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
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.
Ghassan Hamarneh
Area: Medical Image Analysis (Computational/Artificial Intelligence, Computer Vision, Image Processing)
Anoop Sarkar
Area: Computational Linguistics; Machine Learning; Probabilistic Grammars and Formal language theory
Yasutaka Furukawa
Area: Computer Vision, Deep Learning, Computer Graphics & Computational Photography
Greg Mori
Area: Computer Vision, Machine Learning
Oliver Schulte
Area: Machine Learning, Computational Logic, Computational Decision Theory
Maxwell Libbrecht
Area: Computational Biology and Machine Learning
COMPUTER VISION
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.
Greg Mori
Area: Computer Vision, Machine Learning
Yasutaka Furukawa
Area: Computer Vision, Deep Learning, Computer Graphics & Computational Photography
Ghassan Harmeneh
Area: Medical Image Analysis (Computational/Artificial Intelligence, Computer Vision, Image Processing)
Ze-Nian Li
Area: Computer Vision, Multimedia
Ping Tan
Area: Computer Vision, Computer Graphics, Robotics
Brian Funt
Area: Computational Color Vision
Mark Drew
Area: Computer Vision
COMPUTER GRAPHICS
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.
KangKang Yin
Area: Computer Animation, Computer Graphics, Humanoid Robotics, Machine Learning, Multimedia Analysis
Manolis Savva
Area: Computer Graphics, Computer Vision, Deep Learning
Angel Chang
Area: Natural Language Processing, Artificial Intelligence, Computer Graphics, Computer Vision
Richard (Hao) Zhang
Area: Computer Graphics; Geometric Modelling
Eugene Fiume
Area: Computer Graphics
CYBERSECURITY
Cybersecurity is an interdisciplinary field of study, partly building on classical information security, risk management, situation analysis, data analytics, applied cryptography, cyber forensics and several other areas. While the broader scope is interdisciplinary, the core is fundamentally a computing-based discipline involving technology, people, information, and processes to enable assured operations in the context of adversaries.
Mohamed Hefeeda
Area: Computer Networks, Multimedia Communications
Uwe Glässer
Area: Cyber Security Analytics, Crime Data Analysis, Situation Analysis
Andrei Bulatov
Area: Constraint Satisfaction, Complexity of Computation
Mohammad Tayebi
Area: Data Mining, Social Network Analysis
Ouldooz Baghban Karimi
Area: Data & Networks
Brad Bart
Area: Instruction
William (Nick) Sumner
Area: Automated debugging, debugging tools, concurrency & parallelism, program analysis & transformation
DATA MINING
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.
Martin Ester
Area: Databases and Data Mining
Ke Wang
Area: Databases, Data Mining
Jian Pei
Area: Databases and Data Mining
Jiannan Wang
Area: Database Systems and Big Data
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.
Rob Cameron
Area: Software Engineering Languages; Electronic Publication
Arrvindh Shriraman
Area: Systems architecture, hardware-software interactions, parallelism, sychronization and imporoving software reliability within specialized fields.
CLOUD COMPUTING
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.
Mohamed Hefeeda
Area: Computer Networks, Multimedia Communications
J.C. Liu
Area: Networking and multimedia communications
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.
Fred Popowich
Area: Computational linguistics and logic programming
Anoop Sarkar
Area: Computational Linguistics; Machine Learning; Probabilistic Grammars and Formal language theory
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.
Richard Vaughan
Area: Robotics and Autonomous Systems
Mo Chen
Area: Robotics and Autonomous Systems
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.
Parmit Chilana
Area: Human-Computer Interaction
Angelica Lim
Area: Human Robot Interaction
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.
Leonid Chindelevitch
Area: Computational Biology
Martin Ester
Area: Databases and Data Mining
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