computer science

Russell Greiner

Russell Greiner is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Russell Greiner rather than just read about it. In short: Russell Greiner is a Canadian computer scientist and professor of computing science at the University of Alberta. He is also an adjunct professor in psychiatry at the University of Alberta, a fellow of the Association for the Advancement of Artificial Intelligence, and a Canada CIFAR AI Chair.

Key takeaways

Russell Greiner belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Russell Greiner to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Russell Greiner from memory before moving on to harder problems.

Reference excerpt

Russell Greiner is a Canadian computer scientist and professor of computing science at the University of Alberta. He is also an adjunct professor in psychiatry at the University of Alberta, a fellow of the Association for the Advancement of Artificial Intelligence, and a Canada CIFAR AI Chair. After earning a PhD from Stanford University, Greiner worked in both academic and industrial research before joining the University of Alberta, where he became professor of computing science and adjunct professor in psychiatry. He was also a founding scientific director of the Alberta Machine Intelligence Institute. Greiner served as program chair of the International Conference on Machine Learning in 2004 and conference chair in 2006. He was elected a fellow of the AAAI in 2007. He received a McCalla Professorship and a Killam Annual Professorship at the University of Alberta. In 2021, he received the CAIAC Lifetime Achievement Award and was named a Canada CIFAR AI Chair. In 2022, he received the University of Alberta Precision Health Innovator Award. In 2023, he received the CS-Can / Info-Can Lifetime Achievement Award. In 2024, Greiner shared the Brockhouse Prize with David Wishart for work on machine learning for metabolomics. For his mentoring, Greiner received the University of Alberta Great Supervisor Award in 2020 and the Killam Award for Excellence in Mentoring in 2023. His research has focused on machine learning, bioinformatics, medical informatics, survival prediction, and the formal foundations of learnability.

References

External links Russ Greiner at the University of Alberta

Illustrations

Worked examples

Example 1 — a first encounter with Russell Greiner

Start with the simplest possible case. Write down what Russell Greiner claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Russell Greiner before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Russell Greiner ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Russell Greiner

In research: Russell Greiner appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Russell Greiner in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Russell Greiner is common in secondary-school and first-year university syllabi. It links to neighbouring topics Academic staff of the University of Alberta, Canadian computer scientists, Computer scientist stubs, so understanding it makes those chapters shorter.
In everyday life: Look for Russell Greiner outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Russell Greiner in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Russell Greiner means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Russell Greiner out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Russell Greiner in simple terms?

Why does Russell Greiner matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Russell Greiner?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Russell Greiner.