Talk:Ronen Eldan/Temp

Ronen Eldan (רונן אלדן; born 1980) is an Israeli mathmetician and theoretical physicist. Eldan is a senior researcher at the Weizmann Institute of Science. He is among the recipients of the 2022 Blavatnik Award for Young Scientists.

Early life
Ronen Eldan was born in Israel in 1980 to Rachel and Yoram Eldan. Eldan spent a majority of his childhood growing up in Ramat Aviv.

Education
In 2005, Eldan received his B.A degree in Maths from the Open University of Israel. In 2006, he persued an additional discipline in physics from Tel Aviv University.

In 2013, Eldan received his PhD. from Tel-Aviv University and later worked as a post-doctorate researcher at the University of Washington.

Career
Eldan worked as an applied mathematician, programming team-leader for the IDF, and also as a computer security specialist. In 2011, he worked as an intern at Microsoft research.

In 2015, Eldan joined the Weizmann Institute's Department of Mathematics.

Eldan's research touches on various mathematical fields, mostly those dealing with high dimensional probability. Eldan's main contribution is that of developing a new methodology derived from the connection seen while analyzing stochastic calculus and high-dimensional systems. Research performed by Eldan has led to new algorithms for decision-making in artificial intelligence and the limitations of neural networks in machine learning.

In 2018, Eldan was awarded the Erdos Prize in Mathematics.

In 2022, Eldan was awarded the Blavatnik Award for Young Scientists for his significant contributions made in the mathematical field of high dimensional probability. The techniques developed by Eldan can be applied in various forms.

Works

 * Sébastien Bubeck, Ronen Eldan: “Multi-scale exploration of convex functions and bandit convex optimization”, 2015; arXiv:1507.06580.
 * Sébastien Bubeck, Ronen Eldan, Yin Tat Lee: “Kernel-based methods for bandit convex optimization”, 2016; arXiv:1607.03084.
 * Ronen Eldan, Bo'az Klartag: “Approximately gaussian marginals and the hyperplane conjecture”, 2010; arXiv:1001.0875.
 * Jian Ding, Ronen Eldan, Alex Zhai: “On multiple peaks and moderate deviations for supremum of Gaussian field”, 2013; arXiv:1311.5592.
 * Ronen Eldan: “Gaussian-width gradient complexity, reverse log-Sobolev inequalities and nonlinear large deviations”, 2016; arXiv:1612.04346.
 * Ronen Eldan, Dan Mikulincer, Alex Zhai: “The CLT in high dimensions: quantitative bounds via martingale embedding”, 2018; arXiv:1806.09087.
 * Ronen Eldan: “Taming correlations through entropy-efficient measure decompositions with applications to mean-field approximation”, 2018; arXiv:1811.11530.
 * Ronen Eldan, Renan Gross: “Concentration on the Boolean hypercube via pathwise stochastic analysis”, 2019; arXiv:1909.12067.
 * Sébastien Bubeck, Ronen Eldan, Yin Tat Lee: “Kernel-based methods for bandit convex optimization”, 2016; arXiv:1607.03084.
 * Ronen Eldan, Bo'az Klartag: “Approximately gaussian marginals and the hyperplane conjecture”, 2010; arXiv:1001.0875.
 * Jian Ding, Ronen Eldan, Alex Zhai: “On multiple peaks and moderate deviations for supremum of Gaussian field”, 2013; arXiv:1311.5592.
 * Ronen Eldan: “Gaussian-width gradient complexity, reverse log-Sobolev inequalities and nonlinear large deviations”, 2016; arXiv:1612.04346.
 * Ronen Eldan, Dan Mikulincer, Alex Zhai: “The CLT in high dimensions: quantitative bounds via martingale embedding”, 2018; arXiv:1806.09087.
 * Ronen Eldan: “Taming correlations through entropy-efficient measure decompositions with applications to mean-field approximation”, 2018; arXiv:1811.11530.
 * Ronen Eldan, Renan Gross: “Concentration on the Boolean hypercube via pathwise stochastic analysis”, 2019; arXiv:1909.12067.
 * Ronen Eldan: “Taming correlations through entropy-efficient measure decompositions with applications to mean-field approximation”, 2018; arXiv:1811.11530.
 * Ronen Eldan, Renan Gross: “Concentration on the Boolean hypercube via pathwise stochastic analysis”, 2019; arXiv:1909.12067.
 * Ronen Eldan, Renan Gross: “Concentration on the Boolean hypercube via pathwise stochastic analysis”, 2019; arXiv:1909.12067.

Awards

 * Haim Nessyahu Prize for Mathematics (2013)
 * Erdos Prize in Mathematics (2018)
 * Blavatnik Award for Young Scientists (2022)