Bio: I am an Associate Professor of Financial Engineering (with tenure) at Stevens Institute of Technology (SIT). I hold a Ph.D. in Finance from Rensselaer Polytechnic Institute (RPI) in 2018, and my research lies at the intersection of asset pricing, statistical learning, and financial risk management. I study the economic value of predictive models, focusing on machine learning complexity and portfolio selection under model risk. My work has appeared in Management Science, the European Journal of Operational Research, and Quantitative Finance. My research has also been featured in news outlets such as Bloomberg and funded by the NSF through CRAFT. 

Before joining SIT, I worked part-time as a data scientist at Financial Network Analytics (FNA) during the summer of 2018. Additionally, I pursued graduate training in Mathematical Finance at the London School of Economics (LSE) for one year before joining RPI for my Ph.D. studies. While in London, I worked part-time as a Quantitative Analyst at Pantheon Ventures. A proponent of open-source software, I actively promote R for statistical computing and reproducible research in both academic and applied settings. Growing up in Galilee, I hold both a BA and an MA in Statistics from the University of Haifa with a specialization in actuarial science. In Aug 2023, I became an FRM-certified professional through GARP.