For the theoretical research project, participants will pick a topic according to their own interests,
or from a pool of suggestions that will be provided.
For their topic, the participants will give an overview of the state-of-the-art relevant to that topic
in a presentation during the seminar (30 min) and a term paper (8 – 10 pages per person, ACM style)
due at the end of the seminar.
Through this process, which the lecturers supervise and guide, the participants will train their ability to:
- find, organize, and systematically read relevant research papers;
- analyze, compare, and contrast research approaches and findings;
- structure, write, and format an academic paper;
- present their work using appropriate presentation techniques and presentation aids;
- answer questions and discuss their work with peers.
The theoretical research project is best suited to compile a state-of-the-art review in preparation for a subsequent
bachelor’s or master’s thesis in the same area.
For the practical research project, participants will implement a system that solves an applied real-world problem. Participants can suggest a problem or choose from suggestions that will be provided. In addition to delivering a functioning application, completing this seminar requires giving a presentation (30 min) about the project and compiling a developer documentation for the application (min 3 pages ACM style per person).
By completing the practical research track, participants will gain hands-experience with state-of-the-art methods and technologies and train their application development skills.
Topic suggestions for both tracks include, but are not limited to:
- Product Recommendation
- User Profiling
Artificial Neural Networks for Industrial Applications
- Time Series Analysis for Soft Sensors
- Time Series Forecasting for Predictive Quality Control
- Image Recognition for Waste Product Classification
- Transfer Learning for Simulation and Real-World Data
- Reinforcement Learning for Robotics and Production Scheduling
Explainability of Decision Processes in Artificial Neural Networks
- Object Recognition in Convolutional Neural Networks
- Visualization of Network Activity
- Structure of Learning Representations
- Importance of Network Areas for the Learning Task
For the theoretical research project:
- Presentation (30 min)
- Term paper (8-10 pages per person, ACM style)
For the practical research project:
- Developed application
- Presentation (30 min)
- Developer documentation (min 3 pages per person, ACM style)
Group work is possible for both project types.