engineering

Sylvia Plevritis

Sylvia Plevritis is a engineering 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 Sylvia Plevritis rather than just read about it. In short: Sylvia Katina Plevritis is Professor and Chair of the Department of Biomedical Data Science at Stanford University. Education Plevritis received a Bachelor's in Electrical Engineering from The Cooper Union in 1985, an M.S. in Electrical Engineering from Stanford in 1986, a PhD in Electrical Engineering from Stanford University in 1992, and an M.S. in Health Services Research in 1996.

Key takeaways

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

Reference excerpt

Sylvia Katina Plevritis is Professor and Chair of the Department of Biomedical Data Science at Stanford University.

Education Plevritis received a Bachelor's in Electrical Engineering from The Cooper Union in 1985, an M.S. in Electrical Engineering from Stanford in 1986, a PhD in Electrical Engineering from Stanford University in 1992, and an M.S. in Health Services Research in 1996. She was a NSF fellow for her pre-doctoral work and her dissertation was titled: "Resolution improvements for magnetic resonance spectroscopic images." After her post-doctoral research, she joined Stanford's Department of Radiology as an assistant professor. In 2013, she became a full professor in the department of Radiology and (by courtesy) Management, Science, and Engineering (MS&E). In 2019, she was appointed as professor and chair of Biomedical Data Science at Stanford University.

Research and career Plevritis's primary research interests lie in population cancer screening outcomes and developing computational techniques to solve problems within the field of cancer systems biology. In 2006, she was the first to demonstrate the cost-effectiveness of adding Magnetic Resonance Imaging MRI to mammography for screening BRCA1/2 mutation carriers. In 2000, Plevritis led the National Cancer Institute (NCI) Cancer Intervention and Surveillance Network (CISNET) to understand the effects of screening and adjuvant therapy on breast cancer trends by molecular subtype CISNET is a consortium of NCI-sponsored investigators who use simulation modeling to improve our understanding of cancer control interventions for prevention, screening, and treatment. CISNET is one of 13 research concepts proposed to the Board of Scientific Advisors of the NCI in 2020. In 2004, Plevritis became the Director of the Stanford Center for Cancer Systems Biology (CCSB) and the Director of the Cancer Systems Biology Scholars (CSBS), and the co-Section Chief of the Integrative Biomedical Imaging Informatics at Stanford (IBIIS). Her lab also focuses on developing computational tools to identify heterogeneous molecular features with the tumor microenvironment, such as SPADE, DRUGNEM, PhenoSTAMP, and REMI. She was a speaker for the AI and Cancer Research Symposium at Stanford University in 2025. More information can be found at Dr. Plevritis' website at Stanford University.

Awards and honors Plevritis received the Distinguished Investigator for the Academy of Radiology Research and Inaugural Award for Basic Scientist of the Year in the Stanford Radiology Department. She is a fellow of the American Institute for Medical and Biological Engineering (AIMBE) and the International Society for Computational Biology (ISCB).

References

Worked examples

Example 1 — a first encounter with Sylvia Plevritis

Start with the simplest possible case. Write down what Sylvia Plevritis claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In engineering, 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 Sylvia Plevritis 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 Sylvia Plevritis 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 Sylvia Plevritis

In research: Sylvia Plevritis appears in engineering 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 Sylvia Plevritis 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: Sylvia Plevritis is common in secondary-school and first-year university syllabi. It links to neighbouring topics 21st-century American engineers, 21st-century American women engineers, American bioinformaticians, so understanding it makes those chapters shorter.
In everyday life: Look for Sylvia Plevritis 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 Sylvia Plevritis in 20 minutes

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

Frequently asked questions

What is Sylvia Plevritis in simple terms?

Sylvia Katina Plevritis is Professor and Chair of the Department of Biomedical Data Science at Stanford University. Education Plevritis received a Bachelor's in Electrical Engineering from The Cooper Union in 1985, an M.S. in Electrical Engineering from Stanford in 1986, a PhD in Electrical Enginee…

Why does Sylvia Plevritis matter?

Because it connects several engineering 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 Sylvia Plevritis?

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 Sylvia Plevritis.