Master thesis with internship
Supervisor: Prof.Dr. Frank van der Velde
Modeling and implementing aspects of cognitive processing forms the basis of many new applications in ICT systems, as used in society ("smart society") and industry ("smart industry"). An example is the success of "Deep Learning" (DL) in ICT systems such as self-driving cars, face recognition, speech recognition, and other forms of pattern recognition. DL models now begin to outperform humans on certain tasks. This offers possibilities for many new applications (e.g., in medical data classification).
The extent and importance of these applications will continue and increase in the near future. HFE students will most likely be directly confronted with these applications in their professional career. Hence, HFE students would profit by combining their skills in human factors with a basic understanding of and experience with these applications.
Recent developments in computer modeling have resulted in modeling tools that can be used by HFE students to model aspects of cognitive processing and implement them in systems such as robots. Some computer training is required, such as a basic knowledge of Python as taught in the HFE module. But the use of these tools does not require a profound experience with computer modeling.
In these master thesis projects a choice can be made on the task that will be modeled. This could be a (neural network) model of motor behavior, pattern classification, or concept development in language. In each of these domains, learning can be modeled using tools such as DL. The models developed can be implemented on a robot such as the iCub robot at the university of Twente.
These master projects are 35 EC projects, with an internship period of 10 EC to become familiarized with the tool to be used.
Contact: prof. dr. Frank van der Velde: email@example.com