My Education and My Research

1. My Education and My Research National Chi Nan University R. C. T. Lee

2. I only learned vacuum tubes in EE Dept of NTU, without knowing anything about transistors. • I learned so-called network theory, something very theoretical, in Berkeley for my MS degree, still knowing nothing about transistors.

3. Yet I worked as a transistor circuit designer for one year after I got my MS degree. I learned the tricks all by myself. • I was trying to get into the network theory for my Ph.D. degree in University of Illinois and was rejected.

4. So I went back to Berkeley for Ph.D. having no idea about what I should study. • I saw an advertisement and met my later adviser who is blind. • He asked me whether I learned the first order predicate calculus. I said yes, which was a big mistake because I only heard the word “calculus”.

5. First order predicate calculus is actually a kind of symbolic logic. But I did not know even the Boolean logic. That is, I did not know what A&B is.

6. I started by reading a classics in symbolic logic, written by Church. Could not understand even the first page. • Luckily, I found a very good introductory book “Sets, Logic and Axiomatic Theories”, written by R. Stoll of Oberlin College.

7. For my Ph.D. work, I had to be able to write computer programs. I had never taken any course in programming. Again, I learned all by myself. • I considered myself to be extremely lucky to study symbolic logic because this gave me a logical mind.

8. I got my Ph.D. degree from Berkeley in 1967, shortly after the EE Department was renamed as EECS Department. I was one of the first Ph.D. graduated from a CS Department in the world although I only took one CS course in Berkeley.

9. To think back, I am the only one in my EE class who got into the CS field without knowing that the CS field would become so popular in the future. • As the Chinese proverb says, Old Man, Mr. Own, lost his horse. Only God knows that this brought him great fortune.

10. My Ph.D. research was a part of the artificial intelligence (A.I.). A.I. was applied to the so-called problem solving by computer.

11. To solve a problem, we must have knowledge which can be stored as symbolic logic formulas. For example, consider the following knowledge, or common sense: • If it rains, we need to carry an umbrella. • It is raining now. • Having the above two formulas, we may obtain the following logical consequence: • We need an umbrella.

12. We can use logical formulas to represent our knowledge: Let R and U represent it rains and we need an umbrella respectively. Then the above knowledge can be represented as follows: • The logical consequence is U.

13. Suppose we do not have any umbrella. We may use the following fact: If we do not have umbrella, we may use a rain coat.

14. One can easily see that the A.I. research is not practical because we have to store an exceedingly large amount of knowledge into our computer and later search for the relevant ones when we use the computer to solve a problem.

15. The Johns Hopkins Research Laboratory robot problem. The robot can wonder around without any trouble. But it may fall downstairs if the door is opened. So, they put an axiom into the robot: Whenever the slope of the ground is changed, reverse yourself. Unfortunately, the robot would repeatedly reverse itself because after the axiom is applied, it would be applied immediately again.

16. So, here comes a problem: How does a human being store common sense into his brain and quickly retrieve the relevant knowledge? • There is another problem: How is common sense represented in the brain? Most people who do not know anything about slope know what a staircase is.

17. In fact, we can distinguish cats and dogs. But we can hardly use words to explain why we think it is a cat or a dog. It is even more difficult when we have to explain why we think a certain person looks kind or wicked.

18. I once published a paper about using logic to prove the correctness of a program. I just pointed out that we can do this without claiming that it is a practical idea. In fact, it is not practical at all. • To prove that a program is correct, we need to use logical formulas to describe the program and we also have to use logical formulas to describe the specification of a program.

19. Can we describe an operating system precisely? Can we specify an operating system precisely? No, we can do neither. • But the U.S. Defense Department started to be interested in A.I. and put tremendous amount of money into A.I. research. They got nothing.

20. I tried to tell one of my colleagues that he should not take my research too seriously because my approach could only solve toy problems. He did not listen. He quite his job as a professor and finally ended as a mentally disturbed person all his life.

21. Japan, at the same time, started the so-called the Fifth Generation Computer Project, emphasizing A.I. and parallel programming. They did not produce anything. • For this project, Japan invited the whole world to do research together. I immediately knew that this was a hoax. If the research is that meaningful, Japan would do the research in absolute secret.

22. About the same time, Professor James LightHill of Cambridge University wrote a report on A.I. His conclusion: It would not be meaningful. LightHill did not visit any A.I. laboratory and he only spent three months to write the report. His report was entirely based upon his logical mind. Only a mathematician can do this.

23. In the LightHill Report, he pointed out one important fact: To solve a problem, we do not need to imitate human beings. Instead, we may use the engineering approach. For instance, we should not have a robot to land a plane. We should develop a very good microwave guidance system to land the plane.

24. The U.S. Defense Department wasted a lot of money on nonsense. For example, the ADA programming language project is a typical one. ADA was supposed to be a language for all purposes. How can this be? Anyone with logical mind would know that for each purpose, there must be a specific language if we want it to be efficient. There can never be a language which can be used for accounting as well as jet fighter control.

25. I must admit that I seldom follow others while most of my fellow professors would do that. • In 1973, I published a book, “Symbolic Logic and Mechanical Theorem Proving”, by Academic Press and translated in Japanese, Russian and Italian.

26. An important decision was made by me after I started to have some reputation in the computer science academic world: I decided to come back to Taiwan. I came to Taiwan in 1975, the year which a lot of people tried to leave Taiwan because President Chiang Kai-Sheik died that year and South Vietnam also fell into communism at that year.

27. I came back for one simple reason: I wanted to put Taiwan onto the academic world map. Most of my friends in America thought I was crazy. They told me that if I go back to Taiwan, forget about research. Concentrate on teaching and promotion of computer technology. I ignored them from the very beginning.

28. I was lured to the National Tsing Hua University. At that time, the computer which we used was an IBM 1130 computer. At any time, only one program could be run. Besides, the sound of the computer running the COBOL compiler is entirely different from that running the FORTRAN compiler.

29. Yet, under such a bad environment, I continued to do research and continued to produce academic papers. Besides, I bumped into a very exciting field: algorithm research. • Algorithm is interesting because a seemingly difficult problem can be solved by a clever and elegant algorithm. This always arouses my curiosity. But, it is difficult to do research in this field: Too many research papers have been written.

30. Consider the exact matching problem which is defined as follows: Given a pattern P and a text T which are both strings of characters. Locate every substring in T which matches exactly with P. • Example: We can see that there are two substrings in T which exactly match P.

31. Although the exact matching problem is easy to understand, there are at least 24 algorithms developed to solve the problem. If you miss even one of them, your research may become garbage because you may well be reinventing the wheel. I can almost say that I almost remember all of these 24 algorithms? How can I achieve this? After all, I am a very old man now. Besides, nearly all of the papers are quite difficult ones.

32. The trick: Force your poor graduate students to read them. My slogan: A good adviser is a professor who forces his students to read difficult papers.

33. I organized an algorithm paper reading seminar which is held once a week. In every meeting, a student reports a paper. This algorithm seminar started in 1980 in National Tsing Hua Universiyty and has been continuing ever since. A similar seminar has been going on in the National Chi Nan University since 2001.

34. My advice: A solid foundation is always important. Therefore being knowledgeable in a field is absolutely important. Many researchers do not get anywhere because they actually have not read all of the relevant papers. It is nonsense to have so-called organized research because there cannot be organized innovation. But, organized study of literature can be done and should be done.

35. One problem arouse in my study of algorithms: NP-completeness. An NP-complete problem is a difficult problem in the sense no efficient algorithm can likely be designed to solve this problem. A mathematical definition was given to NP-complete problems and all books used this very abstract definition.

36. I was not satisfied with this abstract definition at all. I insist, all my life, that we must have some physical feeling about anything, including NP-completeness. • I succeeded in giving examples to show why an NP-complete problem can be so difficult. Why did I succeed? I succeeded because I studied symbolic logic before.

37. I must admit that I was not happy about any of the existing algorithm books because they often fail to explain things clearly, including the concept of NP-completeness. • I wrote a book myself and this book was published by McGraw-Hill. Within one year, this book has a Spanish translation.

38. Although I have been considered a theory person because my research is quite theoretical, I have always been concerned about my students. I note that almost all of my recent graduate students got into the communication field. This is not surprising. After all, almost every communication system, including a cell phone, has a CPU in it.

39. But most of computer science students have very limited knowledge about communication. As compared with the professional communication engineers, they are just idiots. For example, they do not know what modulation is and cannot understand why RF technology is important for a cell phone.

40. Can a computer science student simply go to the EE department to take an introductory course in communication? I found that most of the communication courses offered by EE departments are too difficult and again, they do not explain things very well.

41. So, I again wrote an introductory book on communication. It was published by John Wiley in Oct 1, 2007. • I am still not satisfied. As I talked about modulation, my poor computer science students asked me how modulation is done in the physical layer. They are equally puzzled how sinusoidal signals are generated.

42. I decided to write another book on analog circuit design for one simple reason: I do not like any existing analog circuit design book. To give you an example, one of the most interesting circuit in this field is the so-called phase lock loop. It is somehow a circuit to make two signals synchronized. I was shocked to note that all of the books presented the phase lock loop circuit by starting with Laplace transform and ending with it also.

43. I remember clearly the analog circuit design problem for my Ph.D. qualifying examination in Berkeley in 1965. I was given a rather simple circuit and I was asked two questions: (1) What can this circuit do? (2) What are the important engineering issues of this circuit that we should pay attention to?

44. A good engineer must have engineering sense. A good analog circuit designer must also have engineering sense about analog circuit design, I am presently writing an analog circuit design book which emphasizes physical meaning of analog circuits.

45. Conclusion : I have never studied those topics which I have been teaching. How can I do it? • Answer: I have a relatively solid background in mathematics. This gives me the ability to switch fields.

46. How could I publish so many papers? (1) I always try to build a solid background in the particular which I was working because I know that innovation is still based upon knowledge. (2) I like to know everything rather thoroughly. If I do not understand some points, I admit the fact. A typical case is the NP-completeness. I bet that a lot of people do not understand it. Yet they simply pretend that they understand it. They even teach it.

47. (3) Whenever I am puzzled, I ask anyone who can help, including graduate students. Most professors do not do this. (4) I was trained in logic before. This makes me more rigorous than many people. (5) I like to challenge others while many people have the habit of defending others. For example, graduate students tend to defend the papers which they are reporting without realizing that they are not obliged to do so.

48. (6) I like and am able to organize my knowledge. Remember: Science is built of facts the way a house is built on bricks. But an accumulation of facts is no more science than a pile of bricks is a house. Example: From 24 algorithms designed for exact string matching, I managed to extract seven rules out of them. This helps quite a lot.

49. A story which I like to tell before I finish: All of my elementary school classmates went to college and went to fancy schools. How did that happen? After all, when we were admitted to the school, no IQ test was conducted. • The answer: Our parents were elites. 80 years ago, our parents all graduated from universities. Many studied abroad. Our parents, in other words, belonged to a very privileged class of Chinese 80 years ago. The majority of Chinese, 80 years ago, were illiterate, not mentioning having received college education.

50. I am never proud of myself because I am what my parents were. This is rather unfair. I have met so many kids who are much less fortunate than I am. No wonder their achievement is not very good. • I have been helping less fortunate kids all my life. I believe that the seeds which I see in this generation will become blossoms in the next generation and the blossoms in this generation will become fruits in the next generation.