Annie Chen

Annie's research interest is in large-scale discrete optimization methods, including mixed integer programming heuristics, approximate dynamic programming, and simulation-based optimization. Her research focuses on applications in online-retail inventory management, which draws from her work experience at Amazon.com and Walmart eCommerce. Prior to joining Marshall, Annie completed her PhD in the Department of Electrical Engineering and Computer Science at MIT, where she also served as a teaching assistant in Introduction to Operations Management, Nonlinear Programming, and Design and Analysis of Algorithms.

Teaching Experience

USC Marshall School of Business

Instructor and course developer, DSO 499 Python Programming for Business Analytics (Fall 2019, Spring 2020).

• Undergraduate elective course.
• Topics include computational thinking, variables, data structures, loops, conditional statements, functions, object-oriented programming, data analytics with pandas, and visualization.

Instructor, BUAD 311 Operations Management (Fall 2017, Spring 2018).

• Undergraduate upper-division core course for Business Administration majors.
• Topics include process analysis, Little's Law, queueing, optimization, revenue management, inventory management, and supply chain dynamics.

MIT

Teaching Assistant, 15.734 Introduction to Operations Management (Summer 2014).

• Overall rating of teaching: 5.8/7.0. Level: Executive MBA course. Faculty instructors: Prof. Özalp Özer and Prof. Charles Fine.

Instructor, MIT MISTI-Israel Global Teaching Lab (Winter 2014).

• Assisted with teaching at ORT High School, Lod, Israel for four weeks. Worked with Israeli teachers and students in a dynamic, multi-cultural, multi-lingual environment. Tutored students and designed learning material for grades 9-12 on English and math, in small groups of 1-6.

Teaching Assistant, 6.252/15.084J Nonlinear Programming (Spring 2013).

• Overall rating of teaching: 6.6/7.0. Level: Graduate. Faculty instructor: Prof. Pablo Parrilo.

Teaching Assistant, 6.046 Design and Analysis of Algorithms (Fall 2012).

• Overall rating of teaching: 5.9/7.0. Level: Undergraduate. Faculty instructors: Prof. Srini Devadas and Prof. Ronitt Rubinfeld.

Industry Experience

Amazon.com, Seattle, WA (Summer 2015)

• Research Scientist Intern, Supply Chain Optimization Technologies Group
• Developed simulation methods and software for online retail inventory placement decisions.

Walmart eCommerce (WalmartLabs), Mountain View, CA (Summer 2013)

• Engineering Intern, Demand Generation Group
• Developed large-scale optimization models, efficient computation methods, and software prototypes for business decisions in online advertising. Internship featured in Universum Top 100 article.

Interactive Intelligence, Indianapolis, IN (Summer 2012)

• Software Engineer Intern, Automatic Speech Recognition Group
• Improved the performance of an industrial-strength speech recognizer by reducing memory usage while preserving accuracy. Researched optimization methods for simultaneous staffing and scheduling in call center workforce management.

Research Publications

• A. I. Chen and S. C. Graves, Item Aggregation and Column Generation for Online-Retail Inventory Placement. Accepted to Manufacturing and Service Operations Management as of September 2019. Available at SSRN: https://ssrn.com/abstract=3464278.
• A. I. Chen and S. C. Graves, Inventory Replenishment in Online Retail via Simulation Optimization. Working paper.
• A. I. Chen, Large-Scale Optimization in Online-Retail Inventory Management. PhD thesis, Massachusetts Institute of Technology, 2017.
• A. I. Chen and S. C. Graves, Simulation optimization with sensitivity information: An application to online-retail inventory replenishment. Proceedings of the 2016 Winter Simulation Conference (WSC), Washington, DC, 2016, pp. 3654-3655.
• A. I. Chen and S. C. Graves, Sparsity-Constrained Transportation Problem. Proceedings of the Production and Operations Management Society (POMS) 25th Annual Conference, Atlanta, Georgia, May 2014.
• A. I. Chen and A. Ozdaglar, A Fast Distributed Proximal-Gradient Method. [Appendix with full proofs] Proceedings of the 50th Annual Allerton Conference on Communications, Control, and Computing, Urbana, Illinois, October 2012.
• A. I. Chen, Fast distributed first-order methods. Master of Science thesis, Massachuestts Institute of Technology, 2012.