About
I am a finance professional with a strong foundation in quantitative research and risk management. Currently,
I am embarking on an exciting new chapter as a founding member with a stealth crypto quant startup, leveraging
my passion for digital finance and innovation in the rapidly evolving cryptocurrency domain.
Prior, I contributed my expertise as a quantitative analyst and developer at GSR,
where I supported several projects in the Risk, Analytics, and Alpha teams. I used my coding skills in Python and
C++ and delved deeper into trading strategies and quantitative modeling.
Before joining GSR, I specialized in counterparty risk management at Citi. At Citi, I joined and later
led a team focusing on the development of a greenfield Python library for counterparty risk modeling. Before Citi,
I successfully led 16 employees at a Hungarian manufacturing company in 2019, bridging a gap in management transition.
My career began at Allianz Private Health Insurance in Munich, Germany during my master's degree, where I contributed
to new pricing analytics strategies during the unisex tariff development.
I am a PhD graduate from the Courant Institute, where I studied under the
guidance of Charles Newman, Daniel Stein, and Yuri Bakhtin. My academic background in probability theory,
statistics, mathematical physics, and neuroscience is integral to my career.
Research/Theses
Exit time asymptotics for dynamical systems with fast random switching near an unstable equilibrium, with Yuri Bakhtin, Stochastics and Dynamics 20(1) (2020)
Long-range orientational order of a random near lattice hard sphere and hard disk process, first version, Journal of Applied Probability 57(2) (2020)
Decision Making and Learning in Artificial Physical Systems, Doctoral dissertation (2019)
Prospective Coding by Spiking Neurons, with Brea J., Urbanczik R., Senn W., PLoS Comput. Biol. 12(6) (2016)
Long-range order in a hard disk model in statistical mechanics, Electron. Commun. Probab. Volume 19 (2014)
Spontaneous breaking of rotational symmetry in a probabilistic hard disk model in Statistical Mechanics, Master thesis (2013)
Große Abweichungen für empirische Verteilungen, Bachelor thesis (2011)
Past Teaching
Mathematical Statistics, Spring 2019
Recitations take place Fridays 2pm to 3:15pm in WWH 201 for Thomas Leblé's class and 3:30pm to 4:45pm in WWH 312 for Yisong Yang's class. Please note that the two recitations are not completely interchangeable.
Office hours are Tuesdays 2pm to 3pm in WWH 805 and Fridays 5:15pm to 6:15pm in WWH 524.
For a concise review of probability see Review of Probability Theory by Arian Maleki and Tom Do. For general purposes, Hogg and McKean's Introduction to Mathematical Statistics is a book that I can recommend.
Optional coding homework:
- A .cvs file with a list of 4000 zeros and ones was created using the Python 3 code. Here is a short description.
- Two .csv files (file1, file2) with a list of 50 data points (x_i, y_i) are provided. The data are generated from the same model in both cases with different parameters though. Find the suitable model and fit your parameters to the data.
Probability seminar (undergrad/master), Fall 2018
Dates and location: Mon. 6pm to 7:30pm (09/17 through 12/10) in WWH 805.
Theory of Probability, Summer 2018
Analysis, Spring 2017
Homework problems are from
Foundations of Mathematical Analysis by Richard Johnsonbaugh, and W. E. Pfaffenberger.
Changes in the pdf's are shown in red.
Mathematical Statistics, Spring 2017
Stochastic Calculus, Summer 2016
