Bio: I am a tenure-track assistant professor at the School of Business 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, with a focus on machine learning complexity and portfolio selection under model risk. My work has been published in various outlets, including Management Science, the European Journal of Operational Research, and Quantitative Finance. Additionally, my research has been featured in news outlets such as Bloomberg and has been funded by the NSF via CRAFT. 

Before joining SIT, I worked as a part-time data scientist for 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 as a part-time Quantitative Analyst for Pantheon Ventures. A proponent of open-source software, I actively promote the use of 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 a certified FRM via GARP.