Foad Mahdavi Pajouh (fmahdav1)

Foad Mahdavi Pajouh

Associate Professor

School of Business

Babbio Center 627
(201) 216-3339

Education

  • PhD (2012) Oklahoma State University (Industrial Engineering and Management)
  • MS (2006) Tarbiat Modares University (Industrial Engineering)
  • BS (2004) Sharif University of Technology (Industrial Engineering)

Research

Theoretical, Computational and Algorithmic Optimization. Big Data Analytics of Complex Networks with applications in Business Analytics, Social Network Analysis, Financial Network Analysis and Cybersecurity.
Google Scholar Profile

Appointments

Stevens Institute of Technology
Jack Howe Fellow and Associate Professor,
School of Business,
August 2021 - Present.

University of Massachusetts Boston
Assistant Professor,
Management Science and Information Systems,
August 2014 - May 2021.

University of Florida
Research Assistant Professor,
Industrial & Systems Engineering,
August 2012 - July 2014.

Selected Publications

Book Chapter

  1. Mahdavi Pajouh, F. (2023). Finding central cliques in network systems.. Encyclopedia of Optimization (3 ed.). Springer.
    https://link.springer.com/referenceworkentry/10.1007/978-3-030-54621-2_805-1.
  2. Mahdavi Pajouh, F.; Veremyev, A.; Boginski, V. (2014). Analysis and design of robust network clusters with bounded diameter. Examining Robustness and Vulnerability of Networked Systems (pp. 141-160). IOS Press,.
    https://ebooks.iospress.nl/publication/36426.
  3. Rysz, M.; Mahdavi Pajouh, F.; Krokhmal, P.; Pasiliao, E. (2014). On risk-averse weighted k-club problems. Examining Robustness and Vulnerability of Networked Systems (pp. 231-242). IOS Press.
    https://ebooks.iospress.nl/volumearticle/36431.
  4. Balasundaram, B.; Mahdavi Pajouh, F. (2013). Graph theoretic clique relaxations and applications. Handbook of Combinatorial Optimization (2 ed., pp. 1559-1598). Springer.
    https://link.springer.com/referenceworkentry/10.1007%2F978-1-4419-7997-1_9.
  5. Mahdavi Pajouh, F.; Balasundaram, B. (2011). Gradient-type methods. Wiley Encyclopedia of Operations Research and Management Science (vol. 3, pp. 2092-2099). John Wiley & Sons, Inc..
    https://onlinelibrary.wiley.com/doi/10.1002/9780470400531.eorms0363.
  6. Bukkapatnam, S. T.; Yang, H.; Mahdavi Pajouh, F. (2009). Towards prediction of nonlinear and nonstation- ary evolution of customer preferences using local Markov models. The Art and Science behind Successful Product Launches (pp. 271-287). Springer.
    https://link.springer.com/chapter/10.1007%2F978-90-481-2860-0_15.

Conference Proceeding

  1. Nasirian, F.; Mahdavi Pajouh, F.; Namayanja, J. (2017). Exact algorithm for the minimum cost vertex blocker clique problem. In: Proceedings of the Northeast Decision Sciences Institute 2017 Annual Conference (pp. 621-627).
    https://nedsi.decisionsciences.org/past-proceedings.
  2. Mahdavi Pajouh, F.; Kamath, M. (2010). Applications of Queueing Models in Hospitals. In: Proceedings of the 2010 Midwest Association for Information Systems (MWAIS) Conference, paper 23.
    https://aisel.aisnet.org/mwais2010/23/.
  3. Oztekin, A.; Mahdavi Pajouh, F.; Kong, Z.; Bukkapatnam, S. T. (2010). Determining the Optimum Number of RFID Readers for E cient Asset Tracking. In: Proceedings of the 2009 American Society of Mechanical Engineers (ASME) Conference (pp. 1323-1331).
    https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2009/1323/335564.

Journal Article

  1. Zhong, H.; Mahdavi Pajouh, F.; Butenko, S.; Prokopyev, O. A. (2024). On interdicting dense clusters in a network. INFORMS Journal on Computing [UTD-24 Journal List, ABS/AJG 2021: 3].
    https://pubsonline.informs.org/doi/10.1287/ijoc.2023.0027.
  2. Jenkins, D.; Mahdavi Pajouh, F.; Kirshen, P.; Eftekhar, M. (2024). Which Is More Rewarding in Managing Sea Level Rise and Hurricane Storm Surge Flooding: Mitigation or Response?. Production and Operations Management [FT-50 Journal List, ABS/AJG 2021: 4] (1 ed., vol. 33, pp. 364-382).
    https://journals.sagepub.com/doi/abs/10.1177/10591478231224945.
  3. Zhong, H.; Mahdavi Pajouh, F.; Prokopyev, O. (2023). On designing networks resilient to clique blockers. European Journal of Operational Research [ABS/AJG 2021: 4] (1 ed., vol. 307, pp. 20-32).
    https://www.sciencedirect.com/science/article/abs/pii/S0377221722007251?via%3Dihub.
  4. Wei, N.; Walteros, . L.; Mahdavi Pajouh, F. (2021). Integer programming formulations for minimum spanning tree interdiction. INFORMS Journal on Computing [UTD-24 Journal List, ABS/AJG 2021: 3] (4 ed., vol. 33, pp. 1461-1480).
    https://pubsonline.informs.org/doi/10.1287/ijoc.2020.1018.
  5. Zhong, H.; Mahdavi Pajouh, F.; Prokopyev, O. A. (2021). Finding influential groups in networked systems: the most degree-central clique problem. Omega [ABS/AJG 2021: 3] (vol. 101, pp. 102262).
    https://www.sciencedirect.com/science/article/pii/S030504831931059X.
  6. Mahdavi Pajouh, F. (2020). Minimum cost edge blocker clique problem. Annals of Operations Research [ABS/AJG 2021: 3] (vol. 294, pp. 345-376).
    https://link.springer.com/article/10.1007/s10479-019-03315-x#citeas.
  7. Nasirian, F.; Mahdavi Pajouh, F.; Balasundaram, B. (2020). Detecting a most closeness-central clique in complex networks. European Journal of Operational Research [ABS/AJG 2021: 4] (2 ed., vol. 283, pp. 461-475).
    https://www.sciencedirect.com/science/article/pii/S0377221719309464.
  8. Yezerska, O.; Mahdavi Pajouh, F.; Veremyev, A.; Butenko, S. (2019). Exact algorithms for the minimum s-club partitioning problem. Annals of Operations Research [ABS/AJG 2021: 3] (1-2 ed., vol. 276, pp. 267-291).
    https://link.springer.com/article/10.1007/s10479-017-2665-2#citeas.
  9. Nasirian, F.; Mahdavi Pajouh, F.; Namayanja, J. (2019). Exact algorithms for the minimum cost vertex blocker clique problem. Computers & Operations Research [ABS/AJG 2021: 3] (vol. 103, pp. 296-309).
    https://www.sciencedirect.com/science/article/pii/S0305054818303022.
  10. Rysz, M.; Mahdavi Pajouh, F.; Pasiliao, E. L. (2018). Finding clique clusters with the highest betweenness centrality. European Journal of Operational Research [ABS/AJG 2021: 4] (1 ed., vol. 271, pp. 155-164).
    https://www.sciencedirect.com/science/article/pii/S0377221718303849.
  11. Rysz, M.; Mahdavi Pajouh, F.; Krokhmal, P.; Pasiliao, E. L. (2018). Identifying risk-averse low-diameter clusters in graphs with stochastic vertex weights. Annals of Operations Research [ABS/AJG 2021: 3] (1 ed., vol. 262, pp. 89-108).
    https://link.springer.com/article/10.1007/s10479-016-2212-6.
  12. Yezerska, O.; Mahdavi Pajouh, F.; Butenko, S. (2017). On biconnected and fragile subgraphs of low diameter. European Journal of Operational Research [ABS/AJG 2021: 4] (2 ed., vol. 263, pp. 390-400).
    https://www.sciencedirect.com/science/article/pii/S0377221717304484#!.
  13. Mahdavi Pajouh, F.; Moradi, E.; Balasundaram, B. (2017). Detecting large risk-averse 2-clubs in graphs with random edge failures. Annals of Operations Research [ABS/AJG 2021: 3] (1 ed., vol. 249, pp. 55-73).
    https://link.springer.com/article/10.1007%2Fs10479-016-2279-0.
  14. Mahdavi Pajouh, F.; Balasundaram, B.; Hicks, I. V. (2016). On the 2-club polytope of graphs. Operations Research [FT-50 Journal List, ABS/AJG 2021: 4*] (6 ed., vol. 64, pp. 1466-1481).
    https://pubsonline.informs.org/doi/abs/10.1287/opre.2016.1500?journalCode=opre.
  15. Ma, J.; Mahdavi Pajouh, F.; Balasundaram, B.; Boginski, V. (2016). The minimum spanning k-core problem with bounded CVaR under probabilistic edge failures. INFORMS Journal on Computing [UTD-24 Journal List, ABS/AJG 2021: 3] (2 ed., vol. 28, pp. 295-307).
    https://pubsonline.informs.org/doi/10.1287/ijoc.2015.0679.
  16. Mahdavi Pajouh, F.; Walteros, J. L.; Boginski, V.; Pasiliao, E. L. (2015). Minimum edge blocker dominating set problem. European Journal of Operational Research [ABS/AJG 2021: 4] (1 ed., vol. 247, pp. 16-26).
    https://www.sciencedirect.com/science/article/pii/S0377221715004270?via%3Dihub#!.
  17. Mahdavi Pajouh, F.; Boginski, V.; Pasiliao, E. . (2014). Minimum vertex blocker clique problem. Networks [Impact Factor: 2.1] (1 ed., vol. 64, pp. 48-64).
    https://onlinelibrary.wiley.com/doi/abs/10.1002/net.21556.
  18. Mahdavi Pajouh, F.; Miao, Z.; Balasundaram, B. (2014). A branch-and-bound approach for maximum quasi-cliques. Annals of Operations Research [ABS/AJG 2021: 3] (1 ed., vol. 216, pp. 145-161).
    https://link.springer.com/article/10.1007%2Fs10479-012-1242-y.
  19. Mahdavi Pajouh, F.; Xing, D.; Zhou, Y.; Hariharan, S.; Balasundaram, B.; Liu, T.; Sharda, R. (2013). A specialty steel bar company uses analytics to determine available-to-promise dates. INFORMS Journal on Applied Analytics [ABS/AJG 2021: 2] (6 ed., vol. 43, pp. 503-517).
    https://pubsonline.informs.org/doi/abs/10.1287/inte.2013.0693.
  20. Mahdavi Pajouh, F.; Balasundaram, B.; Prokopyev, O. A. (2013). On characterization of maximal independent sets via quadratic optimization. Journal of Heuristics [ABS/AJG 2021: 3] (4 ed., vol. 19, pp. 629-644).
    https://link.springer.com/article/10.1007%2Fs10732-011-9171-5.
  21. Mahdavi Pajouh, F.; Balasundaram, B. (2012). On inclusionwise maximal and maximum cardinality k-clubs in graphs. Discrete Optimization [ABS/AJG 2021: 2] (2 ed., vol. 9, pp. 84-97).
    https://www.sciencedirect.com/science/article/pii/S1572528612000163#!.
  22. Oztekin, A.; Mahdavi Pajouh, F.; Delen, D.; Swim, L. K. (2010). An RFID network design methodology for asset tracking in healthcare. Decision Support Systems [ABS/AJG 2021: 3] (1 ed., vol. 49, pp. 100-109).
    https://www.sciencedirect.com/science/article/pii/S0167923610000205#!.
  23. Oztekin, A.; Mahdavi Pajouh, F.; Erande, K.; Kong , Z.; Swim, L. K.; Bukkapatnam, S. T. (2010). Criticality index analysis based optimal RFID reader placement models for asset tracking. International Journal of Production Research [ABS/AJG 2021: 3] (9 ed., vol. 48, pp. 2679-2698).
    https://www.tandfonline.com/doi/abs/10.1080/00207540903565006.
  24. Sepehri, M. M.; Mahdavi Pajouh, F. (2010). Predicting web users viewing route using clickstream analysis. Iranian Journal of Electrical and Computer Engineering (4 ed., vol. 7, pp. 290-298).