mathematics

Noriko H. Arai

Noriko H. Arai 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 Noriko H. Arai rather than just read about it. In short: Noriko H. Arai (Japanese: 新井紀子, romanized: Arai Noriko, born 1962) is a Japanese researcher in mathematical logic and artificial intelligence, known for her work on a project to develop robots that can pass the entrance examinations for the University of Tokyo.

Key takeaways

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

Reference excerpt

Noriko H. Arai (Japanese: 新井紀子, romanized: Arai Noriko, born 1962) is a Japanese researcher in mathematical logic and artificial intelligence, known for her work on a project to develop robots that can pass the entrance examinations for the University of Tokyo. She is a professor in the information and society research division of the National Institute of Informatics.

Early life and education Professor Noriko H. Arai was born in Tokyo. During her time at Tokyo Metropolitan Kunitachi High School, her strongest subject in high school was Japanese language arts which led her to pursue a liberal arts degree for her undergraduate studies at Hitotsubashi University. She received a bachelor’s degree from the Faculty of Law; this type of degree is different from a J.D. and instead emphasizes sending human resources into society. At Hitotsubashi University, math was a required subject which led to Arai’s interest in understanding the process behind the math itself. With this renewed desire, she took the SAT and TOEFL exams to study abroad at the University of Illinois in the Department of Mathematics. She graduated magna cum laude from the Department of Mathematics at the University of Illinois in her first year in 1985. Arai then received a scholarship to enter the five-year doctoral program in mathematics at the University of Illinois Graduate School, but she instead completed her master's degree in 1990. While at the University of Illinois, she married mathematician Toshiyasu Arai. She returned to Tokyo in 1990. At the time, she was 7 months pregnant. With the University’s support she was able to still finish her degree. After giving birth to her first daughter, she completed her Bachelor of Law from Hitotsubashi University in March of 1995. She became an assistant professor in the Faculty of Information Science at Hiroshima University, where her husband worked. Afterwards, she received her Doctor in Science from the Tokyo Institute of Technology in March of 1997. Her dissertation was: "On Lengths of Proofs in Propositional Calculi." She joined the National Institute of Informatics as a professor in 2001.

Contributions Arai's recent research has focussed on the intersection between Artificial Intelligence and education. Alongside several co-authors, Arai contributed as the last author to a 2018 paper called "Can an A.I. win a medal in the mathematical olympiad? – Benchmarking mechanized mathematics on pre-university problems" published in AI Communications, in which her team created a "problem library [...] designed to support the integration of the technologies of mechanized mathematics and natural language processing towards the goal of end-to-end automatic mathematical problem solving". This paper acts as an extension to Matsuzaki et al. (2017), "Semantic parsing of pre-university math problems" for which Arai and her team developed an "end-to-end math problem solving system that accepts natural language input." Beyond mathematical education, Arai has also contributed to research on reading and language skills, developing a Reading Skill Tests to compare AI and human reading comprehension skills. The Reading Skill Test was developed in collaboration with the Japanese Ministry of Education, Culture, Sports, Science, and Technology, and the test was administered to over 40,000 students. Her early publications examine mathematical proof systems, particularly within the fields of calculus and combinatorics. In 2011, the National Institute of Informatics launched "The Todai Robot Project (Can a robot get into the University of Tokyo?", an Artificial Intelligence initiative aimed at creating a robot capable of answering real questions from the University of Tokyo entrance examinations. Arai became director of the project in 2011. The examination includes eight subject tests, including two social studies, two sciences, Japanese and Chinese classics, English, and two mathematics. Over 500 thousand high school graduates participate in standardized admissions exams each year in Japan, yet fewer than fifteen thousand students are permitted to advance to the selective University of Tokyo test. In 2015, Arai published her paper: "The impact of AI: can a robot get into the University of Tokyo?", which announced her team's Todai Robot achieved a score above the median human test taker, yet below the average score of those admitted to the University of Tokyo. Still, the robot was "competent enough to pass the entrance exams of 472 out of 581 private universities in Japan". The Todai robot received international attention, and was the subject of Professor Arai's 2017 TEDTalk. Arai sees the success of the project as evidence that human education should concentrate more on problem solving and creativity, and less on rote learning. Arai won multiple awards for her work related to the Todai Robot Project, including the Association for Natural Language Processing's 30th Anniversary Paper Award in 2024. Arai is also an award-winning author. Her book, AI vs. Children Who Can't Read Textbooks, grapples with the problems with the education system in Japan and discusses the future of AI. The book won the Okawa Publishing Award in 2018, a TOPPOINT Award for the First Half of 2018, the 66th Japan Essayist Club Award, the 2019 Business Book Award, and others. Arai is the founder of Researchmap, "the largest social network for researchers in Japan". She was one of 15 top artificial intelligence researchers invited by French president Emmanuel Macron to join him in March 2018 for the announcement of a major new French initiative for artificial intelligence research.

Selected publications Noriko Arai's Reading Comprehension Training, published by Toyo Keizai, 2025. Shin Reading Comprehension, published by Toyo Keizai, 2025. Detour Pan! Introduction to Mathematics for Survival (New and Expanded Edition), published by Shinyosha, 2021. Raising children who can compete with AI, published by Toyo Keizai, 2018. AI vs. Children Who Can't Read Textbooks, published by Toyo Keizai, 2018. Detour Pan! Can a Cellobot get into Tokyo University? Published by East Press, 2014.

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Worked examples

Example 1 — a first encounter with Noriko H. Arai

Start with the simplest possible case. Write down what Noriko H. Arai 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 Noriko H. Arai 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 Noriko H. Arai 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 Noriko H. Arai

In research: Noriko H. Arai 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 Noriko H. Arai 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: Noriko H. Arai is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1962 births, Artificial intelligence researchers, Hitotsubashi University alumni, so understanding it makes those chapters shorter.
In everyday life: Look for Noriko H. Arai 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 Noriko H. Arai in 20 minutes

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

Frequently asked questions

What is Noriko H. Arai in simple terms?

Why does Noriko H. Arai 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 Noriko H. Arai?

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 Noriko H. Arai.