Computer graphics scholar receives Distinguished SFU Professorship
By Andrew Ringer
SFU computing science professor Richard Zhang, a renowned visual computing and graphics researcher, has received a Distinguished SFU Professorship. This achievement recognizes the top research faculty members in the university for their exceptional performance and distinguished accomplishments.
“This is a great honour and a recognition for our hard work and dedication. I immediately think of all those who have worked with me, from my mentors to my excellent students. It has been a privilege to be in such good company,” says Zhang. “On a personal level, I feel that I must hold myself to an even higher standard of excellence in research, teaching and contribution to the university and community.”
Zhang is a visual computing researcher, who specializes in computer graphics and computational methods to understand, process and generate visual data. In particular, he focuses on 3D data such as the shapes of everyday furniture, industrial models for design and production, and scene environments for virtual and augmented reality. Zhang’s research also explores the use of machine learning and shape analysis to train robots to identify and interact with objects in its surroundings.
Due to his expertise, Zhang is often involved in industry projects. For example, he is currently working with Autodesk, a leader in 3D design software, to turn 3D models generated by machines into something that can be manufactured. This is done using traditional fabrication methods such as computer numerical control, which describes the automated control of machine tools and 3D printing.
He is also working with Google to train deep neural networks to understand, predict and generate 3D shapes. This collaboration led to a research publication that recently received the Best Student Paper Award at CVPR 2020, an annual visual computing conference and the top conference in computer science in terms of impact.
While his expertise is regularly sought out for industry projects, Zhang’s academic contributions are also significant, publishing more than 150 papers, mainly in the top venues of his field, and being cited over 9000 times.
Zhang has also been an influential part of the professional master’s program in the School of Computing Science, where he previously served as program director and developed the visual computing concentration.
For the future, Zhang is fascinated by the topic of computational creativity, which is an emerging area of artificial intelligence that focuses on a machine’s capability of being creative. He is particularly interested in the possibility of training a machine to produce graphics patterns such as 2D logos and other creative visuals including product designs and virtual environments. While this area is relatively new and has not been explored much given the difficulty of the task at hand, Zhang and his team are determined to find answers.
“Personally, this is my ultimate problem. In one of our earlier works, we mimicked the evolution process where random mutation and crossover operations over 3D shapes led to potentially creative outcomes,” says Zhang.
“Now, with advancement in machine learning, we are exploring means to break the barrier of traditional learning paradigms to allow a trained network to venture beyond the training data, gradually, but surely, which will hopefully lead to creativity.”