Research Groups

  • Computer Vision and Robotics: This is one of the most influential vision and robotics groups in the world. It is this group that created RoboCup and the celebrated SIFT features. The students in this group have won most of the AAAI Semantic Robot Challenges. The group has four active faculty: David Lowe, Jim Little, Alan Mackworth and Bob Woodham. 
  • Empirical AlgorithmicsLed by Holger Hoos and Kevin Leyton Brown, this research group studies the empirical behaviour of algorithms and develops automated methods for improving algorithmic performance. Work by the empirical algorithmics group at UBC/CS has lead to substantial improvements in the state of the art in solving a wide range of prominent problems, including SAT, AI Planning and Mixed Integer Programming, and won numerous awards. 
  • Game Theory and Decision TheoryWith Kevin Leyton Brown in the lead, this group has made significant contributions to algorithmic game theory, multiagent systems and mechanism design. David Poole also contributes to this group with his work on decision processes and planning. The research problems attacked by this group are therefore of great importance to e-commerce, auctions and advertising.
  • Intelligent User InterfacesWith Cristina Conati and Giuseppe Carenini this group's goal is to investigate principles and techniques for preference modeling and elicitation, interactive decision making,  user-adaptive information visualization and visual interfaces for text analysis. 
  • Knowledge Representation and Reasoning: David Poole leads this group with his foundational work on probabilistic first order logic and semantic science. This work on logical and probabilistic reasoning has been of profound and broad impact in the field of artificial intelligence (AI). Holger Hoos is also an important member of this group with his work on satisfiability (SAT) and planning, which has won numerous awards and competitions.
  • Machine Learning: With the guidance of Mark Schmidt, this group's vision is to advance the frontier of knowledge in Bayesian inference, Monte Carlo algorithms, probabilistic graphical models, neural computation, personalization, mining web-scale datasets, prediction and optimal decision making. 
  • Natural Language Processing: Under the leadership of Giuseppe Carenini and Raymond Ng (Data Management and Mining Lab) this group's vision is to further our understanding of abstactive summarization, mining conversations and evaluative text, natural language generation.
  • Programming Languages for Artificial Intelligence (PLAI): This recently established group under the leadership of Frank Wood develops general-purpose probabilistic methods and programming language technology for machine learning and artificial intelligence, with a focus on interpretable generative models and universal inference for deep unsupervised learning. Current projects span domain applications in particle physics and neuroscience, the theoretical and empirical development of statistical inference methods, and the implementation of probabilistic programming languages. Work at Frank Wood's previous research group in Oxford has led to the probabilistic programming systems Anglican and PyProb.


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