Stephen Gould is Fellow in the Research School of Computer Science at The Australian National University.
"I was always interested in engineering and computers as a kid - I was devoted to Lego and got my first computer when I was 13. I spent all my time on that Apple IIe and I still have it, though now I tend to spend all my time on the iMac it sits next to."
Stephen received a PhD in Electrical Engineering and a Master of Science in Electrical Engineering from Stanford University, having completed Bachelor of Engineering and Bachelor of Science degrees at the University of Sydney.
"I now work at the intersection of two areas of computer science, computer vision and machine learning," says Stephen. "In computer vision, the goal is to get the machine to understand its visual input, so that it can detect and identify objects. In machine learning, the computer can learn from situations and improve its performance.
"Bringing the two together means that the computer can learn from the scenes it is shown and improve its recognition of particular objects. I want to be able to give a machine an image and for it to come back with a comprehensive description of what it is 'seeing'".
Computer vision and machine learning have many applications.
"Currently, when you search for an image in Google, what the program is really searching for are the words around the images. With effective image recognition you could get the computer to search for images directly, either from the words you give it or from a sample picture.
"There is a lot of effort being put into cars that drive automatically, without any driver. That means the car's computer needs to be able to see and recognise many things - roads, pedestrians and other hazards, road signs and so on.
"There are even applications in biomedical imaging. State-of-the-art medical imaging technology, such as MRIs, often use image recognition software for diagnostic systems to aid doctors. We are using image recognition to monitor the development of cells in an embryo, which will give us a greater understanding of cell development and may also help in developing new IVF techniques."
Stephen's career has spanned both academia and industry. Between completion of his Masters degree and starting his PhD research, Stephen worked in industry for a number of years. He co-founded Sensory Networks, a network security start-up company, and has developed freely available software libraries for machine learning and scene understanding. He holds eight international patents.
"My most notable achievements have been the start-up company that I co-founded, and just the satisfaction of the contributions I have made to the machine learning of the future," says Stephen. "I would like to be involved in other start-ups and new products - the whole area of moving between ideas and development to an actual product is a fascinating one. I would also like to mentor students in this as I think they benefit greatly from this kind of interaction."
"I have two kids and one more on the way and they keep me busy. I have also taken up woodworking, which is a great gadget hobby for an engineer, and it does get me away from the computer. In woodworking my most notable achievement is the toy kitchen I built for my kids!"