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Doron Zeilberger was born on July 2, 1950, in Haifa, Israel. His academic formation took place at the Weizmann Institute of Science, where he received his education. Working in both Hebrew and English, he has pursued a career that spans two countries, holding citizenship in both Israel and the United States.

Zeilberger works as a mathematician and computer scientist, and his contributions to research have been recognized through a series of professional distinctions. Among these, the Steele Prize for Seminal Contribution to Research stands as a significant acknowledgment of his work. He has also received the David P. Robbins Prize and the Euler Medal, honors that reflect the scope of his activity across mathematics and related areas.

Zeilberger has additionally received the Paul R. Halmos – Lester R. Ford Awards, further extending the list of distinctions associated with his career. He has been named a Fellow of the American Mathematical Society, a designation reflecting sustained professional contribution to the discipline. Together, these awards document a record of engagement with mathematics and computer science recognized across multiple professional bodies.

Zeilberger continues to work as a mathematician and computer scientist, maintaining citizenship in both Israel and the United States. His career traces back to his education at the Weizmann Institute of Science in Israel and has extended through decades of work conducted in English and Hebrew alike. His ongoing activity in both fields is anchored by the recognition he has received from the American Mathematical Society and other organizations.

Quotes by Doron Zeilberger

Conventional wisdom, fooled by our misleading “physical intuition”, is that the real world is continuous, and that discrete models are necessary evils for approximating the “real” world, due to the innate discreteness of the digital computer.
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Conventional wisdom, fooled by our misleading “physical intuition”, is that the real world is continuous, and that discrete models are necessary evils for approximating the “real” world, due to the innate discreteness of the digital computer.
When a problem seems intractable, it is often a good idea to try to study “toy” versions of it in the hope that as the toys become increasingly larger and more sophisticated, they would metamorphose, in the limit, to the real thing.
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When a problem seems intractable, it is often a good idea to try to study “toy” versions of it in the hope that as the toys become increasingly larger and more sophisticated, they would metamorphose, in the limit, to the real thing.
No Victor, you got it backwards, you should evaluate these integrals non-rigorously if you can, and rigorously if you must.
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No Victor, you got it backwards, you should evaluate these integrals non-rigorously if you can, and rigorously if you must.
Let me also remind you that zero, like all of mathematics, is fictional and an idealization. It is impossible to reach absolute zero temperature or to get perfect vacuum. Luckily, mathematics is a fairyland where ideal and fictional objects are possible.
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Let me also remind you that zero, like all of mathematics, is fictional and an idealization. It is impossible to reach absolute zero temperature or to get perfect vacuum. Luckily, mathematics is a fairyland where ideal and fictional objects are possible.
The ‘lowly’ finite is MUCH more beautiful than any ‘infinite’
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The ‘lowly’ finite is MUCH more beautiful than any ‘infinite’
Regardless of whether or not God exists, God has no place in mathematics, at least in my book.
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Regardless of whether or not God exists, God has no place in mathematics, at least in my book.
Mathematics my foot! Algorithms are mathematics too, and often more interesting and definitely more useful.
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Mathematics my foot! Algorithms are mathematics too, and often more interesting and definitely more useful.
The real work of us mathematicians, from now until, roughly, fifty years from now, when computers won’t need us anymore, is to make the transition from human-centric math to machine-centric math as smooth and efficient as possible.
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The real work of us mathematicians, from now until, roughly, fifty years from now, when computers won’t need us anymore, is to make the transition from human-centric math to machine-centric math as smooth and efficient as possible.
Programming is much much harder than doing mathematics.
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Programming is much much harder than doing mathematics.