Research Topics and Domains

Metapages collecting information on general research topics of interest in the lab.

Our research can be grouped by intersections of pure research directions, that lead to application ideas, as well as applied domains which lead to new fundamental directions for research. Dive into any of the topics below to find out more.

Another way to explore this is to look at all the lab’s Publications Grouped by Research Topics or at individual Research Projects.

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Machine Ethics (or Ethical AI)

Can machines perform ethical reasoning?
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Vision Language Navigation

Building AI systems that can navigate when given open ended image and natural language isntructions.
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Sustainable Forest Management

All research related to assessment, modelling, prediction and planning for the sustainable management of forest ecosystems and resources.
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Reinforcement Learning

RL is the study of learning decision making policies from experience with computers.
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Machine Learning (ML)

ML is the study of how to build computer programs that can learn to detect patterns from data.
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Artificial Intelligence (AI)

AI is the study of how to build computer programs that can learn to detect patterns from data.
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Causality

Using AI/ML to do moar Sciencing!
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AI for Science

Using AI/ML to do moar Sciencing!
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Multi-Agent Reinforcement Learning

MARL is the problem of learning how to make decisions from experience in the presence of multiple other decision making agents.
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Autonomous Driving

Using computing to make driving safer.
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Manifold Learning

Manifold learning looks at ways to automatically extract meaningful features, dimensions or subspaces from data in order to build better models, expand data, reduce data, etc.

Game Theory

Game theory is the mathematical study of competitive, or co-operative optimal decision making by multiple agents.