Published or Near-Complete Research

Chronological List of Journal Papers: (student advisees marked with *; working papers not included)

  1. Y. Yeh, S. Shashaani, and R. Pasupathy (2024), Bias Correction in Optimization with Bootstraps, To Submit.
  2. S. Sanchez, S. Shashaani, and D. Eckman (2024), Changing the Paradigm: Learning Deeply About Sequential Optimization Algorithms via Data Farming, To Submit.
  3. K. Vahdat* and S. Shashaani (2024), Robust Output Analysis with Monte-Carlo Methodology, To Submit. [arxiv]
  4. Y. Ha*, S. Shashaani, and R. Pasupathy (2024), On Common Random Numbers and the Complexity of Adaptive Sampling Trust-region Methods, To Submit. [online]
  5. A. Kushwaha, S. Shashaani, and A. Kemper (2024), Robust Variational Quantum Algorithms and Hamiltonian Uncertainty, Submitted.
  6. Y. Ha*, S. Shashaani, and M. Menickelly (2024), Two-stage Sampling and Variance Modeling for Variational Quantum Algorithms, Submitted. [arxiv]
  7. P. Jain*, S. Shashaani, and E. Byon (2024), Simulation Model Calibration with Dynamic Stratification and Adaptive Sampling, Under Second Review at Journal of Simulation. [arxiv]
  8. Y. Jeon, R. Pasupathy and S. Shashaani (2023), Statistical Inference on Simulation Output: Batching as an Inferential Device, Under Second Review at Journal of Simulation. [arxiv]
  9. N. Alizadeh, K. Vahdat*, S. Shashaani, O. Ozaltin, and J. Swann (2023), Personalized Predictions for Unplanned Hospitalization due to Urinary Tract Infection, Submitted. [online]
  10. J. Park, E. Byon, Y. M. Ko, and S. Shashaani (2023), Strata Design in Stochastic Simulations with Multivariate Inputs, Under Second Review at Technometrics. [online]
  11. S. Shashaani, D. Eckman, and S. Sanchez (2023), Data Farming the Parameters of Simulation-optimization Solvers, Under Second Review at ACM TOMACS. [online]
  12. Y. Ha* and S. Shashaani (2024), Iteration Complexity and Finite-time Efficiency of Adaptive Sampling Trust-region Methods for Stochastic Derivative-free Optimization, IISE Transactions. [download]
  13. S. Shashaani, O. Surer, M. Plumlee, and S. Guikema (2023), Building Trees for Probabilistic Prediction via Scoring Rules, Tentatively Accepted at Technometrics. [online]
  14. P. Jain*, S. Shashaani, and E. Byon (2023), Wake Effect Parameter Calibration with Large-scale Field Operational Data using Stochastic Optimization, Applied Energy, 347, p.121426. [pre-print][download]
  15. E. Houser*, S. Shashaani, O. Harrysson and Y. Jeon* (2023), Predicting Additive Manufacturing Defects with Feature Selection for Imbalanced Data, IISE Transactions, pp.1-26. [pre-print][download]
  16. D. Eckman, S. Shashaani, and S., Henderson (2022), SimOpt: A Testbed for Simulation-optimization Experiments, INFORMS Journal on Computing, 35(2):495-508, 2023. [pre-print][download]
  17. D. Eckman, S. Shashaani, and S., Henderson (2022), Diagnostic Tools for Evaluating and Comparing Simulation-optimization Algorithms, INFORMS Journal of Computing, 35(2):350-367.[download]
  18. S. Shashaani and K. Vahdat (2022), Improved Feature Selection with Simulation Optimization, Optimization and Engineering, 24:1183–1223. [download]
  19. T. Chen*, J. Beekman, S. Guikema, and S. Shashaani (2019), Statistical Modeling in Absence of System Specific Data: Exploratory Empirical Analysis for Prediction of Water Main Breaks, Journal of Infrastructure Systems, 25(2):04019009. [download]
  20. S. Shashaani, S. Guikema, J. Pino, and S. Quiring (2018), Multi-Stage Prediction for Zero-inflated Hurricane Induced Power Outages. IEEE Access, 6: 62432-62449. [download]
  21. S. Shashaani, F. Hashemi, and R. Pasupathy (2018), ASTRO-DF: A Class of Adaptive Sampling Trust-region Algorithms for Derivative-free Stochastic Optimization, SIAM Journal on Optimization, 28(4):3145-3176. [download]
  22. E. Nsoesie, R. Beckman, S. Shashaani, K. Nagaraj, and M. Marathe (2013), A Simulation Optimization Approach to Epidemic Forecasting, PLoS ONE, 8(6):e67164. [download]
  23. M. Mazdeh, S. Shashaani, A. Ashouri, and K. Hindi (2011), Single-machine Batch Scheduling Minimizing Weighted Flow Times and Delivery Costs, Applied Mathematical Modeling, 35(1): 563-570. [download]

Chronological List of Conference Proceedings and Book Chapters: (student advisees marked with *)

  1. N. Felice*, S. Shashaani, D.E. Eckman, and S.S. Sanchez, Data Farming for Repeated Simulation Optimization Experiments, In Proceedings of the 2024 Winter Simulation Conference, Under Review.
  2. Y. Jeon* and S. Shashaani, Digital Twin Calibration with Root Finding and Bayesian Optimization, In Proceedings of the 2024 Winter Simulation Conference, Under Review.
  3. E. Houser* and S. Shashaani, Rapid Screening and Nested Partitioning for Feature Selection, In Proceedings of the 2024 Winter Simulation Conference, Under Review.
  4. H.K. Eun*, S. Shashaani, and R.R. Barton, Identifying Input Uncertainty Induced Bias Using Wasserstein and Kingman Metrics, In Proceedings of the 2024 Winter Simulation Conference, Under Review.
  5. S. Shashaani (2024), Simulation Optimization: A Tutorial, In Proceedings of the 2024 Winter Simulation Conference, Under Review.
  6. K. Vahdat* and S. Shashaani (2023), Adaptive Ranking and Selection Based Genetic Algorithms For Data-driven Problems, In Proceedings of the 2023 Winter Simulation Conference, edited by C.G. Corlu, S.R. Hunter, H. Lam, B.S. Onggo, J. Shortle, and B. Biller. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc. [download]
  7. Y. Ha and S. Shashaani (2023), Towards Greener Stochastic Derivative-free Optimization with Trust Regions and Adaptive Sampling, In Proceedings of the 2023 Winter Simulation Conference, edited by C.G. Corlu, S.R. Hunter, H. Lam, B.S. Onggo, J. Shortle, and B. Biller. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc. [download]
  8. P. Jain* and S. Shashaani (2023), Stratification with Concomitant Variables in Stochastic Trust-region Optimization, In Proceedings of the 2023 Winter Simulation Conference, edited by C.G. Corlu, S.R. Hunter, H. Lam, B.S. Onggo, J. Shortle, and B. Biller. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc. [download]
  9. D. Eckman, S. Henderson, and S. Shashaani (2023), Stochastic Constraints: How Feasible is Feasible?, In Proceedings of the 2023 Winter Simulation Conference, edited by C.G. Corlu, S.R. Hunter, H. Lam, B.S. Onggo, J. Shortle, and B. Biller. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc. [download]
  10. S. Shashaani, and K. Vahdat (2023), Monte Carlo based Machine Learning, In: Grothe, O., Nickel, S., Rebennack, S., Stein, O. (eds) Operations Research Proceedings 2022. OR 2022. Lecture Notes in Operations Research. Springer, Cham. [download]
  11. P. Jain*, S. Shashaani, and E. Byon (2022), Robust Simulation Optimization with Stratification, In Proceedings of the 2022 Winter Simulation Conference, edited by B. Feng, G. Pedrielli, Y. Peng, S. Shashaani, E. Song, C.G. Corlu, L.H. Lee, E.P. Chew, T.M.K. Roeder, and P. Lendermann. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc. [download]
  12. Y. Ha*, S. Shashaani, and Q. Tran-Dinh (2021), Improved Complexity of Trust-region Optimization for Zeroth-order Stochastic Oracles, In Proceedings of the 2021 Winter Simulation Conference, edited by S. Kim, B. Feng, K. Smith, S. Masoud, Z. Zheng, C. Szabo, and M. Loper, Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc. [download]
  13. K. Vahdat*, and S. Shashaani (2021), Non-parametric Uncertainty Bias and Variance Estimation via Nested Bootstrapping and Influence Functions, In Proceedings of the 2021 Winter Simulation Conference, edited by S. Kim, B. Feng, K. Smith, S. Masoud, Z. Zheng, C. Szabo, and M. Loper, Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc. [download]
  14. P. Jain*, S. Shashaani, and E. Byon (2021), Wake Effect Calibration in Wind Power Systems with Adaptive Sampling based Optimization, In Energy Systems Division of IISE Annual Conference and Expo Proceedings. [download]
  15. L. Mao*, K. Vahdat, S. Shashaani, and J. Swann (2020), Personalized Predictions for Unplanned Urinary Tract Infection Hospitalizations with Hierarchical Clustering, In 2020 INFORMS Conference on Service Science Proceedings; AI and Analytics for Public Health (H. Yanh, R. Qiu, and Q. Chen, eds.), pp. 453-465, Springer International Publishing. [download]
    • Finalist – Student Paper Competition
  16. K. Vahdat*, and S. Shashaani, Simulation Optimization Based Feature Selection, a Study on Data-driven Optimization with Input Uncertainty, In Proceedings of the 2020 Winter Simulation Conference, edited by K.G. Bae, B. Feng, B., S. Kim, S. Lazarova-Molnar, Z. Zheng, T.M.K. Roeder, and R. Thiesing, Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc. [download]
  17. A. Manda, K. Gopalswamy, S. Shashaani, and R. Uzsoy (2019), A Simulation Optimization Approach for Managing Product Ramp Up in Production Lines, In Proceedings of the 2020 Winter Simulation Conference, edited by by K.-H.G. Bae, B. Feng, B., S. Kim, S. Lazarova-Molnar, Z. Zheng, T.M.K. Roeder, and R. Thiesing, Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc. [download]
  18. D. Vasquez*, S. Shashaani, and R. Pasupathy (2019), ASTRO for Derivative-based Stochastic Optimization: Algorithm Description and Numerical Experiments, In Proceedings of the 2019 Winter Simulation Conference, edited by N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc. [download]
  19. S. Shashaani, S. Hunter, and R. Pasupathy (2016), ASTRO-DF: Adaptive Sampling Trust-region Optimization Algorithms, Heuristics, and Numerical Experience. In Proceedings of 2016 Winter Simulation Conference, edited by T.M.K. Roeder, P.I. Frazier, R. Szechtman, E. Zhou, T. Huschka, and S.E. Chick, Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc. [download]
    • Winner – Best Student Paper award