Refereed Papers

  • Ben-Gal, I., & Singer, G. (2004). Statistical process control via context modeling of finite-state processes: An application to production monitoring. IIE Transactions, 36(5): 401-415.
  • Singer G., & Ben-Gal I. (2007). The funnel experiment: The Markov-based SPC Approach. Quality and Reliability Engineering, 23(8): 899-913.
  • Singer G., & Khmelnitsky E. (2007). Optimal control of a stochastic system: State-costate analysis. The IASTED Int'l. Conf. Modelling, Identification, and Control (MIC 2007). Innsbruck, Austria.
  • Khmelnitsky E., & Singer G. (2009). A stochastic inventory control problem with reputation-dependent demand. Proc. 13th IFAC Sym. on Information Control Problems in Manufacturing. Moscow, Russia., 3-5 June 2009.
  • Singer G., & Khmelnitsky E. (2010). A finite-horizon, stochastic optimal control policy for a production-inventory system with backlog-dependent lost sales. IIE Transactions, 42(12): 855-864.
  • Apartsin Y., Maymon Y., Cohen Y., & Singer G. (2013). Nationality and risk attitude: Testing differences and similarities of investors' behavior in selected financial markets. Global Finance Journal, 24(2): 114-118.
  • Singer G., Golan M., & Cohen, Y. (2014). From product documentation to a 'method prototype' and standard times: A new technique for complex manual assembly. International journal of Production Research, 52(2): 507-520.
  • Ben-Gal I., Dana A., Shkolnik N., & Singer G. (2014). Efficient construction of decision trees by the dual information distance method. Quality Technology & Quantitative Management, 11(1): 133-147.
  • Khmelnitsky E., & Singer, G. (2015). An optimal inventory management problem with reputation-dependent demand. Annals of Operations Research, 231(1): 305-316.
  • Ben-Gal H., I., Pessach D., Avrahami D., & Singer G. (2018). Addressing the growing complexity of global work through human resources analytics: Hidden patterns in turnover. The 34th European Group for Organizational Studies (EGOS) Colloquium. Tallinn, Estonia.
  • Cohen Y., Golan M., Singer G., & Maurizio F. (2018). Workstation–Operator interaction in 4.0 Era: WOI 4.0. Proc. 16th IFAC (Int'l. Federation of Automatic Control) Sym. on Information Control Problems in Manufacturing. Bergamo, Italy.
  • Ben-Gal I., Weinstock S., Singer G., & Bambos N. (2019). Clustering users by their mobility behavioral patterns. ACM Transactions on Knowledge Discovery from Data, 13(4), 45
  • Rabin N., Golan M., Singer G., & Kleper D. (2019). Modeling and Analysis of Students’ Performance Trajectories using Diffusion Maps and Kernel Two-Sample Tests. Engineering Applications of Artificial Intelligence, 85: 492-503.
  • Singer, G., & Golan, M. (2019). Identification of subgroups of terror attacks with shared characteristics for the purpose of preventing mass-casualty attacks: a data-mining approach. Crime Science, 8(1), 14.
  • Singer G., Golan M., Rabin N., & Kleper D. (2020). Evaluation of the effect of learning disabilities and accommodations on the prediction of the stability of academic behavior of undergraduate engineering students using decision trees. European Journal of Engineering Education, 45(4), 614-630.
  • Golan, M., Cohen, Y., & Singer, G. (2020). A Framework for Operator - Workstation Interaction in Industry 4.0. International Journal of Production Research, 58(8), 2421-2432.
  • Singer, G., Anuar, R., & Ben-Gal, I. (2020). A Weighted Information-Gain Measure for Ordinal Classification Trees. Expert Systems with Applications, 152, DOI: 10.1016/j.eswa.2020.113375.
  • Golan, M., Singer, G., Rabin, N., & Kleper D. (2020). Integrating actual time usage into assessment of examination provided to disabled college engineering students. Assessment & Evaluation in Higher Education, DOI: 10.1080/02602938.2020.1717434.
  • Pessach, D., Singer, G., Avrahami, D., Chalutz Ben-Gal, H., Shmueli, E., & Ben-Gal I. (2020). Employees recruitment: A prescriptive analytics approach via machine learning and mathematical programming. Decision Support Systems, 134, DOI: 10.1016/j.dss.2020.113290.
  • Singer, G., & Cohen, I. (2020). An Objective-Based Entropy Approach for Interpretable Decision Tree Models in Support of Human Resource Management : The Case of Absenteeism am Work. Entropy, 22(8), 821. DOI: 10.3390/e22080821.
  • Singer, G. & Marudi, M. (2020). Ordinal Decision-Tree-Based Ensemble Approaches: The Case of Controlling the Daily Local Growth Rate of the COVID-19 Epidemic. Entropy, 22, 871.
  • Singer, G., & Khmelnitsky E. (2021). A production-inventory problem with price-sensitive demand. Applied Mathematical Modelling, 89(1), 688-699.
  • Singer, G., & Golan, M. (2021).  Applying data mining algorithms to encourage mental health disclosure in the workplace. International Journal of Business Information Systems, 36(4), 553-571.
  • Singer, G., Ratnovsky A., & Nafali S. (2021). Classification of severity of trachea stenosis from EEG signals using ordinal decision-tree based algorithms and ensemble-based ordinal and non-ordinal algorithms. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2021.114707.
  • Cohen, Y., & Singer, G. (2021). A Smart Process Controller Framework for Industry 4.0 Settings. Journal of Intelligent Manufacturing. https://doi.org/10.1007/s10845-021-01748-5.
  • Singer G., Cohen, Y. (2021). A framework for smart control using machine-learning modeling for processes with closed-loop control in Industry 4.0. Engineering Applications of Artificial Intelligence. https://doi.org/10.1016/j.engappai.2021.104236.
  • Chalutz Ben-Gal, H., Avrahami, D., Singer G., Pessach D., & Ben-Gal., I. (2021).  Examination of Turnover : HR Analytics Perspective.  The European Academy of Management Online Conference.
  • Chalutz Ben-Gal, H., Avrahami, D., Singer G., Pessach D., & Ben-Gal., I. (2021). Artificial Intelligence at Work: Examination of Turnover: HR Analytics Prespective. The 37th EGOS Online Colloquium: European Group for Organizational Studies.
  • Chalutz Ben-Gal, H., Avrahami, D., Pessach D. & Singer G. (2021). A Machine Learning Examination of Turnover: Hidden Patterns and New Insights. The Virtual 81st Annual Meeting of the Academy of Management. Best Paper.
  • Chalutz Ben-Gal H., Forma I., & Singer G. (2022). A flexible employee recruitment and compensation model: A bi-level optimization approach. In press: Computers & Industrial Engineering.
  • Avrahami, D., Pessach, D., Singer, G., & Chalutz Ben-Gal H. (2022). A human resources analytics and machine-learning examination of turnover: implications for theory and practice. In press: International Journal of Manpower.
  • Marudi, M., Ben-Gal, I., & Singer, G. (2022). A Decision-Tree-Based Method for Ordinal Classification Problems. In Press: IISE Transactions.
  • Singer, G., Golan, M., Shiff, R., & Kleper, D. (2022). Evaluating the Effectiveness of Accommodations Given to Students with Learning Impairments: Ordinal and Interpretable Machine Learning-Based Methodology.  In press:  IEEE Transactions on Learning Technologies.
  • Rabin, N., Singer, G., Friedman, S., Hedvat, O., & Ben-Mayor C. (2022). Graph-based Extreme Feature Selection for Multi-class Classification Tasks. INFORMS Workshop on Data Science.  Indianapolis, Indiana, USA.
  • Abukasis Shifman, D., Cohen, I., Huang, K., Xiaochen, X., & Singer G. (2023). An adaptive machine learning algorithm for the resource-constrained classification problem. Engineering Applications of Artificial Intelligence.
  • Haba, R., Singer, G., Naftali, S., Kramer R., M., & Ratnovsky, A. (2023). A remote and personalised novel approach for monitoring asthma severity levels from EEG signals utilizing classification algorithms. Expert Systems with Applications.
  • Volk, O., Ratnovsky, A., Naftali, S., & Singer, G. (2023). Classification of Tracheal Stenosis with Asymmetric Misclassification Errors from EMG Signals Using an Adaptive Cost-Sensitive Learning Method. Biomedical Signal Processing and Control.
  • Khmelnitsky, E., & Singer, G. (2023). Optimal Real Estate Pricing and Offer Acceptance Strategy. IEEE Access.
  • ‏Volk, O., & Singer, G. (2024). An adaptive cost-sensitive learning approach in neural networks to minimize local training–test class distributions mismatch. Intelligent Systems with Applications, 200316.‏

Book Chapters

  • Khmelnitsky E., & Singer G. (2005). A stochastic optimal control policy for a manufacturing system on a finite time horizon. Optimal Control and Dynamic Games: Applications in Finance, Management Science and Economics. Christophe Deissenberg, Richard F. Hartl (Eds.). Part of the Advances in Computational Management Science Book Series (AICM), 7: 275-288. [ISBN: 978-0-387-25804-1]
  • Cohen Y., Singer G., Golan M., & Goren-Bar D. (2013). Automating the transformation from a prototype to a method of assembly. Innovations and Advances in Computer, Information, Systems Sciences, and Engineering Part I, Khaled Elleithy, Tarek Sobh (Eds.). Lecture Notes in Electrical Engineering, 152: 99-106. Springer, New York, NY. [ISBN: 978-1-4614-3534-1]

Oral presentation at scientific Conferences

  • Singer G., & Ben-Gal I. (2000). An information theoretic approach to statistical process control of autocorrelated data. Industrial Engineering and Management Conf. Israel.
  • Ben-Gal  I., & Singer G. (2001). A methodology for integrating engineering process control and statistical process control. The 16th Int'l. Conf. on Production Research (ICPR-16). Prague, Czech Republic.
  • Singer G., & Khmelnitsky E. (2006). Time-dependent hedging policies for optimal production control under reputation dependent demand. The Annual ORSIS (Operation Research Society of Israel) Conf. Nahariya, Israel.
  • Halevi, R. Atzmoni, A. Bar-Moshe S., Cohen I., Ben-Nun M., Kaplan N., Ishbir C. & Singer G. (2007). Using predictive maintenance concepts for structure integrity in the IAF. US Air Force – The Aircraft Structural Integrity Program (USAF ASIP) Conf. Palm Springs, California, USA.
  • Khmelnitsky E., & Singer G. (2008). An inventory management model with reputation-dependent demand. INFORMS Annual Meeting. Washington D.C., USA.
  • Singer G., & Ben-Gal I. (2008). The funnel experiment: A Markov-based SPC approach. Industrial Engineering and Management Conf. Israel.
  • Kaplan N., Singer G., & Cohen I. (2008). Using business intelligence system for implementation of the maintenance concept in the Israeli Air Force. Industrial Engineering and Management Conf. Israel.
  • Kedem D., Singer G., & Sabbah G. (2008). Using the SPC method to define and monitor the cycle time in an IAF factory for improvement of aircraft availability.        Industrial Engineering and Management Conf. Israel.
  • Almozlinos B., Khmelnitsky E., & Singer G. (2009). Optimal stopping problem: Dynamic pricing of an asset. The Annual ORSIS (Operation Research Society of Israel) Conf. Herzliya.
  • Ben-Gal I., &, Singer G. Classification of defectives products via a pattern-based model. INFORMS Annual Meeting. San Diego, California, USA.
  • Khmelnitsky E., & Singer G. (2010). A stochastic optimal control policy for a production-inventory system with lost sales. The 8th Int'l. Conf. on Optimization: Techniques and Applications. Shanghai, China, December 2010
  • Kedem D., Ben-Gal I., & Singer G. (2010). Automatic fault identification in the presence of noise via rough set theory and error correcting codes. Industrial Engineering and Management Conf. Israel.
  • Singer G, Ben-Gal I., & Anuar R. (2010). Automatic fault identification via variable-order Bayesian networks Industrial Engineering and Management Conf. Israel.
  • Ben-Gal I., Kedem D., & Singer G. (2011). Sensoring design via rough set theory and error correcting codes. European Network for Business and Industrial Statistics and DEsign of INDustrial Experiments. Torino, Italy.
  • Ben-Gal I., & Singer G. (2011). Demand sensing via C-B4 pattern analysis and SAS® forecast server. Proc. SAS Global Forum. Las Vegas, Nevada, USA.
  • Cohen Y., Singer G., Golan M., & Goren-Bar D. (2011). Automating the transformation from a prototype to a method of assembly. Int'l. Conf. on Industrial Electronics, Technology and Automation (IETA 11).
  • Khmelnitsky E., & Singer G. (2012). Dynamic pricing of an asset in an unstable market. Industrial Engineering and Management Conf.  Israel.
  • Golan M. Singer G., & Goren-Bar D. (2012). Using manual assembly instructions to generate standard times. Industrial Engineering and Management Conf. Israel.
  • Maymon Y., Singer G., & Apartsin Y. (2012). Nationality and attitude toward risk: A quantitative study using machine learning techniques and historical stock prices. Industrial Engineering and Management Conf. Israel.
  • Cohen Y., Singer G., Golan M., &  Goren-Bar D. (2012). Using assembly instructions for generating standard times and automation requirements. Int'l. Conf. on Flexible Automation and Manufacturing (FAIM). Stockholm, Sweden.
  • Singer G., Golan M., Kleper D., Kedar S., &  Rabin N. (2014). Using data mining algorithms to evaluate the effectiveness of adjustments given to engineering and science students with learning disabilities. Industrial Engineering and Management Conf. Israel.
  • Chalutz H., & Singer G. (2014). Some thoughts on human resources analytics. INFORMS Annual Meeting.          San Francisco, USA.
  • Golan M., Rabin N., Singer G, & Kleper D. (2015). The effectiveness of extended time in tests provided to students with learning disabilities.     The 14th European Congress of Psychology. Milan, Italy.
  • Singer G. (2016). Predictive maintenance using machine learning techniques. 5th PHM Israel Conf. Tel-Aviv, Israel.
  • Pessach D., Singer G., Avrahami D. Ben-Gal I., & Ben-Gal H. (2017). A two-step method for a granular job placement optimization. Industrial Engineering and Management Conf. Israel.
  • Pesach D., Singer G., Avrahami D., Ben-Gal H., Shmueli E., & Ben-Gal I. (2019). Using Machine Learning for Employees’ Recruitment & Placement. Industrial Engineering and Management Conf. Israel.
  • Cohen Y., & Singer G., (2020). Industry 4.0 Methodological Framework for Process Control and Maintenance with Embedded AI. The 9th Israeli Industrial Engineering and Management Research Conf., Israel.
  • Marudi M., & Singer G., (2020). Affecting factors on local Cov19 pandemic growth rates via new ordinal decision-tree based algorithms. INFORMS Annual Meeting. Digital meeting via ZOOM.
  • Singer G., & Golan M., (2020). Evaluation of the effect of including parameters related to learning disabilities and extended exam time on the prediction of the exam performance of undergraduate engineering students: Ordinal decision-tree based algorithms. International Conference on Educational Data Mining. Digital meeting via ZOOM.
  • Golan M., & Singer G., (2020). Multi-dimensional evaluation of academic performance using Ensemble learning approach based on ordinal algorithms. International Conference on Educational Data Mining. Digital meeting via ZOOM.
  • Khmelnitsky E., & Singer G., (2021). An optimal policy for a production control problem with uncertain price-sensitive demand. In the POMS 31st Annual Conference.
  • Rabkin L., Cohen Reuven I., & Singer G., (2021). An analytic approach for classification problems with resource constraints via cost-sensitive learning and mathematical programming. Industrial Engineering and Management Conf. Israel.
  • Forma I., Chalutz Ben-Gal H., & Singer G., (2021). An employee recruitment and compensation model for the post COVID-19: A bi-level optimization approach. Industrial Engineering and Management Conf. Israel.
  • Haba R., Ratnovsky A. Naftali S., & Singer G., (2021). A non-invasive and remote personalized monitoring approach for asthma disease using EEG and ordinal algorithms. Industrial Engineering and Management Conf. Israel.
  • Haba R., Ratnovsky A, Naftali S., Kremer M., & Singer G., (2021). A remote and personalized approach for monitoring Asthma severity level from EEG signals utilizing novel classification algorithms. Israeli Association for Medical Informatics. Israel.
  • Forma I., Chalutz Ben-Gal H., & Singer G., (2022). Flexible employee recruitment and retention models via flexible work plans: A bi-level optimization approach. 32nd European Conference on Operational Research (EURO 2022). Espoo, Finland.
  • Ratnovsky A., Haba R., Singer G., Kramer M.,  & Naftali S., (2022). Asthma severity levels monitoring based on EEG signals using novel classification algorithms. 27th Congress of the European Society of Biomechanics. Porto, Portugal.
  • Singer G., & Volk O., (2022). Adaptive Cost-Sensitive Approach in Neural Networks for Medical Applications. INFORMS Annual Meeting. Indianapolis, Indiana, USA.
  • Forma I., Singer I., Bukchin Y., & Singer G., (2023). Hila Chalutz Ben-Gal A flexible work arrangement for employee: A bi-level optimization approach. Industrial Engineering and Management Conf. Israel.
  • Volk O, & Singer G., (2023). Adaptive cost-sensitive learning approach in neural networks to minimize local training-test class distribution mismatch. Industrial Engineering and Management Conf. Israel.
  • Abukasis Shifman D., Cohen, I., Huang, K., Xian, X., & Singer G., (2023). An adaptive machine learning algorithm for the resource-constrained classification problem. Industrial Engineering and Management Conf. Israel.

Patents

  • Ben-Gal I., Shmilovici A., Morag G, & Singer G. Stochastic modeling of spatial distributed sequences. Int'l. Publication No. WO 02/067075 A3, Int'l. Publication Date: 29 August 2002
  • Ben-Gal I. Shmilovici A., Morag G., & Singer G. Stochastic modeling of time distributed sequences.  Publication No. US 2003/0061015 A1, Publication Date: 27 March 2003.
  • Anuar A., Singer G., & Cohen N.L. System, method and computer program product for data analysis Publication No. WO/2017/168410, Publication Date: 5 October 2017
  • Singer G., & Anuar R. A risk-based weighted information-gain measure for ordinal classification decision-trees  US Provisional Patent Application No.62/784,856, 26 December 2018.
  • Singer G. Adaptive cost-sensitive learning in neural networks for misclassification cost problems US Provisional Patent Application No.63/157,829, 8 March 2021.