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Shaurya Shriyam

 
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Taught

Industrial Engineering Lab II (Fall UG, 2020). We conducted coding exercises primarily in Python on inventory control, economic order quantity (EOQ) model, dynamic lot sizing, Wagner-Whitin algorithm, materials requirement planning, task assignment, facility location, integer linear programming, discrete-event simulation, queueing simulation, and greedy algorithm for multi-arm bandits.

Operations Research (Fall PG, 2020). Part of the course was taken by me. Lectures covered nonlinear optimization, method of Lagrange multipliers, calculus of variations, bracketing method of optimization, Fibonacci search method, graph-theoretical optimization problems such as Shannon’s confusion graph and Turan’s multipartite graph.

Manufacturing System Design (Spring UG, 2021). This course gave an introduction to the operations research perspective on the manufacturing industry. Major focus was on how to handle uncertainty in manufacturing and industrial systems. Lectures covered modeling inventory systems, modeling multi-agent decision-making scenarios under uncertainty, Nash equilibrium, sequential games, extensive games, modeling queueing systems, and a brief introduction towards the end on bandit modeling and causal inference.

Advanced Operations Research (Spring PG, 2021). Part of the course was taken by me to introduce Bayesian machine learning concepts. Lectures covered maximum likelihood estimation (MLE) technique, latent-variable models, expectation-maximization (EM) algorithm, inference for Gaussian mixture models.

Industrial Engineering Lab II (Fall UG, 2021). We conducted coding exercises primarily in Python on inventory control, economic order quantity (EOQ) model, dynamic lot sizing, Wagner-Whitin algorithm, materials requirement planning, task assignment, integer linear programming, linear regression, and game theoretic solution methods for simultaneous and sequential games.

Operations Research (Fall PG, 2021). Lectures covered simplex algorithm, linear programming duality, branch-and-bound algorithm, transportation problem, knapsack problem, traveling salesman problem, dynamic programming, interval scheduling, load balancing, minimum spanning tree, Dijkstra's algorithm, Bellman-Ford algorithm, Floyd-Warshall algorithm, network flows, Ford-Fulkerson algorithm, Euler tours, Konig's theorem, Hall's theorem, Gale-Shapley algorithm, Christofides' (3/2)-Approximation algorithm, and Menger’s theorem.