Published Papers
•
Self-Adapting Approximations of Markov Decision Processes: A Guided Tour
A. Cire, S. Nadarajah, P. Pakiman, N. Soheili.
Forthcoming in INFORMS TutORials in Operations Research
•
Self-Guided Approximate Linear Programs: Randomized Multi-Shot Approximation of Discounted Cost Markov Decision Processes.
P. Pakiman, S. Nadarajah, N. Soheili, Q. Lin.
Published in Management Science.
•
SMOILE: A Shopper Marketing Optimization and Inverse Learning Engine.
A. Chenreddy, P. Pakiman, S. Nadarajah, R. Chandrasekaran, R. Abens.
Published in Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2019).
Under Review / Working Papers
•
Dynamic Optimization of Workforce Talent.
D. Adelman, A. J. Mersereau, P. Pakiman.
Under second-round review at Operations Research.
•
Adaptive Risk Mitigation in Demand Learning
P. Pakiman, B. Chen, S. Nadarajah, S. Jasin.
Major revision at Manufacturing & Service Operations Management.
•
Automated Design of Inventory Policy with Large Language Models: An Exploratory Study
F. Yang, P. Baxi, S. Jasin, Y. Zhang, Y. Lei, M. Liu, P. Pakiman.
Under review at Management Science.
•
Back to the Future: Revisiting a Pioneering Approximation of Average Cost Markov Decision Processes Using a Multi-Shot Perspective
P. Pakiman, S. Nadarajah.
In preparation for submission to INFORMS Journal on Computing.
Work In-Progress
•
Performance-blind and Data-driven Dynamic Assignment.
D. Adelman, C. Keceli, P. Pakiman.
Work in progress.
•
Retrospective Approximate Dynamic Programming.
D. Adelman, P. Pakiman.
Work in progress.
•
Randomized Multi-Shot Least Squares Monte Carlo for Option Exercise.
S. Nadarajah, P. Pakiman.
Work in progress.