Chats with Kelly Gotlieb, "the" Internationally Renowned Pioneer in Computing - Kelly talks about his work in Academia

Kelly GotliebThis week, Stephen Ibaraki, FCIPS, I.S.P. continues his exclusive interviews with computing pioneer, Calvin C. (Kelly) Gotlieb, C.M., M.A., PhD. (University of Toronto), D. Math. (Hon., University of Waterloo), D. Eng. (Hon., Technical University of Nova Scotia), Fellow CIPS (FCIPS), Fellow of the Royal Society of Canada, the British Computer Society and the Association for Computing Machinery.

Kelly Gotlieb is currently Professor Emeritus in Computer Science and in the Faculty of Information Studies at the University of Toronto (UT). He is a computing pioneer, whose innovations and accomplishments helped lay the foundation of an entire worldwide industry, educational stream, and profession. His contributions are so profound and their impact so diverse and in so many areas that the lasting value cannot be comprehended. Have a look at this blog to find out more:

To listen to the interview, click on this MP3 file link

The latest blog on some selected interviews can be found in the IT Managers Connection (IMC) forum where you can provide your comments in an interactive dialogue.


Interview Time Index (MM:SS) and Topic

:00:39: Before we get into your substantive contributions in Academia, can you provide background of what triggered your initial interest in science?
"....When I was about twelve, I would get university textbooks and read up on how to make gunpowder and how to make rockets....I had a strong interest in science and chemistry....I read a lot of (other) books besides chemistry books, ....I always thought that if you were reading a book you would insult the author if you didn't finish it, so I always finished what I read no matter how dull it was. I read a lot of garbage but if you read enough garbage, you begin to understand what is good and what is bad. I learned to read quickly and I unconsciously learned to sort out what was good and what was garbage...."

:04:48: Kelly profiles his educational history.

:10:52: Can you describe your time with graduate school leading eventually to your PhD?
"....As far as I know those are the only classified PhDs that have ever been done and they were never declassified. Now, if you tried to do research which was classified, you'd probably find students marching against it because the whole idea about university is that the research is for the good of mankind...."

:18:43: Can you describe the environment in the early days at University of Toronto?
"....It was a much smaller and a much more tightly knit group...."

:19:28: How did the first courses in computing eventually lead to graduate education in computing?
"....In Canada they decided, much to our advantage, that the best place to put money on computing would be in the universities because then you would teach people and would more likely be available to Canadian industries and Canadian companies..."

:26:04:  You were a very critical part of building the foundation of the industry and building the hardware itself and evolving the hardware. This led to creating the first courses in computing and eventually to graduate information in computing. What kind of courses did you offer and how did that evolve into a graduate department in computing?
"....In Canada, as we got the Ferranti computer in 1952, a lot of the interest came from industry. One group was insurance companies, another group was Ontario Hydro...There was a huge public interest on the arrival of the Ferranti computer....We started offering courses in the extension department of the university in night school...non-credit courses....but well attended by people in industry....After about two years....I got permission to give credit courses....They were formal academic credit courses....graduate courses....Then as we got electronic computers...I started offering courses in programming languages....artificial intelligence....information retrieval....Each time a new subject would come up, I almost always gave the first courses...."

:30:40: Kelly talks about when the first graduate students finished at University of Toronto.

:35:28: Kelly was involved with a series of computers at the University of Toronto and through these computers many contributions were made. He shares his experiences.
".....We continued on ....three streams....A teaching stream, a computing stream (where we did a lot of calculations and issued reports....), and building computers....We finally phased out of the building of computers and concentrated on computing and teaching...."

:41:45: Kelly talks about some of the problems that were worked on at the computing center during this time period and the contributions made using these computers.
"....We had an annual report in which we listed the problems and in a year there would be several hundred. I deposited in the university archives some of these reports but unfortunately it is not complete. But there was a tremendous variety of problems....graduate problems, problems coming out of medicine for example....Canada had the first postal system in which you could read the postal codes by computer and these were all demonstrated on our computers....research on the St. Lawrence Seaway....another project was the work on the Avro Arrow...."

:52:14: In terms of other aspects of your research, how did that evolve over time?
"....We did all these useful calculations for industry and we did work on numerical analysis which resulted in some theorems so we had students in mathematics, medicine, geophysics which contributed to the spread of computing into a lot of disciplines....and into industry....Canadian academics have been very successful in helping to proliferate the use of computers and keeping the country productive....."

:55:47: How did your teaching and students evolve over time?
"....I've been blessed with good students who made my reputation...."

:59:14: Where do you believe education is heading at University of Toronto?
"....You have to choose some area of excellence......One of the areas that University of Toronto is particularly good is in machine learning....You can't be good across the board anymore.... I think it is necessary for university departments to see what they are good at, to build on its strengths and to try and become first rate in three or four areas...."