Convex sets in the $d$-dimensional Euclidean space $\mathbb{R}^d$ feature prominently in optimization, statistics, functional analysis and data science. We are interested in understanding how their volume is distributed, how polytopes approximate them, and in their isoperimetric properties. Our toolkit contains combinatorial ideas, probabilistic methods, and anything that you may bring to solve problems in discrete geometry and geometric analysis.
Our group has received funding from NRDI grants 119670, 143778 (PI: Márton Naszódi), 147145 (PI: Gergely Ambrus) and 2024-1.2.8-TÉT-IPARI-CN-2025-00011 (PI: Zsolt Lángi).
Members
Researchers
Students
Akbar Shahkaramov (PhD student), Eötvös University, Budapest
Barnabás Gárgyán, Shanshan Wang (PhD students), University of Szeged
Sándor Fazekas (MSc student), Eötvös University, Budapest
Kristóf Huszta, Dorottya Dancsó, Emese Kőműves, Katalin Olasz (BSc students), University of Szeged
Past students
Almohammad Sami Mezal Araibi (PhD 2023)
Bushra Basit (PhD 2025)