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Name: Dr. Ismail Shah
Designation: Assistant Professor
Department: Statistics


Qualifications: PhD      (University of Padova, Italy)
MS       (Lunds University, Sweden)
M.Sc.   (University of Peshawar, Pakistan)

(HEC Approved PHD Supervisor)


Phone: +92-51 9064-2186
Email: ishah@qau.edu.pk
Status: On Job
Other Weblink: https://www.researchgate.net/profile/Ismail_Shah2


Research Interests Publications Conferences Research Projects

Functional Data Analysis
Regression Analysis
Time series Analysis
Applied Statistics
Quality Control

Courses Taught:
ST-102: Basic Statistical Inference
ST-310: Regression Analysis-I
ST-609: Linear Models
ST-302: Statistical Methods
ST-625: Recent Development in Statistics
ST- 301: Probability and Probability Distribution-I
ST- 309: Probability and Probability Distribution-II
ST-407:  Generalized Linear Models
ST-616:  Time Series Analysis
ST- 403/411: Time Series Analysis and Forecasting
ST-313: Quality Control and Quality Management
ST-420: Statistical Quality Management

Current Courses:
ST-704: Functional Data Analysis
ST- 301: Probability and Probability Distribution-I

·         Shah, I., Bibi, H., Ali, S.,  Wang, L., and Yue, Z. (2020), Forecasting one-day-ahead electricity prices for Italian electricity market using parametric and nonparametric approaches, IEEE Access, 8(1), 123104-123113, doi: 10.1109/ACCESS.2020.3007189. (Impact Factor= 3.745, ISSN: 2169-3536)

·         Raza, SMM, Ali, S, Shah, I, and Butt, MM. (2020), Conditional mean‐ and median‐based cumulative sum control charts for Weibull data. Quality and Reliability Engineering International, 1– 25, doi:10.1002/qre.2746 (Impact Factor=1.718 , ISSN: 1099-1638)

·         Siddiqa, H., Ali, S. and Shah, I. (2020),  Most recent changepoint detection in censored panel data. Computational Statistics, 1-26, doi:10.1007/s00180-020-01028-5, (Impact Factor=0.744 , ISSN: 1613-9658)

·         Shah, I., Iftikhar, H., & Ali, S. (2020). Modeling and Forecasting Medium-Term Electricity Consumption Using Component Estimation Technique. Forecasting, 2(2), 163-179, doi:10.3390/forecast2020009 (Impact Factor= , ISSN: 2571-9394)

·         Ali, S., Shah, I., Wang, L., and Yue, Z. (2020), A Comparison of Shewhart-type Time-Between-Events Control Charts based on the Renewal Process, IEEE Access, 8(1), 113683-113701, DOI:10.1109/ACCESS.2020.3003265. (Impact Factor= 4.098, ISSN: 2169-3536)

·         Raza, S. M. M ., Ali, S., Shah, I., Wang, L., and Yue, Z. (2020), On Efficient Monitoring of Weibull Lifetimes Using Censored Median Hybrid DEWMA Chart, Complexity, 2020, Article ID 9232506, 10 pages, DOI: https://doi.org/10.1155/2020/9232506. (Impact Factor= 2.591, ISSN: 1076-2787)

·         Shah, I., & Lisi, F. (2020). Forecasting of electricity price through a functional prediction of sale and purchase curves. Journal of Forecasting. 39, 242259, DOI: 10.1002/for.2624, (Impact Factor=0.816, ISSN: 0277-6693, E-ISSN: 1099-131X)

·         S. Ali, S. Ali, Shah, I., G. F. Siddiqui, T. Saba and A. Rehman. (2020). Reliability Analysis for Electronic Devices Using Generalized Exponential Distribution, IEEE Access, 8, 108629-108644, doi: 10.1109/ACCESS.2020.3000951. (Impact Factor= 4.098, ISSN: 2169-3536)

·         Ali, S., Zafar, T., Shah, I., and Wang, L. (2020), Cumulative Conforming Control Chart assuming Discrete Weibull Distribution, IEEE Access, 8 (1), 10123-10133, DOI: 10.1109/ACCESS.2020.2964602. (Impact Factor= 4.098, ISSN: 2169-3536)

·         Ali, S., Altaf, N., Shah, I., Wang, L., and Raza, S. M. M. (2020), On the effect of Estimation Error for the Risk-adjusted Charts, Complexity, 2020, Article ID 6258010, 21 pages. DOI:10.1155/2020/6258010 .(Impact Factor= 2.591, ISSN: 1076-2787)

·         Aslam, M., Ali, S., Yousaf, R., and Shah, I. (2020), Mixture of Transmuted Pareto Distribution: Properties, Applications and Estimation under Bayesian Framework, Journal of the Franklin Institute-Engineering and Applied Mathematics, 357 (5), 2934-2957, DOI: 10.1016/j.jfranklin.2019.11 (Impact Factor= 3.653, ISSN: 0016-0032)

·         Ara, J., Ali, S., and Shah, I., (2020), Monitoring Schedule Time using Exponentially Modified Gaussian Distribution, Quality Technology & Quantitative Management, 17 (4), 448-469, DOI: 10.1080/16843703.2019.1668164. (Impact Factor=0.946, ISSN: 1684-3703)

·         Ali, S., and Shah, I. (2020), Monitoring Regularly Maintained Systems Based on the Renewal Process with Generalized Exponential Distribution of Time between Events, 48 (5), Journal of Testing and Evaluation, 48, DOI: 10.1520/JTE20180044. (Impact Factor=0.669,  ISSN 0090-3973, E-ISSN: 1945-7553).

·         Shah, I., Iftikar, H., Ali, S., and Wang, D., (2019). Short-Term Electricity Demand Forecasting Using Components Estimation Technique, Energies, 12, 2532. DOI: 10.3390/en12132532 (Impact Factor=2.707, ISSN and EISSN: 1996-1073)

·         Ali, S., Shafqat, M., Shah, I., and Dey, S. (2019), Bivariate Discrete Nadarajah and Haghighi Distribution: Properties and Different Methods of Estimation, Filomat, 33 (17), 5589-5610. (Impact Factor=0.789, ISSN: 0354-5180)

·         Ali, S., Khan, H., Shah, I., Butt, M. M., and Suhail, M., (2019), A comparison of some new and old robust ridge regression estimators, Communication in Statistics-Simulation and Computation, DOI:10.1080/03610918.2019.1597119. (Impact Factor=0.501,  Print ISSN: 0361-0918 Online ISSN: 1532-4141)

·         Ali, S., Ali, S., Shah, I., and Khajavi, A. N. (2019), Reliability Analysis for Electronic Devices using Beta Generalized Weibull Distribution, Iranian Journal of Science and Technology, Transactions A: Science, 43, (5), 2501-2514. DOI:10.1007/s40995-019-00730-4. (Impact Factor= 0.692,  ISSN: 1028-6276 (Print) 2364-1819 (Online))

·         Yousaf, F., Ali, S. and  Shah, I. (2019), Statistical Inference for the Chen Distribution Based on Upper Record Values. Annals of Data Science. 6, 831–851. DOI: 10.1007/s40745-019-00214-7.

·         Lisi, F., and Shah, I. (2019). Forecasting next-day electricity demand and prices based on functional models. Energy Systems, 1-33. DOI: 10.1007/s12667-019-00356-w (ISSN: 1868-3967 (Print) 1868-3975 (Online))

·         Shah, I., and Lisi, F. (2015). Day-ahead electricity demand forecasting with nonparametric functional models. In 12th International Conference on the European Energy Market (EEM) (pp. 1-5). IEEE.

·         Siddiqa.H., Ali, S. and Shah, I. (2019). cpcens: Changepoint Analysis using Censored Time Series Data. R package version 0.1.0., https://CRAN.R-project.org/package=cpcens

·         Durante, D., Shah, I., & Torelli, N. (2014). Bayesian nonparametric modeling of contraceptive use in India. arXiv preprint arXiv:1405.7555.

 

·         Bernoulli-IMS One World Symposium 2020, held virtually, August 24 – 28, 2020.

·         12th International Conference on the European Energy Market, Lisbon Portugal. April 19-22, 2015

·         13th International Conference On Statistical Sciences, Peshawar Pakistan. March 16-18, 2015

·         International work-conference on Time Series, Granada Spain. June 25-27, 2014

·         Recent advances in statistical inference: theory and case studies, Padova Italy.  March 21-23, 2013

 

Hierarchical modeling for determinants of out-of-school children in Pakistan

Principal Investigator

0.430 Millions

Higher Education Commission, Pakistan.

01 year

2018- 2019

(Completed)

Monitoring the Regularly Maintained Systems assuming an Exponentiated Class of Lifetime Distribution of the Renewal process

Co-Principal Investigator

0.348 Millions

Higher Education Commission, Pakistan.

01 year

2019-2020

(Completed)

A comparison of Reliability analysis for electronic devices using beta generalized Weibull and generalized exponential distributions

Co-Principal Investigator

0.430 Millions

Higher Education Commission, Pakistan.

01 year

2018- 2019

(Completed)

Modeling and Forecasting complex time series data: A case study from electricity market

Principal Investigator

0.150 Millions

URF, Quaid-i-Azam University.

12 months

2018.

(Completed)



Quaid-i-Azam University Islamabad, 45320, Pakistan.
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