I am not a traditional teacher. I ever taught courses. My experience is supervising Ph. D students and Master students through investigating challenging projects.

I ever draft an article to propose three laws to govern the technology rise or fall. Before reading the following summary, please refer to my previous article, "Three Laws of technology rises or Falls."

I summarize my teaching interests and philosophy in four points.

• Studying through investigating a challenging project is the best learning process or experience.


• If you fail to achieve on a challenging issue, I suggest you work on an open-source tool valuable to the community. There are three reasons to justify it. First, most junior researchers are not qualified to tackle a significant challenge. Second, a tool valuable to our community will gain your reputation. Three, working on a tool will train your skill which will help you find a job.
• If you are experienced and confident, I encourage you to find and tackle a challenging issue. Even solving a challenge in ten years is worthwhile. But you cannot expect too much.
• System innovation is very challenging and needs a tradeoff. Many guys plan to build innovative system prototypes. But as a Ph. D student or a junior researcher, you must consider people and time budget. With a limited budget, the systems are error-prone or too simple to justify their motivation. The first importance of all, you need to define a minimum set of functionalities to showcase the convincing innovation and demonstrate the change force. After the change force is validated, it is time to implement a fledged function with a double budget.

I plan to teach two courses:

1、Interdisciplinary Evaluatology and Benchmarkology

The main topics covered include:
(1) Fundamental concepts and terminology of evaluation
(2) The essence of evaluation
(3) Axioms of evaluation
(4) Fundamental theories of evaluation
(5) Methodologies of evaluation
(6) Key issues in evaluation
(7) The nature of benchmarks
(8) Basic principles of benchmarks
(9) Unified benchmark methodologies
(10) Development and limitations of evaluation in various disciplines
(11) Evaluatology in science and technology
(12) Evaluatology in intelligence
(13) Evaluatology in computer sciences

2、Social Infrastructure based on Advanced Computing:

The main topics covered include:
(1) Case studies
(2) Principles and methods
(3) Key system architectures
(4) Representative systems
(5) Fundamental abstractions
(6) Evaluation