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Kung-Yee Liang

Kung-Yee Liang 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 Kung-Yee Liang rather than just read about it. In short: Kung-Yee Liang (Chinese: 梁賡義; pinyin: Liáng Gēng yí; born September 7, 1951) is a Taiwanese biostatistician known for his work on generalized estimating equations, which he introduced together with Scott Zeger in 1986. He is a distinguished chair professor at Feng Chia University and the chairman of OBI Pharma, Inc.

Key takeaways

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

Reference excerpt

Kung-Yee Liang (Chinese: 梁賡義; pinyin: Liáng Gēng yí; born September 7, 1951) is a Taiwanese biostatistician known for his work on generalized estimating equations, which he introduced together with Scott Zeger in 1986. He is a distinguished chair professor at Feng Chia University and the chairman of OBI Pharma, Inc. From 1982 to 2010, Liang was a professor at the department of biostatistics at the Johns Hopkins Bloomberg School of Public Health. In 2010, Liang returned to Taiwan, where he was the president of National Yang-Ming University from 2010 to 2017 and the president of the National Health Research Institutes from 2017 to 2022.

Education and career Liang earned a bachelor's degree in mathematics from National Tsing Hua University in 1973 before coming to the U.S., where he received a master's degree in statistics from the University of South Carolina in 1979. In 1982, Liang completed his PhD in biostatistics at the University of Washington under the supervision of Norman Breslow. His dissertation was titled The Asymptotic Equivalence of Conditional and Unconditional Inference Procedures. That same year, he joined the biostatistics department faculty at the Johns Hopkins Bloomberg School of Public Health where he became a full professor in 1991 and stayed until he returned to Taiwan in 2010. Returning to his home country, Liang moved from conducting research towards administrative and leadership roles. In August 2010, Liang became president of National Yang-Ming University, a position he remained in until November 2017. From December 2017 to December 2022, he was the president of the National Health Research Institutes. During his time as a vice president of the organisation (2003–2006), he had already served as the acting president of the organisation between January and June 2006. Since February 2023, Liang has been Distinguished Chair Professor at Feng Chia University. On December 29, 2023, he was elected as chairman of OBI Pharma, Inc.

Awards and recognition Liang has received multiple awards for his work, including the Snedecor Award from the Committee of Presidents of Statistical Societies in 1987, the Rema Lapouse Award from the American Public Health Association in 2010, and the International Statistical Institute's Karl Pearson Prize in 2015. In 2025, he received the Presidential Science Prize of Taiwan, the country's highest honor for scientific research. In 1995, Liang was elected as a Fellow of the American Statistical Association. He was elected as an academician of the Academia Sinica in 2002, as a fellow of The World Academy of Sciences in 2012, and as a member of the National Academy of Medicine in 2015.

References

Worked examples

Example 1 — a first encounter with Kung-Yee Liang

Start with the simplest possible case. Write down what Kung-Yee Liang 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 Kung-Yee Liang 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 Kung-Yee Liang 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 Kung-Yee Liang

In research
Kung-Yee Liang 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 Kung-Yee Liang 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
Kung-Yee Liang is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1951 births, Academic staff of Feng Chia University, Biostatisticians, so understanding it makes those chapters shorter.
In everyday life
Look for Kung-Yee Liang 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 Kung-Yee Liang in 20 minutes

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

Frequently asked questions

What is Kung-Yee Liang in simple terms?

Kung-Yee Liang (Chinese: 梁賡義; pinyin: Liáng Gēng yí; born September 7, 1951) is a Taiwanese biostatistician known for his work on generalized estimating equations, which he introduced together with Scott Zeger in 1986. He is a distinguished chair professor at Feng Chia University and the chairman o…

Why does Kung-Yee Liang 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 Kung-Yee Liang?

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 Kung-Yee Liang.

Tags

  • 1951 births
  • Academic staff of Feng Chia University
  • Biostatisticians
  • Fellows of The World Academy of Sciences
  • Fellows of the American Statistical Association
  • Living people
  • Members of Academia Sinica
  • Members of the National Academy of Medicine
  • National Tsing Hua University alumni
  • Presidential Science Prize recipients
  • Taiwanese statisticians
  • University of South Carolina alumni

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