The UBC Department of Computer Science (UBC CS) has a strong research presence, consistently ranking in the top 3 computer science departments in Canada. Our research is conducted by our faculty members, postdoctoral fellows and students across various research areas and research centres.
Algorithmic Game Theory is a research area spanning theoretical computer science, artificial intelligence, and economics, and additionally drawing on disciplines such as operations research, psychology and statistics. It brings a computational lens to bear on the design and analysis of multi-agent…
Artificial Intelligence and Machine Learning encompass the development of intelligent systems that can learn from data, reason, and make decisions. This is a broad group with diverse interests related to developing or using AI/ML systems; narrower groups with substantial areas of overlap include…
We develop and use cutting-edge computational approaches to study biological systems across multiple scales–from molecules to cells, tissues to organs, and microbiomes to human populations. By integrating machine learning, algorithm design, and high-performance computing with rich biomedical data…
The Computer Science Education Group (CSEd) at UBC is a collaborative research and teaching initiative within the University of British Columbia’s Department of Computer Science. Dedicated to advancing the field of computing education, the group explores innovative teaching methods, inclusive…
The research in the DMM group centres on helping users to manage, mine, understand, and explore their data, whether that is data that's in a traditional relational database, an information network, or genomic data.
Our human-computer interaction (HCI) research explores how humans interact with technology and how to design systems that are effective, accessible, and engaging. This interdisciplinary area encompasses personalized and adaptive interfaces, information visualization, novel interaction technologies…
Our research is at the intersection of AI, Human-Computer Interaction (HCI), and Cognitive Science, with the overarching goal to foster effective Human-AI assisted work. We investigate how to design and evaluate AI systems, digital and robotic, capable of performing useful tasks and adhering to…
The Natural Language Processing (NLP) group at University of British Columbia conducts research on core NLP problems, computational linguistics, text mining, and visual text analytics. We focus on the following research areas in particular (but not limited to): discourse and summarization…
We also examine rigorous approaches for ensuring that software behaves as intended. This work combines both formal verification methods as well as dynamic approaches such as fuzzing to identify defects.
One important avenue of work examines improving how developers express their intent and verifying that the programs they write accurately execute in practice. This line of work includes improving compilers, type systems, and approaches for verifying compilation.
Robotics research at UBC investigates how to build autonomous agents which interact effectively with the physical world. Such autonomous agents require a range of capabilities: perceiving the world accurately, taking efficient and successful actions, and interacting safely with people. Consequently…
The Scientific Computing Lab brings together researchers interested in developing fast, reliable, and robust numerical algorithms needed for modelling and simulation in a variety of fields including physics, engineering, life sciences, and data science. Our research areas include: Numerical linear…
We are a diverse group of people working on topics related to systems security, cloud security, network security, privacy, ML, and software engineering.
We are committed to informing our work with a deep understanding of the context in which practicing software developers work. Practising developers must balance a number of different demands, including cost constraints, time limitations, existing code bases and environments, and the context in which…
We work on topics focused on the core methodology and foundations of machine learning, as a subset of the much broader Artificial Intelligence & Machine Learning group. This includes developing improved models that push the boundaries of what machine learning systems can learn to do as well as…
We conduct research on a variety of topics, including operating systems, distributed systems, security, data provenance, program analysis, and much more! Interpretable Machine Learning We use computational caching as well as novel data structures and algorithms to produce provably optimal solutions…
Visualization research at UBC includes the development of scalable algorithms and techniques and deployable systems. We pursue the evaluation and characterization of visualization approaches using qualitative, quantitative, and mixed methods. We have been particularly active in the application areas…