Curriculum Vitae


I've finished my undergrad studies at BUTE as a Computer engineer specialized in Business information systems, followed by a master's degree with highest honors in Business informatics specialized in Analytical business intelligence. I've been fascinated by the world of data analysis since the final year of my BSc studies, my favourite fields being statistics, data mining, financial modelling, decision support based on stochastic simulations, operations research and risk analysis. Currently I'm a PhD student at the Department of Computer Science and Information Theory.


PhD programme
Department of Computer Science and Information Theory
Budapest University of Technology and Economics
2015 -

Business Informatics, MSc
Specialization in Analytical business intelligence (in english)
Budapest University of Technology and Economics
2013 - 2015

Computer engineer, BSc
Specialized in Business information systems
Budapest University of Technology and Economics
2009 - 2013


Wigner Research Centre for Physics, Hungarian Academy of Sciences
Junior research fellow
I'm working in the development of causal time series analysis algorithms.
2017 -

Ericsson Hungary Research and Development Center
Intern, Data specialist
I worked on Ericsson Expert Analytics, Ericsson's Big Data solution.
2015 - 2017

Morgan Stanley
Project lab thesis, 2 semesters
I worked on a statistical predictor tool for correcting bond pricing errors.
2013 - 2014

HP Hungary
Intern, HP Autonomy Consultant
I worked with HP's Big Data solution, HP Autonomy, to build an analytical framework for the mobile telecommunication sector, and an IT security tool.
2012 - 2013


  • Data analytics

    • Data pre-processing
    • Descriptive analysis
    • Cluster analysis
    • Supervised learning
    • Model evaluation

  • Financial engineering

    • Risk analysis & modelling
    • Time series analysis
    • Portfolio optimization
    • Derivative pricing

  • Stochastics

    • Monte Carlo models
    • Queueing models
    • Stochastic calculus

  • Data visualization

  • Mathematical statistics

    • Hypothesis testing
    • Regression analysis
    • Dimension reduction
    • Robust statistics

  • Operations research

  • Mathematical optimization

    • General convex optimization
    • Duality, KKT
    • LP, QP, SOCP, SDP, GP
    • Unconstrained and constrained solvers (Gradient descent, Steepest descent, Newton descent, Interior point methods)
    • Metaheuristic methods (Simulated annealing, genetic algorithms, particle-swarm, etc.)

  • Tools

    • SPSS Statistics, SPSS Modeler
    • RapidMiner, SAS
    • Advanced Excel, @Risk, Crystal Ball
    • GAMS, AMPL

  • Big Data technologies

    • Hadoop File System
    • Spark
    • Drill
    • Zookeeper

  • Programming

    • Python, R, Lua, MatLab, VBA
    • C/C++, Java, C#
    • Parallel computing (OpenMP, CUDA)
    • Databases (SQL)

  • Basics in

    • Corporate finance
    • Accounting
    • Controlling

Supervised theses

  • Applications of data mining in empirical finance (Master's thesis)
  • Analysis of optimal portfolios (Master's thesis)
  • Analyzing and optimizing the portfolio of a small business via stochastic programming (Master's thesis)
  • Non-parametric sports betting (Bachelor's thesis)