FACULTY EXPERTISE IN THE PROFESSIONAL MASTER'S PROGRAM
SFU's School of Computing Science has several faculty members with expertise in the many aspects of big data analytics, machine learning, and visual computing. Our faculty's expertise spans across the vast spectrum of computer science.
Click on a faculty member's name to view his or her profile and contact information.
Machine learning is a subfield of computing science that deals with algorithms or models that learn patterns in data and are then applied to new data to predict similar patterns. While machine learning is not new, its application has gained new prominence due to the increasing amounts of data generated today. With big data, machine learning can yield even more interesting and accurate insights and predictions. But there are also new challenges, such as ensuring that predictions are delivered quickly and efficiently in real time.
Research Interests: Computer vision, machine learning, video analysis, human activity recognition, object recognition
Research interests: Machine learning, statistical learning for relational databases, computational game theory, computational logic
Computer vision is an area of study that enables computers to see, identify and prcoess images in the same way that human vision does, and then provide approriate output. Computer vision is concerned with the theory behind aritificial systems that extract information from images and then apply these theories and models for the construction of computer vision systems.
Research Interests: Computer vision and machine learning, looking into object recognition, human activity recognition and human body pose estimation.
Research Interests: Computer vision, computer graphics, robotics, 3D reconstruction, image-based modeling, image and video editing, lighting and reflectance modeling.
Research Interests: Computational vision and image processing, with an emphasis on computational models of colour vision.
Computer graphics refers to the creation, storage and manipulation of images and models. Algorithms and data structures are used to draw images using computers with the help of programming. Topics under this area of study include modelling, geometry, animation, 3D, 2D, digital images, 3D viewport, real-time rendering, compositing, user interface design, vector graphics, among others.
Research Interests: Computer animation, computer graphics, humanoid robotics, machine learning, multimedia analysis.
Research Interests: Computer graphics and computer vision focusing on human-centric 3D scene analysis, 3D scene synthesis for VR/AR content creation and learning through simulation, connecting natural language with 3D representations and data visualization.
Research Interests: linking natural language with visual and 3D representations, natural language processing, grounded natural language understanding, common sense reasoning for artificial intelligence.
Research Interests: Computer graphics with special interests in geometric modeling, analysis and synthesis of 3D contents (e.g., shapes and indoor scenes), machine learning as well as computational design, fabrication, and creativity.
Data mining is an area that combines techniques from database, statistics, and machine learning to tackle challenging, real-life and data-intensive problems. The goal is to identify concise summaries that describe the underlying patterns or distributions from which the massive observed data were generated. Such summaries are potentially useful for decision-making and many other purposes.
BIG DATA SYSTEMS
Big data is rapidly moving data towards the edges of the computing spectrum either into the mobile phone or into the data centres of cloud computing. There are many challenges in ensuring rapid availability of data at the required destination while consuming the least energy possible.
Cloud computing is about storing and accessing data and programs over the internet instead of a computer's hard drive. Though the area has seen rapid growth in the last few years, there are challenges relating to the efficiency and effectiveness of cloud services.
Research interests: Internet architecture and protocols; multimedia content, distribution, and processing; wireless mobile networking, cloud computing and big data networking, online gaming and social networking
NATURAL LANGUAGE PROCESSING
A large number of big data applications are based on the analysis of naturally occurring data in the natural languages, such as the web or data on Twitter or Facebook. In particular, the challenge of big data is to effectively summarize and visualize vast amounts of "unstructured" information in language.
Research interests: How computers can be used to process human language either to make it easier for human beings to interact with computers, or to make it easier for human beings to interact with each other; intelligent systems and their applications
ROBOTICS & AUTONOMOUS SYSTEMS
An interdisciplinary branch of science and engineering, this area of study looks into the conception, design, construction and operation of robots - devices that can move and react to sensory input.
HUMAN COMPUTER INTERACTION
Human-computer interaction (HCI) is a multidisciplinary field of study on the use and design of computer technology, particularly focusing on the interactions between humans and computers.
COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
Bioinformatics is about developing methods and tools to solve problems related to biological data. Computational biology is about applying existing tools to arrive at new insights about living systems. Many of our faculty are involved in developing methods for handling, analyzing, and visualizing big data related to genomics and molecular biology.