Gabor Sarosi, PhD
About Gabor Sarosi, PhD
Gabor Sarosi, PhD, is a Quantitative Analyst at UBS, specializing in Corporates and Sovereign Lending Models. He has a strong academic background in theoretical and mathematical physics, with experience at prestigious institutions including CERN and the University of Pennsylvania.
Work at UBS
Gabor Sarosi currently serves as a Quantitative Analyst in Corporates and Sovereign Lending Models at UBS. He has held this position since 2022, contributing to the development of credit risk models specifically in the Pillar 1 lending space. His role involves applying quantitative analysis to enhance the bank's lending strategies and risk assessment processes. UBS, a global financial services company, benefits from his expertise in applied mathematics and theoretical physics.
Education and Expertise
Gabor Sarosi earned his Doctor of Philosophy (PhD) in Theoretical and Mathematical Physics from Budapest University of Technology and Economics, completing his studies from 2012 to 2016. He possesses a strong foundation in applied mathematics and theoretical physics, which underpins his work in quantitative analysis. His programming skills include proficiency in Python and Mathematica, enabling him to develop sophisticated models for financial applications.
Background in Research and Academia
Gabor Sarosi has an extensive background in research and academia. He worked as a Senior Research Fellow at CERN from 2019 to 2022, focusing on advanced theoretical concepts. Prior to that, he held postdoctoral positions at the University of Pennsylvania and Vrije Universiteit Brussel, where he conducted research in theoretical physics. His experience also includes a role as a Graduate Fellow at the Kavli Institute for Theoretical Physics in 2015.
Specialization in Quantum Physics
Gabor Sarosi has specialized in areas such as quantum gravity, black holes, and quantum information. His research in these fields has contributed to a deeper understanding of complex physical phenomena. This specialization informs his analytical approach in finance, particularly in developing quantitative models that address credit risk.