Convex Optimization Techniques

Responsible for student Q&A, assignment feedback, and grading. (Instructor: Changho Suh)

Convex Optimization & Algorithms

Assisted students in understanding convex sets/functions, LP/QP/SOCP/SDP formulations, and core optimization algorithms, providing guidance through problem sets and mathematical derivations.

Duality & KKT Conditions

Supported instruction on Lagrangian duality, primal–dual relationships, strong/weak duality, and KKT conditions, helping students solve analytical exercises and interpret optimality conditions.

Applications in Machine Learning & Finance

Guided students through practical optimization applications including supervised learning, GAN training stability, and portfolio optimization, with emphasis on problem formulation and solution interpretation.