RESEARCH

Research interests

Methodologies:

Interpretable machine learning; Integration of supervised and unsupervised learning; Mathematical Programming; Dynamic Programming; Game theory.

Applications:

Data-driven decision making; Sequential decision making; E-Commerce; Decision support systems; Financial markets; Healthcare markets, operations.

working papers

Hosseininasab, A., van Hoeve, W.J. and Cire, A.A., 2019. Structure Mining for Interpretable Data-driven Sequential Decision Making. Submitted .

• 2nd place, 14th INFORMS Workshop on Data Mining & Decision Analytics best paper competition, Seattle, Washington. Oct. 2019

Hosseininasab, A., van Hoeve, W.J. and Tayur, S., Provider Network Selection and Transition under Competition. Working paper.

publications

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]