معرفی
Monty Essid is a Lecturer since 2018 and a quantitative trader specializing in fully systematic strategies for options. He holds a Ph.D. in Mathematics from the Courant Institute of Mathematical Sciences (May 2018) and dual M.S. degrees in Applied Mathematics and Physics from Columbia University and Diplôme d'Ingénieur from École Centrale Paris, France (2013).
- Education
- Ph.D. in Mathematics, Courant Institute of Mathematical Sciences (2018)
- M.S. in Applied Mathematics and Physics, Columbia University (2013)
- M.S. (Diplôme d'Ingénieur), École Centrale Paris (2013)
His research focuses on optimal mass transportation and its intersections with partial differential equations, probability theory, optimization, and applications in data science and financial mathematics. Recent work includes adaptive optimal transport, minimax algorithms, and graph-based regularization techniques.
Monty collaborates with prominent researchers such as Esteban G. Tabak, Giulio Trigila, Justin Solomon, and Michele Pavon. His publications emphasize theoretical foundations and computational methods across mathematical physics and machine learning domains.
