A research path from mathematics to markets.

I am an applied mathematician, quantitative researcher, and academic lecturer working across probability, statistics, algorithms, data science, and systematic trading.

I currently teach in the Software Engineering Department at Shenkar and in Computer Science at SCE (Sami Shamoon College of Engineering). My academic work combines mathematical modeling with empirical problems, ranging from probabilistic forecasting and Markov models to approximation algorithms and social-network analysis.

I earned a Ph.D. in Applied Mathematics from Ariel University. My doctoral research focused on probabilistic and statistical analysis of menstrual-cycle patterns, including forecasting questions arising from Jewish religious law. I later conducted postdoctoral research at Ben-Gurion University on approximation algorithms for communication-system optimization problems.

Alongside academic research and teaching, I have spent years studying financial markets and developing a more systematic quantitative research process. I am especially interested in validation, multiple testing, overfitting, regime dependence, execution effects, and the gap between an attractive backtest and a strategy that is genuinely robust.

Across both academic and market research, I prefer explicit assumptions, falsifiable claims, reproducible analysis, and methods that remain useful outside the notebook.