Hany Osman

Hany Osman has academic and industrial experiences in the areas of data analytics, machine learning, optimization, and operations management.   

He earned his PhD degree in Industrial Engineering from Concordia University, Montreal, QC. Hany has been involved in developing and teaching courses related to data mining, machine learning, predictive analytics, operations research, engineering statistics, engineering economics, and industrial costing. Hany has several publications focused on both theory and application of operations research, data mining, machine learning techniques, manufacturing systems, and supply chain optimization. 

He has diverse industrial experience in different sectors. He developed optimization and predictive models in supply chain logistics, oil industry, and online education support systems. 

He holds the IBM-Mastery Certificate in Predictive Data Analytics. He also holds the professional engineering, PEng, license from Ontario.

Programs/Courses taught

Operations Analytics, Prescriptive Analytics, Advanced Data Analytics, SQL Databases, Time Series Analysis, Machine Learning, Engineering Economics, Discrete Event Simulation, Industrial Cost Accounting

Areas of academic interest

• Data mining
• Machine learning
• Operations research
• Operations management

Areas of specialization

Predictive analytics techniques, machine learning, optimization, nature-inspired metaheuristics, supply chain management, production planning, and inventory control 

Awards

• ENCS Partial Tuition Fee Remission. Concordia University, Fall 2006 – Summer 2010
• Concordia International Fee Remission, Concordia University, Fall 2007 – Summer 2009

Professional certificates and licenses

• PEng. – Professional Engineer Licensee, Ontario
• IBM – Mastery Certificate in Predictive Data Analytics (August 2017)
• Pearson Education – Mastery Badge in Predictive Data Analytics (August 2017)
• AWS Academy Educator (September 2025)

Publications

• Editorial affiliation Guest Editor, Special Issue on Digital and Intelligent Technologies for Analytics and Optimization in Industrial Systems Engineering, Systems. Q1 journal; Impact Factor: 3.1; CiteScore: 4.1. 2025-2026

Articles published in international journals

• Osman. H, Azab. A, Baki. M.F, Alghazy. A, Duffaa. S. Forecasting Electric Vehicle Charging Loads Using Random Forest and Gene Expression Programming Ensemble Models. Results in Engineering. Volume 28, 2025, 108369 
• Osman. H, Azab. A, Bin Hasan. R, Baki. MF. Computer-Aided Process Planning Group Technology and Delayed Product Differentiation for Hybrid Manufacturing using a Hybridized Machine Learning and Optimization Approach. Annals of Operations Research (2025). https://doi.org/10.1007/s10479-025-06884-2 
• Osman. H, Azab. A, Baki. MF. Gadalla. M. 2025. Stock design in hybrid manufacturing using a constrained clustering approach. Manufacturing letters. Volume 44, Pages 253-260.   
• Alrahi. A, Osman. H, Azab. A, Bin Hasan. R, Baki. MF. 2025. Integrated Product-Platform Design and Multi-Period Lot-Sizing for Hybrid Manufacturing with Fuzzy Demand and Variant Substitution. Manufacturing letters. Volume 44, Pages 243-252 
• Osman. H, Cost Sensitive Learning using Logical Analysis of Data. 2024. Knowledge and Information Systems. Volume 66, pages 3571–3606. 
• Azab. A, Osman. H, Baki. MF. 2024. CAPP-GPT: A Computer-Aided Process Planning-Generative Pretrained Transformer Framework for Smart Manufacturing. Manufacturing Letters. Volume 41, Supplement, Pages 51-62  
• Osman. H, Azab. A, Bin Hasan. R, Baki. MF. 2024. Mass Customization using hybrid manufacturing and smart assembly: An Optimal Configuration and Platform Design Approach. Manufacturing letters. Volume 41, Supplement, Pages 124-132 
• Mousa. M, Osman. H, Azab. A, Baki. MF. 2024. Characterization of Laser Cladding Functional Coatings: An In-situ Monitoring and Variability Analysis Approach. International Journal of Advanced Manufacturing Technology. Volume 133, pages 1155–1183 
• Osman. H, Azab. A, Baki, M.F. 2023. Optimal Process Planning for Hybrid Additive and Subtractive Manufacturing. J. Manuf. Sci. Eng. 45(6), 061013 
• Hasan, R.B, Osman, H., Azab, A., Baki, M.F. 2023. Improvement to an existing multi-level capacitated lot sizing problem considering setup carryover, backlogging, and emission control. Manufacturing Letters. Volume 35, Supplement, Pages 28-39.  
• Sakib, M.D., Osman, H., Azab, A., Baki, M.F. 2023. Product-platform design and multi-period, multi-platform lot-sizing for hybrid manufacturing considering stochastic demand and processing time. Manufacturing Letters. Volume 35, Supplement, Pages 20-27.  
• Osman, H., & Yacout, S., 2022. Condition-based monitoring of the rail wheel using logical analysis of data and ant colony optimization. Journal of Quality in Maintenance Engineering, Vol. 29 No. 2, pp. 377-400.  
• Osman, H., Ali, A., Mahmoud, A. A., and Elkatatny, S., 2021. Estimation of the Rate of Penetration While Horizontally Drilling Carbonate Formation Using Random Forest. ASME. J. Energy Resour. Technol. 143(9): 093003. https://doi.org/10.1115/1.4050778 
• Elfar, O., Yacout, S., Osman, H., 2021. Accelerating Logical Analysis of Data Using an Ensemble-Based Technique. Eng. Lett. 29, 1616–1625.  
• Elfar, O., Yacout, S., Osman, H., 2019. Merging Logical Analysis of Data Models. International Journal of Industrial Engineering and Operations Management Inc.; Emerald Publishing: Bingley, UK; pp. 183–194.  
• Osman, H., Baki, M., F., 2018. A cuckoo search algorithm to solve transfer line balancing problems with different cutting conditions. IEEE Transactions in Engineering Management. 65(3). 505 - 518  
• Ragab, A., Ouali, M.-S., Yacout, S., Osman, H. 2017. Pattern-based prognostic methodology for condition-based maintenance using selected and weighted survival curves. Quality and Reliability Engineering International. DOI: 10.1002/qre.2127 
• Ragab, A., Ouali, M.-S., Yacout, S., Osman, H. 2016. Prognostics of Multiple Failure Modes in Rotating Machinery Using a Pattern-Based Classifier and Cumulative Incidence Functions. Journal of Intelligent Manufacturing. DOI: 10.1007/s10845-016-1244-8. 
• Ragab, A., Ouali, M.-S., Yacout, S., Osman, H. 2016. Remaining useful life prediction using prognostic methodology based on logical analysis of data and Kaplan–Meier estimation. Journal of Intelligent Manufacturing. 27(5), 943–958 
• Osman, H., Baki, M., F., 2014. Balancing transfer lines using Benders decomposition and ant colony optimization techniques. International Journal of Production Research. 52(5), 1334-1350. 
• Osman, H.,  Baki , M. F. 2013.  A linearization and decomposition based approach to minimize the non-productive time in transfer lines. World Academy of Science, Engineering and Technology 74, 440-445. 
• Osman, H., Demirli, K., 2012. Economic lot and delivery scheduling problem for multi-stage supply chains. International Journal of Production Economics. 136(2), 275–286.  
• Osman, H., Demirli, K., 2012. Integrated safety stock optimization for multiple sourced stockpoints facing variable demand and lead time. International Journal of Production Economics. 135(1), 299-307. 
• Osman, H., Demirli, K., 2010. A bilinear goal programming model and a modified Benders decomposition algorithm for supply chain reconfiguration and supplier selection. International Journal of Production Economics, 124, 97–105. 

Articles published in international conferences

• Hany Osman. 2021. Generating maximum prime patterns using Benders decomposition and Apriori algorithm. Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management Singapore, March 7-11, 2021  
• Ragab, A., Ouali, M.-S., Yacout, S., & Osman, H. 2015. Multiple Failure Modes Prognostics Using Logical Analysis of Data, RAMS 2015, Florida, USA. 
• Ragab, A., Ouali, M.S., Yacout, S., & Osman, H. 2014. Condition-Based Maintenance Prognostics Using Logical Analysis of Data, ISERC 2014, May 31 to June 4, 2014, Montreal, Canada. 
• Ibrahim, S., Khater, M., Osman, H., 2005. A knowledge-based system to schedule multi- skilled labor with variable demand. Proceeding of IPROMS, 351-356, Cardiff University, U.K. 
• Ibrahim, S., Khater, M., Osman, H., 2005. Application of manpower scheduling in manufacturing processes. Al-Azhar University Engineering Journal, Egypt. 8 (2), 24-34. 
• Ibrahim, S., Elawady, H., Elgohary, G., Osman, H., 2003. Simulation of cellular manufacturing systems" Proceeding of the 7th Conference on Theoretical & Applied Mechanics, Academy of Scientific Research & Technology, Egypt, 150-162.