Special Projects

Stephen Lam, Staff Interviewer

Enscquire: Could you tell us first a lit-tle bit about your background? For example, how long have you been teaching at SFU?

Andrew: Oh, it was long enough that I forgot when I started. I think I was one of the earliest people who was working in the school. I think I started at around 1983 or 84 as a research associate.

E: Where did you go to school for your undergraduate and graduate studies?

A: All my education was from Poland, and I graduated with a Master in Phys-ics. The university I went to is one of the oldest in the world; it is about 650 years old. The university does not have sep-arate undergraduate and graduate stud-ies as we do here in Canada. So, the program is 5-and-a-half-years long all together.

E: Could you tell us more about per-sonal background, for example, your family?

A: Well, I have a wife and two kids. I wouldn't really call them "kids" any more because they are too old. And I would not tell you how old they are because that would tell you how old I am. But they are both in university.

E: Are they here in SFU?

A: Yes, both of them are.

E: Are they in ENSC?

A: No, my daughter hates science; she is an artist. And my son is in Computer Science.

E: So, could you tell us how and when did the project [prosthetic eye] start?

A: When I first came to Canada in 1982, there was an economical crisis and it took me 15 days to find a job.

E: Oh, that's quick.

A: Yeah, when you want to work, you can get a job. So, I got a job at UBC, and I was working with Professor Lakowski who is a world expert in colour vision. I was working with him to develop better equipment for vision testing. I learned quite a lot about vision. Here, I must thank Professor Lakowski for inspiring, teaching and helping me.

So, when I came to SFU and worked for quite a while on micro-electronics, I found that in practice, we are not limited in technology to build the eyes; the obstacle is how little knowledge we have about how the eye functions. This is why much of our research is on finding out and defining the many functions of the eyes. We are still unsure how much processing is done within the retina and how much is done in the brain. And we have to separate these functions and define precisely what they are, because we don't want to "put the brain in the eye", and we don't want to overload the brain with a lot of "junk".

Our eyes are extremely complicated, and a lot of processing is done within the eyes. And this is how we can see so quickly even though our brain is a relatively slow processor. The pro-cessing in the eyes is highly non-uni-form; we have a pretty wide field of vision but only a very tiny part of the retina is responsible for acute vision. The rest of the retina has extremely complex processing capability and this is what we are trying to develop now. Most of the processing is in 3D and this is where the technology limits us. We cannot make a 3D processor on silicon because silicon limits us to only 2D. So we use several physical phenomena to trick the nature to create something as I called it. By learning how the nature works, we learn immensely about how to make engineering better.

E: Could you tell us where the funding for the project comes from?

A: I have my own company and several companies have together founded an industrial association called OPCOM. My company is in OPCOM and there are also some very strong companies in OPCOM. We have [received] about several million dollars from the government and $800,000 is allocated for the eye project. With other funding, we have about $1 million for this project. Funding is always a very difficult issue for us and it took us a couple of years to persuade the government to grant us funding. What we are trying to do is to market some of the sub-systems that we have developed and put the money back into the project.

E: When did the project actually start and when do you expect it to be completed?

A: The project started a few years ago with a few students and we hope that we can have a prototype of an eye in 8 to 10 years from now. If we have more fun-ding, we could probably reduce it by two years. Some students worked on the project for their bachelor and master thesis.

Let me tell you more about how the eyes work. Our eyes are really good at distinguishing colours differentially and terrible at distinguishing colours absolutely. That is, our eyes are really good at telling contrast between col-ours. There are mechanisms in the retina that emphasize or amplify differences. And I can tell you that my suspicion, which is strongly confirmed by simple but very convincing experiments, that when an eye sees a big uniform object with the same color, your retina does not deal with the inside of the object, it deals only with the circumference of it.

And the retina doesn't send signal about the colour inside the object, but only sends the signal about the colour of the circumference, and then the brain fills it up. Because it does not make sense to send all this information, the brain knows that when it gets information about the circumference of the object, it knows that it has to fill the object with the same colour.

E: Then, what about different shades of the same colour? For example, different parts of your green shirt have different shades.

A: Well, it means that the shirt has quite a lot of different contrast, and the retina has to identify all of these contrasts.

E: So, your eyes will draw out different parts of the shirt.

A: Yes, but you see, the eye concen-trates on a little part of the shirt at a time. Our eyes scan, just like we cannot read the entire page of a book at once.

E: This is amazing.

A: I can tell you that we know at most 20% of our eyes. This is why the project is so interesting and exciting because we know we are going into an unknown.

E: This is quite a complicated project.

A: As you have probably realized, the project is designed in such a way that it is divided into many smaller individual components. For example, we have developed a model for our variable focal lens, and we have tested it. We found that beside the application in our artific-ial eyes, we can redesign and build this lens in such a way that we can replace defective lens in human eyes. So this lens can be surgically implanted. Pretty soon, we are going to test this lens on pigs.

Other subsystems such as the receptive subsystem can be used in sec-urity systems, laser testing, laser beam diagnostics. And hopefully, we can sell these subsystems so that we can fund our project. I have estimated that, even with our efficiency, the project requires at least 5 million dollars of today's currency.

E: Was there any student who worked on this project for a thesis? And is there any potential for ENSC-370 projects, undergraduate and graduate thesis projects?

A: Yes, there were quite a few of both undergraduate and graduate students who worked on this project for their thesis. And there are currently 1 undergraduate and 3 master students working on this project. And I think there is plenty of potential for future thesis, 370 projects and project courses. Those students who are interested can come to me and talk about it.
[Interrupted by a phone call]
A: You see, this is how I work. I work 12 hours a day and I have no weekends, sometimes I don't even have nights. For example, when I fly to Ontario, I fly at night so I don't waste my day. I spend a lot time dealing with business people and bureaucracy.

E: That's tough.

A: Yes, but you see, when you want to accomplish something, especially something ambitious like this, you have to work very hard.

E: So how does your family react to this? Are they supportive?

A: I don't know, I hardly see them. No, actually, I spend quite a bit of time working at home also.

E: I have learned so many things about the wonderful mother nature.

A: I always say that engineers should spend more time observing mother nature. Learning from the books is very artificial; we as engineers should try to observe how mother nature engineers. We can always learn how to make engineering better by observing our surroundings. In here, when something does not work, we add things to the system to make it work. Mother nature does just the opposite; she simplifies it. When something does not work, mother nature gets rid of it and makes a new simplified version.

E: Thank you very much for telling us so many wonderful things today. Is there anything you would like to add?

A: I hope that the students reading this article will recognize how complex mother nature is, and how much we can really learn from it. We should all start observing our environment and see how we can improve our engineering skills.

E: Thanks.

A: You are welcome.

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