Applied Mathematics MSc student at the Technical University of Munich, focused on quantitative research, statistical learning, time-series modelling, and portfolio risk.
I build research-oriented software at the intersection of dependence modelling, machine learning, optimisation, and financial decision-making. I care about leakage-free evaluation, reproducibility, realistic constraints, and conclusions that match the available evidence.
| Project | What it demonstrates |
|---|---|
| Dynamic portfolio selection with vine copulas | Time-varying D-vines, AR-GARCH marginals, synthetic-data validation, recurrent TD3, CVaR-aware allocation, and controlled out-of-sample evaluation |
| Copula estimation research | Monte Carlo research on marginal uncertainty, copula-family effects, sample size, bias, variance, and estimation error |
| Statistical arbitrage modelling | Statistical arbitrage, cointegration, copula-based signals, volatility targeting, backtesting, and risk analytics |
| AERIS aircraft design | Multidisciplinary scientific computing across sizing, optimisation, aerodynamics, structures, propulsion, and flight performance in a large team project |
- Dependence and tail-risk modelling
- Quantitative portfolio construction and risk management
- Statistical and machine-learning methods for time series
- Robust backtesting, model validation, and reproducible research
- Scientific software for high-dimensional optimisation
Python · R · PyTorch · TensorFlow/Keras · pandas · NumPy · SciPy · Git
You can find my professional background on LinkedIn.