Mathematics

Introduction to Machine Learning

Fundamental Methods of Projection Theory

The Szemeredi-Trotter Theorem

Lecture 03: Projection Theory in Euclidean Space

Applications of the Large Sieve to Number Theory

Random Walks on Finite Groups, Part 1

The Bourgain Projection Theorem, Part 1 (over the Real Numbers)

Lecture 10: Sum-Product Theory

Black-Scholes Formula, Risk Neutral Valuation

Homogeneous Dynamics, Part 2: Quantitative Ratner Theorems and Projection Theory

Contagious Structure in Projection Theory

Introduction to Projection Theory

Lecture 24: Sharp Projection Theorems, Part 3 - Combining Different Scales

Lecture 25: Stochastic Calculus (cont.); Stochastic Differential Equations

Random Walks on Finite Groups, Part 3

Projections and Smoothing

Lecture 13: Portfolio Management

Linear Algebra

Lecture 8: Regression Analysis (cont.)

Lecture 20: Homogeneous Dynamics, Part 1

The Bourgain Projection Theorem, Part 3

Lecture 05: The Large Sieve

Probability Theory (cont.); Stochastic Processes I

Counterparty Risk Optimization