Publications

---

Publications:

1. Ezzat, A. A., Pourhabib, A. and Ding, Y., Sequential design for functional calibration of computer models, Technometrics, 60(3), 286-296, 2018.

2. Farmanesh, B., Pourhabib, A., Balasundaram, B., and Buchanan, A., A Bayesian framework for functional calibration of expensive computational models through non-isometric matching, arXiv:1508.01240 [stat.ML], 2018.

3. Farmanesh, B. and Pourhabib, A., Sparse pseudo-input local Kriging for large spatial datasets with exogenous variables, IISE Transactions, accepted, 2019.

4. Pourhabib, A., Huang, J. Z. and Ding, Y., Short-term wind speed forecast using measurements from multiple turbines in a wind farm, Technometrics, 58(1), 138-147, 2016.

5. C. Zhao, Y. Guan, Data-driven risk-averse two-stage stochastic program with zeta structure probability metrics, Optimization Online, 2015.

6. C. Zhao, Y. Guan, Data-driven risk-averse stochastic optimization with Wasserstein metric, Optimization Online, 2015.

7. C. Zhao, Y. Guan, Data-driven stochastic unit commitment for integrating wind generation, IEEE Transactions on Power Systems, 31(4): 2587-2596, 2015.

8. Pourhabib, A., Empirical similarity for absent data generation in imbalanced classification, arXiv:1508.01235 [stat.ML], 2015. 

9. Zhao, C., Chen, Y., Guan, Y., Wang, Q., & Wang, X. Short‐Term Power Generation Scheduling via Robust Optimization. Handbook of Clean Energy Systems, 2015. 

10. Pourhabib, A., Mallick, B. K. and Ding, Y., Absent data generating classifier for imbalanced class sizes, The Journal of Machine Learning Research, 16, 2695-2724, 2015.

11. Pourhabib, A., Huang, J. Z., Wang, K., Zhang, C., Wang, B. and Ding, Y., Modulus prediction of Buckypaper based on multi fidelity analysis involving latent variables, IIE Transactions. 47 (2), 141-152, 2015.

12. Zhao, C, and Guan, Y. Extended formulations for stochastic lot-sizing problems. Operations Research Letters 42.4, 278-283, 2014.

13. Zhao, C., Wang, Q., Wang, J., & Guan, Y. Expected Value and Chance Constrained Stochastic Unit Commitment Ensuring Wind Power Utilization. Power Systems, IEEE Transactions on, 29(6), 2696-2705, 2014.

14. Pourhabib, A., Liang, F. and Ding, Y., Bayesian site selection for fast Gaussian process regression, 46 (5), 543-555, 2014.

15. Zhao, C., & Guan, Y.  Unified stochastic and robust unit commitment. Power Systems, IEEE Transactions on, 28(3), 3353-3361, 2013.

16. Zhao, C., Wang, J., Watson, J. P., & Guan, Y. Multi-stage robust unit commitment considering wind and demand response uncertainties. Power Systems, IEEE Transactions on, 28(3), 2708-2717, 2013

17. Kianfar, K., Pourhabib, A. and Ding Y.,  An integer programming approach for analyzing the measurement redundancy in structured linear systems, IEEE Transactions on Automation Science and Engineering, 8(2), 447-450, 2011.

---

Presentations:

1. Local calibration of computer models, Spring Research Conference, Chicago, IL, May, 2016 (presented by A. Pourhabib)

2. Data-Driven Stochastic Unit Commitment for Integrating Wind Generation, Industrial and Systems Engineering Research Conference, Pittsburgh, PA, 2015 (presented by C. Zhao)

3. Expected Value and Chance Constrained Stochastic Unit Commitment Ensuring Wind Power Utilization, INFORMS Annual Meeting, Philadelphia, PA, 2015 (presented by C. Zhao)

4. Local calibration of computer models, INFORMS, Philadelphia, PA, November, 2015 (presented by A. Pourhabib)

5. Fast Gaussian Process Regression for Large Non-Stationary Spatial Data, INFORMS, Philadelphia, PA, November, 2015 (presented by B. Farmanesh)

6. Sparse pseudo-input local Kriging for large non-stationary spatial datasets with exogenous variables, Data Science Workshop, Seattle, WA, 2015 (presented by B. Farmanesh)

7. Non-isometric matching for local calibration, IIE Annual Conference, Nashville, TN, June, 2015  (presented by B. Farmanesh)

8. Data-driven Spatial-temporal modeling of local wind fields, INFORMS, San Francisco, CA, November, 2014 (presented by A. Pourhabib)

9. Embedded synthetic data generation for imbalanced two-class classification, INFORMS, San Francisco, CA, November, 2014 (presented by A. Pourhabib)

10. Multi-Stage Robust Unit Commitment Considering Wind and Demand Response Uncertainties, IEEE Power and Energy Society General Meeting, Washington D.C., 2014 (presented by C. Zhao)

11. Local calibration of parameters in poly (vinyl alcohol)-treated buckypaper fabrication, INFORMS, San Francisco, CA, November, 2014 (presented by A. Pourhabib)

12. Data-Driven Risk-Averse Two-Stage Stochastic Program, INFORMS Annual Meeting, San Francisco, CA, 2014 (presented by C. Zhao) 

13. Data-driven spatial-temporal modeling of local wind fields, Smart Grid Workshop, Texas A&M University, College Station, TX, April 2014 (poster presentation by A. Pourhabib)

14. Two-Stage and Multi-Stage Stochastic Unit Commitment under Wind Generation Uncertainty, Industrial and Systems Engineering Research Conference, Montreal, Canada, 2014 (presented by C. Zhao)

15. Bayesian site selection for Gaussian process regression, INFORMS, Minnesota, MN, October, 2013 (presented by A. Pourhabib)

16. Unified Stochastic and Robust Unit Commitment, INFORMS Annual Meeting, Minneapolis, MN, 2013 (presented by C. Zhao)

17. Risk Averse Data Driven, INFORMS Annual Meeting, Minneapolis, MN, 2013 (presented by C. Zhao)

18. Modeling the spatio-temporal dynamics of local wind fields at a wind farm, INFORMS, Minnesota, MN, October, 2013 (presented by A. Pourhabib)

19. Multi resolution analysis for modulus prediction of PVA treated buckypaper, INFORMS, Phoenix, AZ, October, 2012 (presented by A. Pourhabib)

20. Two-stage Robust Optimization for Power Grid System, Industrial and Systems Engineering Research Conference, Orlando, FL, 2012 (presented by C. Zhao)

21. An Expected Value Constrained Two-stage Stochastic Unit Commitment with Uncertain Wind Power Output, INFORMS Annual Meeting, Phoenix, AZ, 2012 (presented by C. Zhao)

22. Extended Reformulation of Stochastic Lot-sizing Problem”, INFORMS Annual Meeting, Phoenix, AZ, 2012 (presented by C. Zhao)

23. Bayesian site selection for fast Gaussian process regression, INFORMS, Charlotte, NC, November, 2011 (presented by A. Pourhabib)

24. Dynamic Pricing Strategies for Power Grid Problem, INFORMS Annual Meeting, Charlotte, NC, 2011 (presented by C. Zhao)

25. Multi-accuracy Bayesian models for improving property prediction of nanotube buckypaper composites, NSF Civil, Mechanical and Manufacturing Innovation, Atlanta, GA, January, 2011 (poster presentation by A. Pourhabib)

26. Integer programming approach for analyzing the measurement redundancy in structured linear systems, INFORMS, Austin, TX, November, 2010 (presented by A. Pourhabib)