Course Schedule

This course introduces microsensors that have become pervasive in the past few decades. The essential interdisciplinary topics in mechanical engineering, piezoresistance, semiconductor processing, etc., are introduced from the standpoint of an electronic engineer. A few major types of microsensors are treated in depth to illustrate the transduction principles, design, construction, fabrication, packaging, and testing. Finally, the course is concluded with sensor fusion and applications.

This course focuses on deep learning models and their applications in computer vision multimodal data. Specifically, the topics include various deep neural network architectures with applications in computer vision, natural language processing, and graph data. Some of the latest deep learning models will be introduced, including diffusion models, transformers, graph neural networks, and normalizing flows. The students have the opportunity to implement deep learning models for practical tasks such as visual perception, generative AI, graph processing, and 3D vision.

This course introduces the basic principles, development, and state-of-the-art of robotics. The course starts from the basic theory of robotics, including spatial descriptions, kinematics, Jacobians, and dynamics. Then, this course introduces the components and skills for robot development, such as actuators, sensors, control methods, and programming tools. Lastly, some state-of-the-art robotic topics for case studies, such as unmanned vehicles, humanoid robots, soft robots, micro/nano robots, etc.

This course aims to introduce you to the fundamental principles of engineering thinking and its application in research and entrepreneurship. Throughout the course, you will explore the creative process of generating ideas, formulating problems, and finding solutions through research. Additionally, you will learn how to identify the unique value of a solution and its potential for commercialization. The course will cover a wide range of topics, including creative thinking, idea generation, intellectual property, funding acquisition, presentation skill, legal procedures, branding, and team management. By the end of the course, you will have gained a preliminary understanding of the engineering innovation process and the skills and knowledge necessary to transform an idea into a successful business venture.