computer science

Marina Gavrilova

Marina Gavrilova 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 Marina Gavrilova rather than just read about it. In short: Marina Lvovna Gavrilova (born 1971) is a Russian-Canadian computer scientist whose research interests include machine learning, data fusion, and biometrics, including the use of behavioral characteristics to unmask anonymous social network contributors. She has also published well-cited research on the use of Voronoi diagrams in path planning.

Key takeaways

Marina Gavrilova 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 Marina Gavrilova to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Marina Gavrilova from memory before moving on to harder problems.

Reference excerpt

Marina Lvovna Gavrilova (born 1971) is a Russian-Canadian computer scientist whose research interests include machine learning, data fusion, and biometrics, including the use of behavioral characteristics to unmask anonymous social network contributors. She has also published well-cited research on the use of Voronoi diagrams in path planning. She is a professor of computer science at the University of Calgary in Canada, where she holds a UCalgary Research Excellence Chair. She is also the editor-in-chief of Transactions on Computational Sciences.

Education and career Gavrilova earned a master's degree in computer science in 1993 from Lomonosov State University in Moscow. She completed her Ph.D. at the University of Calgary in 1999. Her doctoral dissertation, Proximity and Applications in General Metrics, was supervised by Jon Rokne. She is editor-in-chief of Transactions on Computational Science, an academic journal whose volumes are published as a series of edited volumes in the Lecture Notes in Computer Science book series.

Recognition In 2021 the University of Calgary named Gavrilova as a recipient of the Order of the University of Calgary. In 2022 the university named her as a Killam Annual Professor, and in 2023 she was one of 22 professors to be awarded an inaugural UCalgary Research Excellence Chair.

References

External links Home page Marina Gavrilova publications indexed by Google Scholar

Worked examples

Example 1 — a first encounter with Marina Gavrilova

Start with the simplest possible case. Write down what Marina Gavrilova 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 Marina Gavrilova 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 Marina Gavrilova 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 Marina Gavrilova

In research: Marina Gavrilova 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 Marina Gavrilova 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: Marina Gavrilova is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1971 births, Academic staff of the University of Calgary, Canadian computer scientists, so understanding it makes those chapters shorter.
In everyday life: Look for Marina Gavrilova 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 Marina Gavrilova in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Marina Gavrilova 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 Marina Gavrilova out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Marina Gavrilova in simple terms?

Why does Marina Gavrilova 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 Marina Gavrilova?

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 Marina Gavrilova.