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Po-Ling Loh

Po-Ling Loh is a mathematics 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 Po-Ling Loh rather than just read about it. In short: Po-Ling Loh (born 1987) is an American statistician who works in England as a professor in the Statistical Laboratory of the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge, a Fellow of St. John's College, Cambridge, and College Lecturer in Mathematical Sciences.

Key takeaways

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

Reference excerpt

Po-Ling Loh (born 1987) is an American statistician who works in England as a professor in the Statistical Laboratory of the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge, a Fellow of St. John's College, Cambridge, and College Lecturer in Mathematical Sciences. Her research involves the theory of high-dimensional statistics including M-estimators, robust statistics, differential privacy, and the applications of non-convex optimisation in high-dimensional statistics.

Education and career Loh was born near New York City, where her father (a professor at the University of Wisconsin–Madison) was on sabbatical; she grew up near the university in Madison, Wisconsin. As a student at James Madison Memorial High School, she became a 2005 finalist in the Intel Science Talent Search. Her project, in the mathematics of group theory, was titled Closure properties of D 2 p {\displaystyle D_{2p}} in finite groups, and described research that she performed at the California Institute of Technology (CalTech) under the direction of Michael Aschbacher. She continued at CalTech as an undergraduate, majoring in mathematics with a minor in English. She graduated in 2009, and became a graduate student at the University of California, Berkeley. There, she received a master's degree in computer science in 2013, and completed her Ph.D. in statistics in 2014. Her dissertation, High-dimensional statistics with systematically corrupted data, was supervised by Martin Wainwright. She became an assistant professor of statistics in the Wharton School of the University of Pennsylvania from 2014 to 2016, and moved to the University of Wisconsin–Madison as an assistant professor of electrical and computer engineering in 2016. She changed departments, moving to the Department of Statistics, in 2018, and was promoted to associate professor in 2019. In 2021 she joined the University of Cambridge as a lecturer, and in 2022 was promoted to professor. She has been a Fellow of St. John's College since 2023.

Recognition For her performance in the 2005 Intel Science Talent Search, minor planet 21432 Polingloh was named for Loh. Loh received a National Science Foundation CAREER Award in 2018, the Army Research Office Young Investigator Award in 2019, and a Philip Leverhulme Prize in 2023. She received both the Tweedie New Researcher Award of the Institute of Mathematical Statistics, "novel contributions in non-convex optimization, robust statistics, and statistical modeling and inference of random graphs and networks", and the New Researcher Award of the Bernoulli Society in 2019. She is the 2025 recipient of the Ethel Newbold Prize of the Bernoulli Society. In 2025, Loh was named a Fellow of the Institute of Mathematical Statistics, "for fundamental contributions to high-dimensional statistics and machine learning, in particular, the study of non-convex penalized estimators, robust statistics, network inference and differential privacy, and for substantial contributions to the profession through work with statistical societies and editorial service".

Family Loh is the daughter of Wei-Yin Loh, a Singaporean statistician at the University of Wisconsin. Her brothers are Po-Shen Loh, a mathematician at Carnegie Mellon University and coach of the US International Mathematical Olympiad team, and Po-Ru Loh, an associate professor of medicine at Harvard University. Her uncle, Wei-Liem Loh, is a statistician at the National University of Singapore.

References

External links Home page Po-Ling Loh publications indexed by Google Scholar

Worked examples

Example 1 — a first encounter with Po-Ling Loh

Start with the simplest possible case. Write down what Po-Ling Loh claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, 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 Po-Ling Loh 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 Po-Ling Loh 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 Po-Ling Loh

In research
Po-Ling Loh appears in mathematics 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 Po-Ling Loh 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
Po-Ling Loh is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1987 births, 21st-century American statisticians, 21st-century mathematicians, so understanding it makes those chapters shorter.
In everyday life
Look for Po-Ling Loh 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 Po-Ling Loh in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Po-Ling Loh 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 Po-Ling Loh out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Po-Ling Loh in simple terms?

Po-Ling Loh (born 1987) is an American statistician who works in England as a professor in the Statistical Laboratory of the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge, a Fellow of St. John's College, Cambridge, and College Lecturer in Mathematical Sci…

Why does Po-Ling Loh matter?

Because it connects several mathematics 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 Po-Ling Loh?

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 Po-Ling Loh.

Tags

  • 1987 births
  • 21st-century American statisticians
  • 21st-century mathematicians
  • American people of Singaporean descent
  • American women statisticians
  • California Institute of Technology alumni
  • Cambridge mathematicians
  • Fellows of St John's College, Cambridge
  • Fellows of the Institute of Mathematical Statistics
  • Living people
  • Professors of the University of Cambridge
  • University of California, Berkeley alumni

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