more. This semester, students can choose from the following three projects:

    This program is part of the European Master Team Project initiative, inspired by the successful model used at the University of Mannheim. For more information and past projects, check out the Mannheim project page.

    Take this chance to work on an exciting project, gain international teamwork experience, and expand your professional network!

     

    2. Lecture: Introduction to Artificial Intelligence (B.Sc.)

    This course provides an introductory overview of Artificial Intelligence (AI), covering fundamental concepts, techniques, and applications. Topics include search algorithms, machine learning, neural networks, and AI ethics, giving students a solid foundation in the field. The lecture combines theoretical insights with practical examples, helping students understand how AI is used in real-world scenarios.

     

    3. Research Project (M.Sc.)

    The research project offers Master’s students the opportunity to work on an advanced AI or machine learning topic, either independently or as part of a team. Guided by a supervisor, students will develop a research question, design experiments, analyze results, and document their findings. This project allows students to gain hands-on experience in scientific research while applying their knowledge to a complex problem.

     

    4. Proseminar Machine Learning (B.Sc.) & Seminar Machine Learning (M.Sc.)

    In these seminars, students explore current topics in machine learning by engaging with research papers, presenting their findings, and discussing key concepts with peers. The Bachelor-level proseminar focuses on foundational machine learning methods, while the Master-level seminar delves into more advanced and specialized topics. These courses help students develop critical thinking, presentation skills, and a deeper understanding of state-of-the-art research.

     

    5. Bachelor and Master Theses

    Students have the opportunity to conduct independent research on a topic related to AI, machine learning, or software engineering under the supervision of a faculty member. A Bachelor’s thesis typically focuses on implementing and evaluating an existing method or concept, while a Master’s thesis involves a more in-depth investigation, potentially including theoretical contributions or novel approaches. These projects provide valuable research experience and prepare students for careers in academia or industry.