Teaching

Human-computer Interaction

Undergraduate course

This course aims to popularize the concepts, theories, and applications of human-computer interaction design to students. Students will gain an understanding of the fundamentals of human-computer interaction, such as knowledge of humans, computers, and interaction. The user-centered design approach (e.g. usability, design process, user modeling, requirements analysis methods, implementation, implementation support, and evaluation techniques) is the focus of this human-computer interaction course, allowing students to participate in user-centered analysis and design. Modern human-computer interaction designs often involve cutting-edge technologies such as deep learning, and this course will provide students with an introduction to these technologies. In addition, the human-computer interaction course also provides tutorials on various prototype designs for interaction design. Lastly, students will be able to design high-usability and innovative interactive products with the knowledge gained from this course.

Deep Learning

Graduate course

This course aims to introduce students to the field of Deep Learning. It provides students with basics and technologies, so that they may proceed to advanced knowledge without barriers. The main contents include definition of deep learning, (mini-batch) gradient descent, parameter and hyper-parameter, regularization methods, optimizer and common network structures (e.g., fully-connected networks and convolutional network networks). Students will also learn to use Python on deep learning platforms (e.g., Pytorch) to do network building and task processing.