Alireza Sheikh-Zadeh, Ph.D. Assistant Professor of Practice in Data Science Rawls College of Business, Texas Tech University Area of Information Systems and Quantitative Sciences (ISQS) 703 Flint Ave, Lubbock, TX 79409 (806) 834-8569, [email protected] EDUCATION Ph.D. in Industrial Engineering, 2017 Industrial Engineering Department at the University of Arkansas, Fayetteville, AR Dissertation: “Developing New Inventory Segmentation Methods for Large-Scale Multi-Echelon In- ventory Systems” (Advisor: Manuel D. Rossetti) M.Sc. in Industrial Engineering (with concentration in Systems Management), 2008 Industrial Engineering & Systems Management Department at Tehran Polytechnic, Tehran, Iran Thesis: “System Dynamics Modeling for Study and Design of Science and Technology Parks for The Development of Deprived Regions” (Advisor: Reza Ramazani) AREA of INTEREST Data Science & Machine Learning Supply Chain Analytics Applied Operations Research System Dynamics Simulation and Stochastic Modeling Logistic Contracting PUBLICATIONS Journal Papers (including under review papers) • Sheikhzadeh, A., & Farhangi, H., & Rossetti, M. D. (under review), ”Inventory Grouping and Sensitivity Analysis in Large-Scale Spare Part Systems”, submitted work. • Sheikhzadeh, A., Rossetti, M. D., & Scott, M. (2nd review), ”Clustering, Aggregation, and Size-Reduction for Large-Scale Multi-Echelon Spare-Part Replenishment Systems,” Omega: The International Journal of Management Science. • Sheikhzadeh, A., & Rossetti, M. D. (4th review), ”Classification Methods for Problem Size Reduction in Spare Part Provisioning,” International Journal of Production Economics. • Al-Rifai, M. H., Rossetti, M. D., & Sheikhzadeh, A. (2016), ”A Heuristic Optimization Algorithm for Two- Echelon (r; Q) Inventory Systems with Non-Identical Retailers,” International Journal of Inventory Re- search. • Karimi-Nasab, M., Bahalke, U., Feili, H. R., Sheikhzadeh, A., & Dolatkhahi, K. (2012). ”Working Time Evaluation in Assembly Lines,” International Journal of Mathematics in Operational Research, 4(1), 1- 17. Peer Reviewed Conference Papers • Sheikhzadeh, A., & Rossetti, M. D. (2016, May), ”Inventory Segmentation Performance Improvement for Multi-Echelon Repairable Items Logistics Systems,” In Proceedings of the 2016 Industrial and Systems Engineering Research Conference (ISERC), Anaheim, CA, USA. • Sheikhzadeh, A., & Rossetti, M. D. (2015, May), ”Segmentation Methods for Large-Scale Multi-Echelon Service Parts Logistics Systems,” In Proceedings of the 2015 Industrial and Systems Engineering Research Conference (ISERC), Nashville, TN, USA. 1 of 6 • Sheikhzadeh, A., & Heidari, H. (2012, July), ”Operations Management Research: a 10-Year Survey,” In Proceedings of the 2012 International Conference on Industrial Engineering and Operations Manage- ment (IEOM), Istanbul, Turkey, 2472-2481. • Sheikhzadeh, A., & Heidari, H. (2011, December), ”Improving a Model for New Service Development,” In Proceedings of 2011 IEEE International Conference on Industrial Engineering and Engineering Man- agement (IEEM), Singapore, Singapore, 674-678. • Sheikhzadeh, A., Basiri, H. Salimi, M. H. (2007, June), ”Production Productivity Improvement with Target-Costing System and Value Engineering,” In Proceedings of 2nd International Conference on Pro- ductivity, Tehran, Iran, (In Farsi). Working Journal Papers • Davletshin, M., Sodero, A., Fugate, B., Johnson, J., Sheikhzadeh, A., ”Information Processing at the Human-Technology Interface: Microfoundations of Food Product Recall Efficacy,” Paper in Process • Sheikhzadeh, A., & Rossetti, M. D., ”Large-Scale Multi-Echelon Inventory Optimization Using Aggre- gation/Disaggregation”. • Farhangi, H., & Sheikhzadeh, A., ”Optimal Product Aggregation in Dynamic Lot-Sizing Problem”. CONFERENCE PRESENTATIONS • Sheikhzadeh, A., & Rossetti, M. D. (2018, May.), ”Segmentation and Aggregation Methods for Problem Size Reduction in Spare-Part Provisioning”, the 2018 POMS Annual Conference, Houston, TX, USA. • Sheikhzadeh, A., & Rossetti, M. D. (2017, May), ”Classification for Large-Scale Multi-Echelon Inventory Systems: A Performance-Based Solution”,The Industrial and Systems Engineering Research Conference (ISERC), Pittsburgh, PA, USA. • Sheikhzadeh, A., & Rossetti, M. D. (2016, Nov.), ”Inventory Classification Versus Statistical Clustering For Solving Multi-echelon Inventory Grouping Problem”, INFORMS Annual Meeting, Nashville, TN, USA. • Sheikhzadeh, A., & Rossetti, M. D. (2016, Nov.), ”Developing A Novel Inventory Classification Approach For Large Scale Multi Echelon Inventory Systems”,INFORMS Annual Meeting Poster Competition, Nashville, TN, USA. • Sheikhzadeh, A., & Rossetti, M. D. (2016, May), ”Inventory Segmentation Performance Improvement for Multi-Echelon Repairable Items Logistics Systems”, The Industrial and Systems Engineering Re- search Conference (ISERC), Anaheim, CA, USA. • Sheikhzadeh, A., & Rossetti, M. D. (2016, May), ”A Novel Inventory Classification Approach for Multi- Echelon Repairable Items Logistics Systems”, IIE Doctoral Colloquium Poster Competition, Anaheim, CA, USA. • Sheikhzadeh, A., & Rossetti, M. D. (2015, May), ”Segmentation Methods for Large-Scale Multi-Echelon Service Parts Logistics Systems”,The Industrial and Systems Engineering Research Conference (ISERC), Nashville, TN, USA. • Sheikhzadeh, A., & Rossetti, M. D. (2014, Nov.), ”Segmentation Methods for Large-Scale Multi-Echelon Service Parts Logistics Systems”, INFORMS Annual Meeting. San Francisco, CA, USA. • Sheikhzadeh, A., & Heidari, H. (2012, July), ”Operations Management Research: A 10-Year Survey”, The International Conference on Industrial Engineering and Operations Management (IEOM), Istan- bul, Turkey, 2472-2481. • Sheikhzadeh, A., & Heidari, H. (2011, December), ”Improving a Model for New Service Development”, IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Sin- gapore, Singapore, 674-678. • Sheikhzadeh, A., Basiri, H. Salimi, M. H. (2007, June), ”Production Productivity Improvement with Target-Costing System and Value Engineering”, In Proceedings of the 2nd International Conference on Productivity, Tehran, Iran, (In Farsi). 2 of 6 TEACHING M.Sc. Data Science (2017-present) TTU, Rawls College of Business Administration • ISQS 5347: Advanced Statistical Methods Applied simulation-based approach using R to learn statistical concepts in – probability modeling: empirical, joint, and conditional probability models, and paramet- ric distributions – statistical inferences: central limit theorem, confidence interval. and hypothesis tests in- cluding normal, t, chi-square, and F tests • ISQS 5346: Statistics for Data Science (including online section) Applied simulation-based approach using R to learn statistical concepts in – data organization – random variables, law of large numbers – probability modeling: empirical, joint, and conditional probability models, and paramet- ric distributions – statistical inferences: central limit theorem, confidence interval. and hypothesis tests in- cluding normal, t, chi-square, and F tests • ISQS 6350: Multivariate Analysis Applied approach using R to learn multivariate analysis techniques such as – multivariate data preparation and visualization – dimension reduction techniques including PCA, MDS, and EFA – cluster analysis such as hierarchical, k-means, and model-based clustering – factor analysis and SEM • ISQS 7339: Prescriptive Analytics: Simulation and Optimization Applied approach using R and Python including – optimization modeling such as LP,IP,and MILP – risk analysis via Monte-Carlo simulation – discrete event simulation – advanced sampling methods such as Markov chain Monte-Carlo Course Evaluation Course Objectives Effectiveness Learning Experience ISQS 5346 (Fa18) 4.7 4.7 4.7 ISQS 5346 (Fa18-online) 4.6 4.7 4.7 ISQS 7339 (Su18) 4.6 4.4 4.4 ISQS 6350 (Sp18) 4.5 3.9 4.1 ISQS 5347 (Fa17) 4.2 4.0 4.1 3 of 6 STEM MBA (2017-present) TTU, Rawls College of Business Administration • ISQS 5345: Statistical Concepts for Business and Management Applied approach using Microsoft Excel to perform – data organization and visualization – probability modeling: empirical, joint, and conditional probability models, and paramet- ric distributions – statistical inferences: central limit theorem, confidence interval. and hypothesis tests in- cluding normal, t, F tests, and ANOVA Course Evaluation Course Objectives Effectiveness Learning Experience ISQS 5345 (Fa18) 4.6 4.3 4.3 ISQS 5345 (Sp18) 4.8 4.8 4.6 ISQS 5345 (Fa17) 4.6 4.3 4.4 Dual MBA (2017-present) TTU, Rawls College of Business Administration • ISQS 5345: Statistical Concepts for Business and Management Course Evaluation Course Objectives Effectiveness Learning Experience ISQS 5345 (Su18) 4.2 4.0 4.1 ISQS 5345 (Fa17) 4.4 3.8 3.9 B.Sc. Industrial Engineering (2012-2017) University of Arkansas, College of Engineering • INEG 2313: Applied Probability and Statistics for Engineers I- Evaluation: 4.3/5 • INEG 4553: Production Planning and Control (Online Section)- As a TA • INEG 4904: Industrial Engineering Design- As a TA • INEG 4911: Industrial Engineering Capstone Experience I- As a TA • INEG 4923: Industrial Engineering Capstone Experience II- As a TA B.Sc. Information Technology (2008-2012) Hatef Institute of Higher Education (Iran) • Applied Probability and Statistics- Evaluation: (19.84/20) • E-Commerce- Evaluation: (19.55/20) • Organizational Behavior Management- Evaluation: (19.59/20) • Project Management- Evaluation: (19.08/20) • Scientific Documentation Methods- Evaluation: