معرفی
Naftali Cohen is an Adjunct Professor at NYU Tandon School of Engineering and Columbia University’s Industrial Engineering and Operations Research Department. He holds a PhD in Applied Mathematics from NYU’s Courant Institute (2013), an MSc and BSc in Atmospheric Science from The Hebrew University of Jerusalem (2008 and 2006). As a Senior Quant in the hedge fund industry, he specializes in systematic, mid-frequency market-neutral equity trading using data-driven approaches.
His research interests bridge quantitative finance and data science, focusing on algorithmic trading strategies, machine learning applications in financial markets, time series forecasting, and risk management. He has held roles at JP Morgan Chase, Yale University, and Columbia University prior to his current positions.
Notable research trends include AI-enhanced factor analysis for equity prediction, momentum strategies, and volatility modeling. His work on adversarial attacks on ML systems for high-frequency trading highlights cybersecurity concerns in algorithmic finance.
He has contributed to climate science research earlier in his career, studying atmospheric dynamics and monsoon patterns. His teaching focuses on graduate-level courses at the intersection of data science and financial engineering.
