Patrick Olivier is an applied mathematician in the Technology Department of Park Medical Systems, a company in Lachine, Quebec, Canada that specializes in diagnostic nuclear medicine. His department is made up of 10 members and the projects he leads require interfacing with mechanical, electrical, software and bio-medical engineers, bio-medical Ph.Ds and high-energy physicists Ph.Ds. The main product of the company is Nuclear Medicine Gamma Cameras that involve robotics, gamma rays detection, software design and imaging algorithms.
He has been involved in the nuclear medicine field for five years, first obtaining a contract from a small company looking for a mathematical model for the behavior of photo-multipliers. He joined Park Medical Systems three years ago when a friend already with Park mentioned that the company was looking for someone with a Ph.D. in mathematics.
"When I was hired I only had to solve several numerical optimizations'" says Patrick. "People then got used to and aware of the importance and the efficiency that mathematics can brought to their work. One of the main consequence is that they attribute more importance and give much more trust to the mathematical contributions that can be performed in their area of interest."
He believes his ability to reason on an abstract level has helped him to be innovative. "Coming with a mathematical background, I am bringing an analytical and a new way of looking at the standard problems that nuclear medicine is facing" he notes. "Moreover, since I am able to communicate information to my colleagues, many people in the company are consulting me on various other technical points and issues."
He recently made a contribution to a project for defining the path that a robot of 6 degrees of freedom must follow. The movement occurs in 2D and concerns 2 detectors located at the end of a chain of 6 "joins". "The goal," he says, "is to set a path along which the detectors are tangent to, and to infer the positions of the 6 joins. I analytically and explicitly solve the inverse problem in spite of the non-trivial geometry of the robot. It then occurs that several benefits come out of this solution and, as far as I know, without any mathematical intervention, none of these features could have been possible"
Patrick has a bachelor's from the Université de Pau, Pau, France, where he began his studies intending to pursue further study in the area of electrical engineering. However, he found he was interested in a higher level of abstraction then he found in engineering and went on to study mathematics, obtaining a master's at Université Paul Sabathier, Toulouse, France and a Ph.D. at University de Montréal , Montréal, Canada.
When he finished his Ph.D. studies he realized that funding in theoretical mathematical research was scarce and that academic positions were highly competitive. "On the contrary," he continues, "medical science is still a very well funded science and it is also satisfactory to contribute to the society in such a valuable sector of the economy. Moreover the problems arising in nuclear medicine are over a wide range of scientific fields: mechanic, electric, robotic, control, network, imaging visualization, imaging reconstruction, noisy data and a lot more."
Patrick is enjoying his work in industry. "I really like to work on 'real life' problems. It is surprising how many of these problems have a deep mathematical background. I really enjoy digging deeply into real world questions in order to extract the most out of them and by this, expanding the possibilities that were available and communicating them to the engineering community."
The areas of study he has found valuable on his job include linear algebra, linear operators, orthogonal expansions, linear integral equations, transforms, numerical analysis, computer programming, and algorithms. In general he emphasizes the importance of a solid background. "One thing I know for sure is that a classical trained guitarist is playing rock better than a rock trained guitarist. The more fundamentals you know in mathematics the better it is. But, also the more you know about real-world applications the better it is. We have to work like mad to learn both worlds, keeping in mind that the applications are only examples of fundamentals. What are the fruits? Innovation, creativity and imagination come first. Then come efficiency, rapidity and opportunities."
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