Introduction to research, this is the outline of my talk. I am going to say a few words about the idea of a university, about the nature of science, nature of research, just briefly what drives research. Then what do research scholars work on? This is a summary from when I was dean researcher, I did a summary of what people work on, try to classify the problems, comes under 6 or 7 classifications and then I am going to talk little bit about learning and creativity because while coursework is mostly about logic, research is a lot about intuition. While you use logic, you make your leaps only through intuition and we have some idea, understanding of it from the work of Spirits.
Perry and co-workers, it is called the split brain experiments. Perry got his Nobel Prize in 1981, a neurosurgeon. Then I will talk, I will give some advice that I cannot resist for research scholars and that is also based on my experience here with students and the last line on ethics. Basically the university itself is conceived somehow we forget to mention this and I think we ourselves forget it. The university is based on, it is a renaissance concept essentially.
current university. In the Renaissance, thinkers made three assumptions. The first assumption is that the material world is lawful.
Its non-living world is governed by laws. That's what it means. The second is that there is an underlying unity in knowledge and this can be discovered only by a combined study of the natural and social sciences.
We have divorced the two essentially. Natural sciences includes engineering, social sciences includes humanities. We think they don't have an effect.
I I will just give you an example, for example when in my own area in molecular thermodynamics Gibbs made the assumption that all the microscopic states of an isolated system are equally probable. This idea a priori that everything should be equal unless there is a good reason for it not to be came from the then social ideas of Clark Karl Marx. If you had been at any other time, the Gibbs may have made some other assumption, but we would have finally come to this assumption because this is what leads to results that compare well with experiment. But the point is that the ideas in society influence your thinking in terms of science.
also. Then the third is that education can lead to indefinite human progress. These are assumptions, these are the postulates.
Then it was von Humboldt in the 19th century who said research and teaching have to go hand in hand. He said research brings passion to teaching and teaching rejuvenates the researcher. So both are important and ever since then all research universities have been based on these four premises. There is a nice article by Oakshott, Oakshott was used to be a professor of political science in Oxford and it is called the idea of a university in fact you can Google it and find the article. He says it is arguably the most civilized.
of human undertakings. The idea is simply of course that education passes on accumulated knowledge to the next generation and no other animal does that. All other animals have to only learn by copying, so by watching and copying.
In fact that is probably the only reason we are on top of the food chain. Then but the purpose of education is refinement aligned not employment. I think that is important to realize many people come to education thinking this will lead to employment afterwards. It does but that is a corollary. A refined mind will find more opportunities and therefore find I mean more jobs available for it.
But what has happened is this has been twisted out of seeing because employment is certainly important for individuals. So everybody thinks. I get a better job after this and therefore they come for it, that is not the purpose of education at all.
In fact the universities are now burdened with not only educating students but also placing them which is, which should never have been the case. Anyway I would like to draw on a metaphor, I like this metaphor, this is Oppenheimer has a book called Science and the Common Understanding, it is a beautiful book, you should read it. He draws the metaphor, he calls it the house of science, I have extended it to the house of education.
It is like an ancient monument, it is a vast house, it is in some wings are complete and perfect and some parts are still receiving finishing touches and there are also parts for which the scaffolding is being built and there are new wings being created but it is also very different from a monument. First it is not done to a preconceived design and it has a wonderful randomness suggestive Unending growth and it has no shut doors, it's open to all comers. Of course this seems a little ironical considering the way people struggle to get into institutions, good institutions in India. But that is an artificial result of our not having enough seats for the people.
the number of students who seek education. Basically it is an open house, it is open to all comers. I mean if you want a degree of course you have to register and so on and then there are limitations.
Let me say a few words about science. nature of science. Science seeks unity in the wild variety around us.
When I say science, I include engineering and I contrast this in particular with the industry which thrives on differences. If you go to the industry, you have to first tell everybody what your product is and how it is different from everybody else's, otherwise you cannot sell your product. Whereas the university seeks unity, it asks what is the minimum number of laws on the basis of which I can describe the entire diversity around us. and you will never seek unity after you leave the university. You have to come back to the university to seek unity.
It is basically a pyramid built by research traditions. The pyramid is robust but needs constant modification. The nice saying is that take Copernicus out and you have to rethink Einstein.
You have to rethink, it does not mean you have to completely change everything. Normally it is a fairly robust structure but at the same time there will be minor changes that occur. For example, when Einstein introduced the limitations of light. light's movement and Newton's idea of instantaneous reaction to a force was lost, it did not make any difference to the macroscopic world. It only made a difference when you started talking about speeds comparable to light.
But on the other hand you did have to make that modification. The science says the theories of science are produced by intuitive insight and validated by logic and experiment and improved by iteration. Please note that no theory can be proved, it can only be corroborated.
You say that this is the theory, current theory and as results come in you may have to modify your thinking. Now, you should read, the other book you should read is Popper and Kuhn. They both write, I mean it is not a book, they are articles by both of these people.
They have also written books but it is primarily about science as an evolutionary process. What they say is science evolves. deliberate idea mutation subject to the following selection rules.
First it ignores all ideas that lack testable consequences. You must realize that that eliminates about two-thirds of life because a lot of things in life don't have testable consequences. In fact, in all of science, almost all of science and engineering, we deal primarily with materials that do not have a memory and therefore you are able to deal with them the way we deal with them.
If they have a memory then it is very difficult, especially if they have a long memory, it is very difficult to have testable consequences for such substances. Secondly, you reject ideas that fail the tests. If you compare with experiment does not agree then the idea has to be rejected. Thirdly, you reject ideas that fail the tests.
Usually you seek ideas that make the widest possible range of predictions. If you can predict 2 things with one idea and 3 things with the third, second idea you keep the second idea and throw out the first because you are seeking unity, you want to know what is the minimum number of basic laws on the basis of which you can explain everything. So science uses a double negative process that is it disproves incorrect theories, it uses double negative process to create a growing store of useful theories.
Okay, so how do scientists work? Basically I have got 2 quotations that tell you quite graphically. First you balance 2 seemingly contradictory attitudes.
This is from Carl Sagan. Carl Sagan was an astronomer. He was a scientist.
his sister who taught in Cornell, he passed away about 10 years ago and he said the one attitude is to remain open to new ideas no matter how bizarre or counter intuitive they may be and the other attitude is scrutiny. scrutinize ruthlessly and skeptically all ideas that come to you. So this apparently conflicting ideas are what you have to work with and Newton said if I have seen further than others it is by standing on the shoulders of giants, it is a very famous quote. What this tells you is please do your literature search very well because you should know what others have done before you start doing your work.
Let me say a few words about the nature of research. Research is basically a creative process. It's complex and it is iterative.
It is a search for truth whether the truth is mundane or profound. It's about going up blind alleys to see if they are really blind. Sometimes you try out a method, after 4 years you discover it's not a useful method.
It's still publishable, you will still get your PhD. It doesn't mean you won't get your PhD. Your thing doesn't have to, of course, normally for a negative.
Negative result you should have done experiments too. If pure theory that gives a negative result usually does not lead to a PhD. So you have to be careful if you are working on pure theory, you have to be little more sure of your ground.
Then there are two kinds of research in general in the university, one is academic, the other is developmental. Academic is basically curiosity driven, but you must remember even here 99% is routine, only 1% is inspired. It's routine because people have said things before, you keep verifying those things, you keep testing them out and so on. And 1% inspired is of course the great people that you have seen in... In science and in engineering various fields.
The developmental research is application driven, it is a team effort, it needs leadership and considerable funding. So what drives research? This is a, this is from Donald Stokes book but it is basically a well known diagram.
On the one hand what drives research is fundamental understanding, you are trying to understand things in a fundamental way. The other is the consideration. of use. So you divide the area space into 4 quadrants and there is a quadrant to be avoided.
The pure basic research quadrant is called the Bohr quadrant, use inspired basic research is called the Pasteur quadrant. research is called the Edison quadrant. Incidentally, there is a famous quotation of Edison that said, I mean they asked him, I believe he succeeded in making the light bulb only out in his 10,000th trial. So they asked him how, they went and said you failed 9,999 times.
He said no I did not fail, I found out how not to make a bulb in 9,999 ways. So that is also a contribution to research. So these are what you have to do. This quadrant is to be avoided. I will say a few more about few words about that later.
This is a slide that I borrowed and adapted from president of the University of Quente. We met in a meeting in Korea. It was about research and what how university should pursue it and the idea is the following. Primarily you have basic research which has takes existing understanding to an improved understanding.
Then you have existing technology which goes to improved technology. So we have industry driven science driven research. The reason I put this in is because I think we should realize increasingly what is happening is we are not able to control the applications of science and technology. So you have some results that come out.
Turns out that you have made an improvement to understanding, you have made an improvement to technology. But there is a side effect in typically for example it may be an environmental side effect of a technology and then there are lots of objections to it and many scientists and technologists have complained that these people who object. to it are eco-terrorists but actually they are not. The point is they didn't know about this technology till you told them about it.
So the idea is increasingly in universities that you should have a society driven research where you should inform people about what you are working on, where it will go so that social scientists are also involved right at the beginning and they warn you that this might lead to consequences. So the idea is if you take them on the team, in the team right at the beginning then you are likely to produce technology. technologies that will be actually useful.
Now a lot of your technologies may not be useful. So there is always a risk of your running into problems because you did not take these considerations into account. So it is called context of use inspired research. You must know where it is going to be used and you must discuss it with people in humanities and social sciences.
Sociologists will tell you society will not take kindly to this or they may say with the existing structure this technology can lead to problems and so on. What drives the research scholar? I am hoping it is interest in an understanding of some aspect of the universe or making things the good God forgot to make. That is a quote from, it is an old quote now, I think it is from 2001. or 2002, Arthur Miller was the president of the US American, US Institution of Engineers, American Institution of Engineers and they have a one week celebration in February of not an engineer engineers day, they have engineers week. There are lots of posters and Miller was apparently sitting in a bus in New York when a little girl was sitting next to him with her mother and this girl kept asking her mother what do engineers do.
Then she kept looking around these posters and finally she said, oh now I know what engineers do, they make all the things that good that the good God forgot to make. He says that is a very good description of what engineers do. So that that That could be one reason why you are a researcher. Let's call it in this institute which is a good thing.
But PhD is also a prerequisite for some jobs in career advancement. If you want to be a faculty member, if you want to be a research scientist, you are going to get a PhD. It is also a good route to change career path.
If you are in one area and you want to change to another area, it is good to come back to graduate school. school do a PhD in that area, then hopefully it is not for want of current employment. Unfortunately a sizable fraction of our research scholars do come because of this reason and it is also not money.
This result is actually for chemical engineers but I suspect it is true of all engineering. They say in chemical engineering, there is a huge survey that the American Institute of Chemical Engineers did. They found a maximum of 10% more in lifetime earnings.
I mean you have to leave out the outliers. Some people make it to the top no matter what their discipline is. Those people you leave out.
By and large you take people who have ordinary career paths and 10% more in terms of lifetime earnings. So it's not. Not because you are going to make more money, hopefully for the love of it because you are curious and so on.
So the value is actually beyond monetary returns, of course it is good for your ego, if somebody has to call you doctor so and so, it is a little harder to curse you. And then research is its own reward, this is something that I want to emphasize, very often research scholars seem to think the reward comes later, that PhD is only a piece of paper, it is something that recognizes what you have done but more than that, doing the research itself is the reward. when you suddenly understand something then I think you have a, then what do research scholars work on? This is a sort of summary of the kinds of problems people work on.
First intuitive imaginative research leading to unifying loss, this is rare. If you are in that category then you do not need this lecture, you do not need any of it. The second is systematic gathering of empirical knowledge for applications.
This is measuring properties. For example, you may measure the viscosity of many substances. Of course lots has been measured but there are new substances coming up, you will have to measure their viscosity for the sake of applications or you may measure the viscosity be doing it in order to check the validity of existing theories. I think these constitute about 60% or maybe little less, maybe about 40% of the entire work.
If you look at journals and look at all the papers that come. you will find this is a very large fraction. Then extensions of existing theories, this is also quite common. A theory may be applicable to Newtonian fluids, you may want to extend it to non-Newtonian fluids.
Then synthesizing materials and characterizing them, this has become a, this has always been a big area and now it is much more so because of so called nano science and technology. 1959, I think when Feynman gave a lecture to the MIT professor, he gave a lecture on American Physical Society. The lecture was titled, there is plenty of room at the bottom.
It was the first lecture on nanoscience and essentially Feynman said that we have reached a point when we can manipulate individual molecules or sets of molecules and therefore you can change the structure of material so that you can get the properties you want. See when I was a student this was unthinkable and I mean that tells you partly how old I am but basically it was unthinkable. They said this is the property, you substituted that into the transport equations, you predicted what would happen and you say if you have this material this is what will happen.
Now you know what you want and you ask can you make a material that would respond to shear stress in this fashion. So you can ask such questions, you can ask for materials for example you have materials that are conducting one way and non-conducting the other way and they are used often in applications where heat is conducted one way but you can touch the material from the other side very practically touch it. So I think there are now what you have is a great potential to synthesize materials, you can change molecular additives here and there and create substances that have properties that you want but you have to characterize them of course, that is a very large fraction of the research. Now at the moment I think nano science and technology probably cover 60% of all current. Chemical modeling and simulation, this is an important part.
Although I must warn you that you should never get into mathematical modeling if you do not have a physical understanding of the system. I mean doing mathematical modeling for its own sake is meaningless although there are some useful occasions where you do that. For example you do neural networks and this is all this is done primarily for control.
It is not so much for understanding the science behind it but to understand the relationship between output and input of a system and use that to control the system. In chemical engineering it is used. used presumably in metallurgy also because in large number of systems you have lag in measurement. What you would like is find a product, set a set point, find the difference in properties between the product and what you wanted, use that difference to drive the process to correct it, that is feedback control.
But in most systems in chemical engineering particularly the feedback comes too late. For example, if you are saponifying oil to produce soap, you are adding sodium hydroxide to oil to produce soap. If you have added too much sodium hydroxide, you will know only after the results come from come back from the lab. By that time that batch is gone.
So what What people do is now do a mathematical model of the process, they give the disturbances that come in the feed to the model and ask what is the consequence. Use that consequence to control the process. So basically mathematical modeling is done in order to do anticipated control.
Then second is simulation, modeling gives you conceptual understanding and simulation is supposed to give you actual understanding. So mathematical modeling and simulation is now a large fraction of the. work.
Finally empirical correlations for design, should realize that a lot of our the science is still inadequate, a lot of systems are not sufficiently well understood and you must also realize very often industry is ahead of us that is if there is a profit to be made people will find a technology to make that material or to produce that service even if you do not understand the science behind the technology. So very often science comes after the technology is successful. You will always need empirical correlation.
for design partly also because we do not understand turbulence. So because you do not understand turbulence, you cannot do the correlations for heat transfer for all kinds of processes. So what you have to do is do it empirically and if you look at analysis basically in all of research, we divide a large problem that is to be solved into parts.
We divide the small parts. Sometimes there is a conceptual difficulty. You leave the half that contains the conceptual difficulty and solve all the problems related to the other half.
And once all of those are solved. people take the other half, again you divide into half. So analysis always proceeds that way. We do not know how to proceed otherwise. Occasionally a person has an intuitive flash and he produces an understanding that completes the design process.
But 99% of the cases we still have to cross the final design using empiricism. So empirical correlations for design are very much a part of engineering design. So now what are the characteristics of a good researcher? The first thing you need is a prepared and an open mind.
When I say open mind, I am not, I do not mean a vacuous, empty mind. I mean a mind that is full, but is still receptive to new ideas. Then, you must have a broad interest in several areas.
I must say, lot of you, although you have chosen your field, still do not know where your interest is. So, I think it is important for you to discover your interest and to keep your interest broad in several areas partly because an idea in one field may help progress in another field. So, I would recommend for example that you attend a large number of seminars.
In fact, in my own case, my PhD problem, I solved the problem actually I had to deal with molecules with angular angle dependent forces and the theory was already known for molecules. monatomic substances and in order to deal with this I had to deal with rotation and I had to deal with 4 dimensional harmonics in the mathematics and I was quite ignorant of what was already in the field at that time. In chemical engineering there was nothing.
So I ended up deriving a lot of properties of 4 dimensional harmonics, very uncomfortable with them because algebra was very complex, I had results that looked somewhat clumsy. Then finally I went to a physics department seminar simply because they gave very good beats. But the seminar was by a guy called Rose, you still remember, I did not understand 90% of what he said, but he was talking about angular momenta in quantum mechanics. And he suddenly showed me the 4 dimensional harmonic results and that were already been done and I just had to go back and verify, I was very happy that my results were right, but they had very elegant notation and a beautiful way of treating them. The idea is that it gave me such confidence then I could proceed further.
I think sometimes the idea comes from various fields, you never know. where it will come from. Then third property you need is capacity for hard work.
I think there is no substitute for hard work. Anything you get without hard work will always leave you a little insecure. So I mean it is always our students have a favorite way of saying they fundas are weak da.
So I do not know. And the main reason they are weak is because you have not put in the hard work to understand them. And Then another characteristic is desire to know the truth. You must have a desire to know the truth. In this context nowadays it is particularly important that you do not pretend to the truth.
I mean there are people who are good research workers who have fallen for this, who have done plagiarism or have manipulated their experiments. It never pays in the long run. So, you must have a desire to know the truth and an ability to challenge prevailing paradigms.
Then discrimination and aesthetics, I think this is very important. Ultimately, all research proceeds based on your sense of aesthetics. You think this is a beautiful way of doing it. doing it and not that and I think that is very very important, you have to develop a sense of aesthetics. When you read a paper, just reading the abstract you should be able to say whether the treatment is beautiful or not.
I think you should have an opinion on that, you may change it but you should cultivate tastes. Discrimination is very important because if I teach you thermodynamics and you have a problem in thermodynamics, you also read transport phenomena which is irreversible processes. if you arrive at an explanation of a thermodynamic problem at equilibrium problem through a non-equilibrium process, it is a very bad way of dealing with it.
It is a, I mean ultimately an equilibrium process should not require that you know how the system changes when it is not at equilibrium. I mean it is basically you must have the discrimination to say I will use only tools that belong to the equilibrium case and not use tools that belong there. So and the other thing I keep telling undergraduates is, and it applies to you when you do coursework in graduate school. Discrimination also means Now the amusing story is that I show an apple and ask you what is it and you shout orange. Then you have told me that you do not know an apple, you do not know an orange, you do not know both.
And a person like me I grade by negative marks. I give you 100 and then subtract whenever you make a mistake. So if you kept quiet you would have lost only 5 marks. If you shout the wrong answer you get minus 5 twice. So I think it is important that you be able to discriminate between.
between in this case apples and oranges. Then ability to learn from mistakes of the past and mistakes of others, this is a peculiar ability that human beings have and I think it is important that you learn that and finally a positive attitude and faith in the scientific method. Basically you can challenge the method but basically you have to have faith that this is a process by which I can do things in a reliable manner.
Let me say a few words about learning and creativity. The split brain experiments are experiment that were conducted by Rogers Perry in 19, he got the 1981 Nobel Prize in Physiology and Medicine. He and his co-workers have elucidated the learning process.
There is a beautiful book by his student Gazzaniga on the brain, but I think a very nice summary is given by a person called Blakesley. It is called The Right Brain and this is a summary. It says essentially two sides of the brain are fundamentally different.
The left brain is logical. logical, thinks in words and is good at step by step reasoning and the right brain is intuitive and musical and uses visual images to draw conclusions. The creative process itself, this is an over simplified summary but gives you a pretty good idea.
There is a preparation stage where information is gathered by the left brain. In fact I keep telling my colleagues, if students do not listen in class, do not worry, their left brain is anyway collecting the data. It's actually true, you will know when you read for an exam and even when you are not attentive in class, when you are reading for the exam you suddenly tell yourself, oh this is why the guy was going on and on in class about this. You suddenly understand something and you know why the teacher went on and on about it even though you are not listening because your left brain was listening. But that's the preparation stage where you gather data, it's information gathering stage.
The second and the third stage belong to the right brain, it's called the incubation stage when the right brain tries to see the whole picture. the illumination stage when the right brain's insight and intuition generate possible solutions and you think you have hit the right solution. But this is often, this happens to you at night when you are reading just before the exam, suddenly things fall into place and everything seems to be right but when you enter the hall it breaks down and you become nervous again and this is typical, I mean the right brain is intuitive, it generates solutions but very often the solutions are wrong. So, you need a verification stage. where the left brain logically tests the solution.
In fact, we take this for granted now but it is only Galileo who said experimentation is very important, verification. Before that, there was a peculiar situation. First let me say this, freedom from logic and structure is what makes the right brain so effective in generating ideas.
Since most such ideas fail when tested logically, the left brain is not effective. ...is equally important. It is the synergy between the two parts that is the real basis of creativity. You need both and basically the coursework is usually based on logic. All of university education is mostly based on logic because I cannot really teach you intuition.
I can only tell you what I understand logically I can explain to you. So you have to nurture your... right brain.
You have it and you should nurture it and you should realize that in our tradition and in the Greek tradition, the left brain was usually that of one person and the right brain was that of another. Typically we collected data and went to a sage who used his right brain, his or her right brain and explained to you how all the confusing things that you had in your mind fit together. But because the sage said it, we could not verify it. I think my favorite anecdote is that of Aristotle, you know, he said women have fewer teeth than men.
This was some 260 AD. It was 1450 AD before somebody finally said no, no, Aristotle was wrong, I have actually counted the teeth of men. men and women, they have the same number of teeth. And mind you Aristotle had two wives and he never counted their teeth apparently.
So but I think this kind of thing happened in both and it's Galileo who said you have to question everything and now if you have a good new theory of science, you have to propose an experiment that may lead to its downfall. For example Einstein proposed that you measure the bending of light during a solar eclipse from a place in Africa. where it was a cloudless weather and there was no new moon.
So you could actually see the light in bending and Eddington went and measured it. It was exactly as Einstein predicted. If it was not Einstein's theory, it would have been thrown out.
But Einstein had to propose that experiment. So basically the creativity results from a meeting of unlike minds. That is somebody's strong right brain, somebody has a strong left brain. So you need not be in the middle. in the same person and you should have a meeting of unlike minds which is why in the university I recommend very strongly, you tend to one tends to group into like minds, you know you make friends of people who are like minded but I think in the university you should make friends with people who have an unlike mind, even if they make for a little unpleasantness the chances of joint creativity are higher.
The university basically trains the left brain, you have to nurture your right brain, I will tell you incidentally in my thermodynamics course I have told. students often that even if it is a complex problem you have an intuitive understanding of it so write the answer on the top. So and then I tell them then do the problem logically and verify if logic confirms your intuition.
Typical of IIT students, they write that intuitive answer in pencil, work out the problem. If it doesn't agree, they erase it and write this answer there. I tell them there are no marks for it but they still play it safe. It's not for me, it's for your own sake. If your logic confirms your intuition, you will get self-confidence and very often you have a feel for what's right, what's likely to be this.
So, then I want to talk a little bit about manage, this is special to IIT Madras because we have a research park. The university is the source of almost all creativity in history and the question is how can university manage its creativity? There are two methods that are described usually, guy called Schrager describes these and I think he has a book on creativity, I forget the name of the book.
Usually there is a magic garden approach where you hire brilliant people, you hire brilliant minds create the right atmosphere and leave them alone. If you are director of the institute you pray because they may sometimes retire without doing anything. This is the risk you have to take because the brain is very good, you must have it in the university. The second approach which is called the idea factory approach was actually evolved in research labs in the US in the 30s and 40s, Bell Labs is the most famous for it. The idea was to bring unlike minds together from different disciplines.
together and allow them to have create the right atmosphere, give them a lot of freedom but structure interactions. And anyway minds can be unlike in different ways. First unlike success of meeting of unlike minds is the US graduate school typically where they take people from different cultural backgrounds.
You must realize that science is universal but the scientist is not. The scientist has a cultural background therefore a set of prejudices. So if you want to overcome at least some prejudices, you must mix people from different cultures and the US did it by accident. Because it's a country of immigrants, they were very, they have been very successful.
Second is disciplinary training, that's the one I told you about Bell Labs. They brought together mathematicians, physicists, chemical engineers, electrical engineers, all kinds of people in one group. And that group produced most of the results in solid state physics. Even Bardeen was in that group. But afterwards they called it the solid state physics group, then they lost a lot of their thing because now you needed a visa, you should have done solid state physics in, either your undergraduate or post graduate to get in.
I think you need to have a mix. In the third is attitude, university research parks where you have the, I think I have a, yeah the university research park is basically a property based venture near campus like we have done here and creates a local concentration of skill and technology. It promotes innovation, competitiveness and entrepreneurship.
It helps convert research ideas into innovative technologies. It houses R&D of companies, creates and nurtures start-ups and drives technology-led regional development. The idea in this is this, it's called the golden triad. You have three types of people. The students who have a spirit to conquer and faculty who have a sound knowledge of fundamentals and R&D personnel from the industry who have an awareness of the market value of an industry.
idea. So, if you have these 3 minds together then see students are likely to come up with a large number of ideas, but they have the advantage that they can come up with all kinds of wrong ideas, nothing happens to them. A prof for example is considered an expert, once you finished your PhD you are considered an expert, then if you say some rotten ideas they will say don't you even know this, whereas in you are a student you have the freedom, you can make 99 mistakes and the 100th idea may be a great hit and that's all that's required. So, you need this combination.
And why IITM research park? We did an analysis of IPRs in Silicon Valley which is probably created the largest number of IPRs per unit time in the 90s and we found a very large number of them have the names of alumni. alumni, almost 50%. So, I mean they have many names, one of them is an IIT alumnus. And Louis Pasteur said discovery is the result of chance meeting a prepared mind.
In particular I think he was talking about the discovery of penicillin. I mean for example, had an idea of what was, when he saw this fungus, when he saw this thing growth, he realized that there was a cure for. for diseases.
Anyway, so he said this, he said discovery is the result of chance meeting a prepared mind in experimental research. I omitted that and I quoted this to MHRD and I said IITs have been preparing minds and chance has been meeting. them in silicon valley. So I said they need to meet chance in our backyard and MHRD agreed.
So we started the IITM research park, it is an independent section 25 company, I think now the section has been changed, it is called section 8. shares in startups, IIT Kant, we got 11.5 acres from the state government, I wanted it just outside the campus and luckily for us the MGR film city was closed down. So they had 40 acres and out of which we got about nearly 12 acres, 11.5 acres and the state government was very generous, they gave us that land, it is adjoining us. The idea is that the values in an academic institution are different from values in a marketplace so you should not mix them if possible.
So I preserve, in fact I told the chief secretary, he said you have 630 acres, why are you asking me for 12? I said 630 acres of pure academic land where only Saraswati will be worshipped and I want a place where I will worship Lakshmi along with you and with the industry and just on that basis he said yes, he was very enlightened chief secretary that time and he gave me 7 acres, then the government changed, they gave me another 5 and half acres. So we got about 11 and half acres. and a half acres total and MHRD gave us 100 crores, it took about 7 years but finally they gave us a 100 crore loan, they are going to make it a grant and we decided to put 1.2 million square feet in 2 phases in this, 85% is for R&D, 15% was incubation.
The search parks, university research parks exist everywhere else in the world. In India this is the first research park. In fact when I started talking about it in 2001 when I became director, 2002, no 2005, is when Dr. Chidambaram, who was then our chairman, he wanted me to go to the US to attend meeting of the Association of University Research Parks. He said, you go represent India.
I said, what India? What research park? There is none in India.
He said, you are the only one talking about it, so you go. And I went there and the first speaker was a Chinese. This girl, lady, she is quite young lady, she got up and said China has a very modest program only 100 research parks, only 100 acres per research park.
only 10,000 companies in each research park and only 1.2 billion dollars of support from the government. So I put up my hand and said, can I go last? I was next on the list and he said nothing doing, you have to speak in this order.
Then I went. up and said one research park, 10 acres, you know, I mean our budget was 300 crores at that time. But anyway, actually China has overdone it, a lot of our research parks are empty. But the point is I think research parks are an important source of innovative technologies.
Now research parks as far as research colleges are concerned also give you chance for summer internships because you get ideas from research there and incubation, if you want to start companies, a lot of IT people have started. companies already. So this is the research park, you must have seen it. I do not know if you have visited it there.
Okay good. Then this is our clients, we have got clients in all sectors and there is also a lot of interaction between the clients that has also generated a lot of research. I think we have a total of some 75 patents per year now.
We used to be 5 and this is very amusing because in 2005 IIT Madras got the award for the university that produced the largest number of patents. of patents. So the commerce secretary called me and said I want to congratulate you.
I said are you sure we got only 5, he said others have less. So it is not that we are not creative but this patenting the idea of intellectual property right was not there and we created a cell here but after the research park came this has increased tremendously. These are some incubates. So let me now get to some advice.
General advice, the PhD problem is yours, so you have to help choose it. By and large we find I had 18 PhD students, only 2 of them help me choose, I mean help choose their own problems. We give a general area because most of us faculty have an area of expertise. So we say within this area if you want you pick a problem.
Usually I used to give students about a year, year and a half and they never came back with a problem. In one or two cases, in two cases they came up with and so the thesis is also yours when When you write your thesis, it should be in your style. Of course if you make mistakes, your guide will correct it.
But by and large, you should have a style of writing. It's a story after all. And research is iterative. You must remember that results very often come in spurts.
There are whole times, year, year and a half when no result comes and you can feel very frustrated and there are no clear intermediate steps. They are very rare. And you have to avoid the temptation to attribute the failure to experience. external causes.
Normally the advisor is what takes the...every student thinks the advisor is indifferent, incompetent. They will come and tell you when you are dean of research, sir I have a problem and very seriously they will look at you, they will say you should not be angry with me but you know my advisor is indifferent and things like that. Actually he is not indifferent.
Usually you take a PhD student because you have run out of ideas, you have got some basic idea but you do not know how to tackle a particular problem, you are hoping this new mind will come up with an idea and then you put it together. that's how I mean if I could solve the problem myself why would I take a student at all. So it's not 90% occasionally this is true okay 1 in a 100 may be true or 1 in 1000 but by and large advisor is not indifferent because he also doesn't have an idea, he is waiting for the nucleus 7 idea to come.
His incompetence is not something that a student can usually judge, it is very rare. Then the other thing is he says problem is too difficult, it is ill-defined. These are things that.
First of all problem too difficult is common assumption but very often after they finish they very happy that they solved a difficult problem. It is ill defined very often you have to define the problem carefully, you have to know what is possible, what is not possible. The environment is not conducive for good work. Normally I find if a student is really good, they get into these conflicts right at the beginning.
I mean not, they do not say the advisor is indifferent, they go argue with the advisor as to why I should work on this problem. But that is out of. of interest.
If you have goofed for 3 years and then you go and complain to the advisor is indifferent or the problem is difficult that means you are just trying to escape from disciplinary action that might follow. So I think the important thing is that the problem is yours, you have to define it in such a manner that it is meaningful. You must know after you finish the problem where what the direct what is the direction of your research will be if you continue as a faculty.
Some do's and don'ts. Acquire scholarship. When I say most of us are not so original, I am not being, you know, pessimistic. It's a fact that we are, there are very few people who are really original.
I am talking about Newton, Einstein, people of the highest caliber, but most of us are not that original and what we are talking about is solving a problem for the first time, but solving it as a follow up of some theory that has already been formulated. So, but you should acquire scholarship. I think that's very very important. So, people very often do not take courses. Every student and the guide also comes to me and says, sir we want to finish these four courses in the first year, as if it is something to be got rid of.
So you take whatever courses available, actually you should take courses that are meaningful to your research and if you take more courses it does not matter. In fact, I probably have a record for the largest number of graduate courses in US, in Florida because the chairman told me why are you taking so many courses, I told him I am not original, so I want scholarship. He was a very nice gentleman. He called me in the evening. He said, this was in a coffee room.
He said, come and see me young man at 4.30 in the afternoon, evening. And the secretary Karen Walker told me, Ananth you are in trouble. When he says come and see me young man, he is going to give you a lecture that you will be sorry to hear.
So, I went in at 4.30 and I told Faheyan, before you say anything, let me say this. I think, I think I am very clever. In my class of 30 students, I think only Charlie and the bros may be cleverer than me, I am certainly cleverer than all others but on the other hand I don't think I am original enough to impress myself.
Then he surprisingly he smiled, he called for coffee and he said you are quite mature, you have to make this decision but don't underestimate yourself, you should work very hard. The point is of course you shouldn't underestimate yourself but on the other hand it is important to realize that many people are not so original. It's good to acquire scholarship because when you learn many areas then ideas come in the area that you are really interested in. I have already said this aesthetics and discrimination, acquire a feel for the subject and interest in the problem and increasing obsession with it.
I am afraid that is not something that seems to happen, I wish people would do that. I mean I have before I became director at least not many students, many students did not know me, so I would walk to the canteen and try to over here what students were discussing. Of course they discuss a lot of politics, lot of cinema, but I was hoping at least 15% of the conversation will be about their research.
I am afraid it was not, I think it was about 10%, I am hoping it will increase with time. Then anticipate results but retain your capacity to be surprised. When a synopsis is presented in the dream researcher's office, people present the results as if it is routine. Some of it could not have been routine, they must have been surprised.
Then I ask them, did you really expect this? Then he says yes. Then I ask them, what is your intuition about this?
Then they say the opposite. Then I tell them, then why are not you surprised? I am not surprised. you have lost that ability to be surprised, I think that should not happen. Then do not investigate a problem without being sure it is worthwhile but this must begin right at the beginning, you must discuss with your guide because the guide is also can also be mistaken about the value of a problem, there I mean at the PhD level you are more like equals.
Then understand physics before attempting optimization, people try to do modeling and optimization without understanding the physics. So more do's and don'ts. and don'ts, discuss problems in the area constantly, I would recommend that very strongly because you never know where ideas will come from, people who don't know the subject can give you very good ideas.
Then do not be afraid of making mistakes, avoid sophistry, you must know the jargon in your field but you shouldn't hide behind it, explain your research to a school kid till he or she understands you, you have to buy them some chocolates or something, ice ice, but I have recommended this, only 2 of my students took this. suggestion and they ended up with...I mean some of the students they explained to were their own cousins or something in school. But the point was that they...when they wrote their thesis, I didn't have to correct it at all.
Because when you explain it, you know the story fully. Otherwise you end up having Ravana kidnap Sita before Sita marries Rama. Then there is no Ramayana at all. You have to have the right order. Anyway, communicating research findings quickly and clearly is both a privilege and a responsibility.
It is a privilege but it's not a responsibility. but it is also a responsibility because all research is a cumulative effort, everybody pitches in puts in epsilon and all of it together is what solves problems. Here I would say make many mental drafts, I think this is important, I prefer mental because when you write it takes a long time but if you can envisage the whole thing and make the draft it be wonderful. You have to be brief but complete, you have to practice pre-c writing, I do not know if If you have done Pre-C writing in school, our teachers used to make us write, write an essay they will say make it one-third the size that is Pre-C without losing content.
And one student came back, came with some 500 pages, then came back with one third, then I said make it one third further, he was about to hit me. But finally he was very happy with his thesis because it was brief to the point and it was excellent, very well written. I think it's not the volume, once you have the ideas right, you have to write the... you have to learn to write it briefly. Value of the work should be obvious from the abstract, you should write an abstract that tells everybody exactly what you have done.
in the field. Then second is time spent on any aspect of the problem is seldom proportional to the number of pages it occupies in print. Sometimes a whole year's work may see only one line in the thesis. This is can happen because you have now you tried different ways of doing it, did not work out and then finally you arrive at it.
So you will write a paragraph about how some of the approaches you used and how it did not work and the actual way you did it will take all the pages. Then give credit where it is due. I think that is very important.
do not plagiarize. I mean that is becoming increasingly important. I was just coming from Bombay by plane and one civil engineering professor was travelling with me.
He said he had just admitted a student to his group and threw him out on the first week itself. At the end of one week he was met, he met him and he said what are you going to do? He said I do not know somebody must have done this problem, so I will take this that and put it together and submit a thesis and said leave the. You are not going to stay. And also he said, the student said, if the experiment does not work, I know how to adjust things.
I think those are things that you have to avoid at all times. Take reviewers comments seriously. When you, you have to write your paper up and send it. Reviewers comments can be very damaging sometimes, sometimes very puzzling.
I had, my most interesting experience was with industrial engineering chemistry. We had done a work on deactivation of catalysts. there is carbon deposition, the catalyst gets deactivated, we had done a very complicated modeling of the system and we coupled partial differential equations and we solved it, had beautiful plots but by the time we finished all that we got so tired our results and discussion was one paragraph and we sent it off and then the reviewer said very good problem, very good formulation, very good solution, so what, that is all he said, he said so what.
Then Pickford who was the editor of the journal said I could not agree more with the editor with the reviewer please revise and send it. So we sat down for one month we took to write the results and discussion. The idea is if you have done so much effort you must be able to explain the results so that others do not have to do the computation and all that effort to understand what the physics is.
So when we finally wrote the discussion alone we only changed that section and then Pickford said I do not have to send it to the reviewer I am accepting it. It appeared afterwards. I think in India particularly we do not write results and discussions with enough care.
Very often you get exhausted by the time you solve the problem. Therefore you do not, but I think that is very very important. I think the last slide is about ethics. Conducting research is an exercise in ethics and a test of character.
I think that is very important to realize. The results of research are ethically neutral, but the researcher cannot remain neutral in respect of its applications. The most dramatic example is the case of the Indian government.
example I can think of is the atom bomb. All the research that was done to develop nuclear power was done after quantum mechanics was born 20s, 30s, 40s and when they finally discovered, understood everything about fission, then meanwhile due to historical accident, people were afraid Germany will make the bomb. So America rushed to make the bomb, they made it, they dropped it on the, at that time the Japanese scientist who had participated in the quantum mechanics and this thing was terribly devastated. He said he never thought his colleagues would do this.
But eventually what happened was a lot of scientists went into a depression because they felt. Suddenly, they had pursued truth, they had pursued the truth about nuclear fission and it had resulted in a bomb that killed hundreds of thousands of people and maimed many more for many years. So you cannot control this and even after that the hydrogen bomb was worked on and Edward Teller made a famous statement saying, I cannot help working on the hydrogen bomb, my curiosity is overwhelming.
How it is used is not my business. I think that is no longer true. The only way to control that, it is not really...
really you, it is not in your hands, but the way to control it as I think for scientist to write about the research in common journals. in a popular journals not giving technical details but telling them what the consequences of the research may be. A well informed public is the best protection in a democracy against misuse of science.
So I think that is important. Finally I will close with a statement on value of values and this was Swami Dayananda Saraswati who spoke here in IIT Madras about 10 years ago. He passed away recently. He said, don't try to tell students about values, they already know. If you tell, for example, if you take a thief and tell him, don't rob, it's not a good thing, he already knows it's not a good thing.
So he said, instead talk about the value of values. There are many values. One could be acquisition of power, another value is acquisition of wealth, another could be acquisition to just fulfillment of desires and so on.
All of these are values. But there is one universal value which is called non-violence. Because you don't want to be hurt, you shouldn't hurt others. But Swami Dayananda Saraswati like Gandhiji also said, So he explained that non-violence is not just absence of physical violence, it could be mental violence, it could be any form, but you know when it is violence. So you know when it is non-violent.
And then... when somebody has used violence against you. So he said, teach them that the value of non-violence is greater than the value of power, is greater than the value of wealth and greater than the value of fulfilment of desires. And then tell them that if they acquire wealth, power or fulfil their desires through non-violent means, they are welcome to it.
And Lord Krishna says, that's the path of Dharma. So if you walk the path of Dharma, I will walk with you. Otherwise you walk alone. There is no punishment. You walk alone.
Then he looked, there were four-fifteen 50 students in the hall, he looked at them and said, you think walking alone is easy and most 20 year olds plus or minus 3, they all said of course we will walk alone. Then he said it was the day after the exam, you know this Taramani temple next to Taramani, I don't know if you people still have that story. My students used to say if you come around that temple you are supposed to get 5 more marks. When you come to the exam you just cycle around it and come to the exam. He says may or may not be true.
why take a chance if you get 5 marks why not. So then he asked them he somehow knew about it he said and 400 hands went up in the CLT. Then he said that's what Krishna means by walking with you.
I mean it's not something dramatic it's simply that human beings need something to hold on to and they create various forms of help for themselves and I think the point he made was very valid that if you know that non-violent ways of getting anything is a acceptable then you are welcome to it, if you use violent means it is just not worth it and I think that is important to remember right through and being ethical is rather important, so I think that is the last slide, thank you very much.