Naftali Cohen

Systematic Trading @ Schonfeld & Faculty @ Columbia

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Short Bio:

I am a senior data scientist and quant at Schonfeld Strategic Advisors, specializing in leveraging data for mid-frequency systematic equity trading. With over 15 years of experience in AI/ML and focused expertise in Quantitative Finance for the past seven years, I also serve as an adjunct professor in the IEOR department at Columbia University, teaching graduate-level courses at the intersection of data science and quantitative finance.

My career has included positions at JP Morgan Chase, New York University, Yale University, and Columbia University, where I developed my skills in leading engineering teams and effectively managing communications between technical and non-technical stakeholders.

I hold a Ph.D. in Applied Mathematics from the Courant Institute of Mathematical Sciences at New York University.

Recent Teaching:

My teaching philosophy is deeply rooted in and driven by a commitment to a data-centric approach. At the heart of this philosophy is the fluid integration of theoretical insights with real-world applications, a blend that is vital in the dynamic realm of scientific work. My courses are meticulously designed to deepen students' understanding of quantitative decision-making strategies, especially those employed under conditions of uncertainty and informed by robust data analysis. As an educator, my aim is to foster an engaging learning environment that not only imparts fundamental knowledge but also ignites a passion for discovery and innovation within this ever-evolving field.

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Recently Organized Academic Meetings:
In my commitment to advancing quantitative finance and operations research, I have had the privilege of organizing and contributing to a series of academic meetings and workshops. These events serve as vibrant platforms for exchanging ideas and fostering collaborative research efforts. They cover a wide range of topics, from the intricacies of AI in finance and the exploration of graph learning in various industrial applications to the nuances of ethical AI development and its implications in the financial sector. Each meeting and workshop is meticulously designed to address the most pressing challenges and emerging trends in our field, bringing together a diverse mix of researchers, practitioners, and thought leaders. These gatherings have been instrumental in disseminating cutting-edge research and shaping the future trajectory of AI and machine learning within the financial and industrial sectors.

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Disclaimer:

The statements on this webpage are my own and do not necessarily reflect the views of the entities and agencies with which I am affiliated. No investment advice or specific course of action is being recommended.