Age, Biography and Wiki
Gábor J. Székely was born on 4 February, 1947 in Budapest, Hungary. Discover Gábor J. Székely's Biography, Age, Height, Physical Stats, Dating/Affairs, Family and career updates. Learn How rich is He in this year and how He spends money? Also learn how He earned most of networth at the age of 76 years old?
Popular As |
N/A |
Occupation |
N/A |
Age |
77 years old |
Zodiac Sign |
Aquarius |
Born |
4 February 1947 |
Birthday |
4 February |
Birthplace |
Budapest, Hungary |
Nationality |
Hungary |
We recommend you to check the complete list of Famous People born on 4 February.
He is a member of famous with the age 77 years old group.
Gábor J. Székely Height, Weight & Measurements
At 77 years old, Gábor J. Székely height not available right now. We will update Gábor J. Székely's Height, weight, Body Measurements, Eye Color, Hair Color, Shoe & Dress size soon as possible.
Physical Status |
Height |
Not Available |
Weight |
Not Available |
Body Measurements |
Not Available |
Eye Color |
Not Available |
Hair Color |
Not Available |
Dating & Relationship status
He is currently single. He is not dating anyone. We don't have much information about He's past relationship and any previous engaged. According to our Database, He has no children.
Family |
Parents |
Not Available |
Wife |
Not Available |
Sibling |
Not Available |
Children |
Not Available |
Gábor J. Székely Net Worth
His net worth has been growing significantly in 2022-2023. So, how much is Gábor J. Székely worth at the age of 77 years old? Gábor J. Székely’s income source is mostly from being a successful . He is from Hungary. We have estimated
Gábor J. Székely's net worth
, money, salary, income, and assets.
Net Worth in 2023 |
$1 Million - $5 Million |
Salary in 2023 |
Under Review |
Net Worth in 2022 |
Pending |
Salary in 2022 |
Under Review |
House |
Not Available |
Cars |
Not Available |
Source of Income |
|
Gábor J. Székely Social Network
Instagram |
|
Linkedin |
|
Twitter |
|
Facebook |
|
Wikipedia |
|
Imdb |
|
Timeline
Since 2006 he is a Program Director of Statistics of the National Science Foundation. Székely is also Research Fellow of the Rényi Institute of Mathematics of the Hungarian Academy of Sciences and the author of two monographs, Paradoxes of Probability Theory and Mathematical Statistics, and Algebraic Probability Theory (with Imre Z. Ruzsa).
In 1989 Székely was visiting professor at Yale University, and in 1990-91 he was the first Lukacs Distinguished Professor in Ohio. Since 1995 he has been teaching at the Bowling Green State University at the Department of Mathematics and Statistics. Székely was academic advisor of Morgan Stanley, NY, and Bunge, Chicago, helped to establish the Morgan Stanley Mathematical Modeling Centre in Budapest (2005) and the Bunge Mathematical Institute (BMI) in Warsaw (2006) to provide quantitative analysis to support the firms' global business.
Between 1985 and 1995 Székely was the first program manager of the Budapest Semesters in Mathematics. Between 1990 and 1997 he was the founding chair of the Department of Stochastics of the Budapest Institute of Technology (Technical University of Budapest) and editor-in-chief of Matematikai Lapok, the official journal of the János Bolyai Mathematical Society.
Székely attended the Eötvös Loránd University, Hungary graduating in 1970. His first advisor was Alfréd Rényi. Székely received his Ph.D. in 1971 from Eötvös Loránd University, the Candidate Degree in 1976 under the direction of Paul Erdős and Andrey Kolmogorov, and the Doctor of Science degree from the Hungarian Academy of Sciences in 1986. During the years 1970-1995 he has worked as a Professor in Eötvös Loránd University at the Department of Probability Theory and Statistics.
Gábor J. Székely (Hungarian pronunciation: [ˈseːkɛj]; born February 4, 1947 in Budapest) is a Hungarian-American statistician/mathematician best known for introducing energy statistics (E-statistics). Examples include: the distance correlation, which is a bona fide dependence measure, equals zero exactly when the variables are independent; the distance skewness, which equals zero exactly when the probability distribution is diagonally symmetric; the E-statistic for normality test; and the E-statistic for clustering.