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astronomy

Jonathan Pillow

Jonathan Pillow is a astronomy 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 Jonathan Pillow rather than just read about it. In short: Jonathan Pillow is an American neuroscientist and professor at the Princeton Neuroscience Institute. His research focuses on the intersection of neuroscience, statistics, and machine learning.

Key takeaways

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

Reference excerpt

Jonathan Pillow is an American neuroscientist and professor at the Princeton Neuroscience Institute. His research focuses on the intersection of neuroscience, statistics, and machine learning.

Early life and education Pillow grew up in Phoenix, Arizona. He attended the University of Arizona as a Flinn Scholar, where he majored in mathematics and philosophy. After a year as a Fulbright U.S. Student Fellow in Morocco studying North African literature, he attended graduate school at New York University's Center for Neural Science. He received a Ph.D. in neuroscience in 2005 for research on statistical models of information processing in the early visual pathway.

Career After his Ph.D., Pillow was a postdoctoral fellow at the Gatsby Computational Neuroscience Unit at University College London. From 2009 to 2014, he was an assistant professor at the University of Texas at Austin in the departments of Psychology, Neuroscience, and Statistics & Data Science. He is currently a professor in the Princeton Neuroscience Institute and the Department of Psychology. Pillow’s lab at Princeton develops statistical methods for understanding how large populations of neurons transmit and process information. His research interests include sensory-motor decision making, working memory, and latent variable models. Since 2016, Pillow has been a member of the International Brain Laboratory.

Awards and honors In 2012, Pillow received the Presidential Early Career Award for Scientists and Engineers, the highest honor bestowed by the U.S. government on science and engineering professionals in the early stages of their independent research careers.

References

Worked examples

Example 1 — a first encounter with Jonathan Pillow

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

In research
Jonathan Pillow appears in astronomy 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 Jonathan Pillow 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
Jonathan Pillow is common in secondary-school and first-year university syllabi. It links to neighbouring topics American neuroscientists, American psychologists, Computational neuroscientists, so understanding it makes those chapters shorter.
In everyday life
Look for Jonathan Pillow 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 Jonathan Pillow in 20 minutes

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

Frequently asked questions

What is Jonathan Pillow in simple terms?

Jonathan Pillow is an American neuroscientist and professor at the Princeton Neuroscience Institute. His research focuses on the intersection of neuroscience, statistics, and machine learning.

Why does Jonathan Pillow matter?

Because it connects several astronomy 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 Jonathan Pillow?

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 Jonathan Pillow.

Tags

  • American neuroscientists
  • American psychologists
  • Computational neuroscientists
  • Living people
  • New York University alumni
  • People from Phoenix, Arizona
  • Princeton University faculty
  • University of Arizona alumni
  • University of Texas at Austin faculty

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