Interpretable machine learning; Integration of supervised and unsupervised learning; Mathematical Programming; Dynamic Programming; Game theory.
Data-driven decision making; Sequential decision making; E-Commerce; Decision support systems; Financial markets; Healthcare markets, operations.
Hosseininasab, A., van Hoeve, W.J. and Cire, A.A., 2019. Structure Mining for Interpretable Data-driven Sequential Decision Making. Submitted .
Hosseininasab, A., van Hoeve, W.J. and Tayur, S., Provider Network Selection and Transition under Competition. Working paper.
Hosseininasab, A., 2020. Interpretable Learning and Pattern Mining: Scalable Algorithms and Data-Driven Applications. PhD Thesis, Carnegie Mellon University. [Thesis]
Hosseininasab, A., van Hoeve, W.J., 2019. Exact Multiple Sequence Alignment by Synchronized Decision Diagrams. INFORMS Journal on Computing, to appear. [Paper]
Hosseininasab, A., van Hoeve, W.J. and Cire, A.A., 2019. Constraint-Based Sequential Pattern Mining with Decision Diagrams. In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, 1495-1502. [Paper]
Hosseininasab, A. and Gzara, F., 2019. Effects of feasibility cuts in Lagrangian relaxation for a two-stage stochastic facility location and network flow problem. Optimization Letters,14(1), 171-193. [Paper]
Hosseininasab, A., 2015. The continuous time service network design problem. MSc Thesis, University of Waterloo. [Thesis]
Hosseininasab, A. and Ahmadi, A., 2015. Selecting a supplier portfolio with value, development, and risk consideration. European Journal of Operational Research, 245(1), 146-156. [Paper]
Hosseininasab, A., 2015. Regularisation and reliability assessment of data in survey analysis. International Journal of Data Analysis Techniques and Strategies vol. 7 (3), 284-300 [Paper]