Ali Yeganeh

Contact Information-&-https://www.researchgate.net/profile/Ali-Yeganeh-5 https://scholar.google.com/citations?user=yjtmk20AAAAJ&hl=en https://orcid.org/- Ali Yeganeh (DOB: 1991-7-5) - PhD Graduated, Ferdowsi University of Mashhad, Department of Industrial Engineering, Mashhad, Iran. Education: Industrial Engineering, Ferdowsi University of Mashhad, Department of Industrial Engineering, Mashhad, Iran. Ph.D Dissertation: Combination of machine learning techniques and- MSc- BSc. run-rules in profile monitoring (In Persian). Civil Engineering, Construction Management, Ferdowsi University of Mashhad, Department of Civil Engineering, Mashhad, Iran. Dissertation: Using fuzzy FMEA technique in in LSF structure risk management run-rules in profile monitoring (In Persian). Civil Engineering, Ferdowsi University of Mashhad, Department of Civil Engineering, Mashhad, Iran. - Research Interests: Artificial Intelligence Artificial Neural Network Data Mining Deep learning Evolutionary Algorithms Health-care applications Operation Research Process Monitoring Statistical Process Control Work Experience:- Arya Sazeh Company Construction manager in LSF buildings projects and dry-wall systems Teaching Experience: ➢ Teaching assistant (TA) at Ferdowsi University of Mashhad Fall 2010 Teaching Assistant, Structure Analysis I Spring 2011 Teaching Assistant, Structure Analysis II Spring 2018 Statistical Quality Control Fall 2019 Data mining Spring 2019 Regression analysis Spring 2020 Design of Experiment Spring 2021 Design of Experiment ➢ Teaching at Ferdowsi University of Mashhad Fall 2019 Statistics ➢ Teaching software courses at Ferdowsi University of Mashhad Fall 2017 Lisrel Fall 2019 R studio Spring 2020 Matlab Level Bachelor Bachelor Bachelor Master Master Master Master Bachelor Master Master Master Research Experience: 2017-Present Ferdowsi University of Mashhad - Ferdowsi University of Mashhad Process monitoring, neural network, Machine learning, Time series prediction, Regression. analysis, Statistical process control Fuzzy theory, Risk management. Programming Skills: Matlab ➢ 4 years during PhD study (Expert). R ➢ 4 years during PhD study (Expert). Python ➢ 1 years for deep learning (Proficient). Design Expert ➢ 4 years during PhD study (Expert). Lisrel ➢ 2 years during PhD study (Expert). Awards and Honors: 2007 Graduated as the first rank student in high school among 130 students (Average of scores = 19.50 form 20 or GPA = 4 ). Ranked 748th (top 1%) among more than 300,000 students participating in the nationwide undergraduate entrance exam, Iran Graduate as a first rank student among 120 students in Bachelor (Average of scores = 17.20 form 20 or GPA = 3.52). Acceptance in master without entrance exam as an elite student. Graduated as the second rank student in MSc among 10 students (Average of scores = 17.88 form 20 or GPA = 3.70). Acceptance in PhD without entrance exam as an elite student. Graduated as the first rank student in PhD among 5 students (Average of scores = 19.22 form 20 or GPA = 4). Acceptance as an elite person for military project in IRAN Selection as the top researcher in Faculty of Engineering in Ferdowsi University of Mashhad Graduated from PhD in industrial engineering with the top rank - Publications: ➢ Journals: A. Yeganeh, A. Shadman, Monitoring linear profiles using Artificial Neural Networks with run rules, Expert Systems with Applications, 168 -, https://doi.org/10.1016/j.eswa-, (IF = 6.954). J2 A. Yeganeh, A.R. Shadman, I.S. Triantafyllou, S.C. Shongwe, S.A. Abbasi, Run Rules-Based EWMA Charts for Efficient Monitoring of Profile Parameters, IEEE Access, 9 -, 10.1109/ACCESS-, (IF = 3.367). J1 J3 A. Yeganeh, A. Shadman, A. Amiri, A novel run rules based MEWMA scheme for monitoring general linear profiles, Computers & Industrial Engineering, 152 -, https://doi.org/10.1016/j.cie-, (IF = 5.431). J4 Mohammadzadeh, M., A. Yeganeh, and A. Shadman, Monitoring logistic profiles using variable sample interval approach. Computers & Industrial Engineering,-: p. 107438, https://doi.org/10.1016/j.cie-, (IF = 5.431). J5 A. Yeganeh, F. Pourpanah, A. Shadman, An ANN-based ensemble model for change point estimation in control charts, Applied Soft Computing, 110 -, https://doi.org/10.1016/j.asoc-, (IF = 6.725). J6 A. Yeganeh, M. Younesi Heravi, B. Razavian, K. Behzadian, H. Shariatmadar. Applying a New Systematic Fuzzy FMEA Technique for Risk Management in Light Steel Frame Systems. Journal of Asian Architecture and Building Engineering, https://doi.org/10.1080/-, (IF = 0.692). J7 A. Yeganeh, S.A. Abbasi, S.C. Shongwe. A novel simulation-based adaptive MEWMA approach for monitoring linear and logistic profiles, IEEE Access, https://doi.org/10.1109/ACCESS-, (IF = 3.367). J8 A. Yeganeh, A. Shadman. Using Evolutionary Artificial Neural Networks in Monitoring Binary and Polytomous Logistic Profiles. Journal of Manufacturing Systems. https://doi.org/10.1016/j.jmsy-, (IF = 8.633). J9 A. Yeganeh, A. Shadman, S. A. Abbasi. Enhancing the detection ability of control charts in profile monitoring by adding RBF ensemble model. Neural Computing and Applications, (IF = 5.606) ➢ Pre-prints & under review manuscripts: P1 A. Yeganeh, S. A. Abbasi, N. A. Adegoke. Improving the detection ability of binary CUSUM Risk-adjusted control charts with run-rules. (Applied Soft Computing (submitted)). P2 A. Yeganeh, A. Shadman, S. A. Abbasi. Employing Evolutionary artificial neural network in Risk-adjusted monitoring of surgical performance. Neural Computing and Applications (Manuscript ID: NCAA-D- (under first revise)). P3 A. Yeganeh, S.A. Abbasi, S.C. Shongwe. A novel simulation-based adaptive EWMA approach for monitoring non-parametric profiles. Quality and Reliability Engineering International (Manuscript ID: QRE-21-0574 (under first revise)). A. Yeganeh, S. A. Abbasi, S. C. Shongwe, J. Malela-Majika, A. Shadman. Evolutionary support vector regression for monitoring Poisson profiles. Soft Computing (Manuscript ID: SOCO-D- (under review)). A. Yeganeh, S. A. Abbasi, F. Pourpanah, A. R. Shadman, A. Johannssen, N. Chukhrova. An ensemble neural network framework for improving the detection ability of a base control chart in non-parametric profile monitoring. Expert Systems with Applications (Manuscript ID: ESWA-D- (under first revise)). A. Yeganeh, A. Johannssen, N. Chukhrova, S. A. Abbasi. Employing machine learning techniques in monitoring auto-correlated profiles. Journal of Manufacturing Systems (Manuscript ID: SMEJMS-D- (under review)). P4 P5 P6 ➢ Book chapter: B1 M. Younesi Heravi, A. Yeganeh, B. Razavian, Using Fuzzy Approach in Determining Critical Parameters for Optimum Safety Functions in Mega Projects (Case Study: Iran’s Construction Industry), (2022) In: Khosravy M., Gupta N., Patel N. (eds) Frontiers in Nature-Inspired Industrial Optimization. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/-_10. Languages: English (writing: fluent, speaking and listening: Conversational) References: ➢ Dr. Alireza Shadman (Ph.D. Supervisor) Persian (mother tongue) Ferdowsi University of Mashhad, Mashhad, Iran, Department of Industrial Engineering-. ➢ Prof. Dr. Saddam Akber Abbasi (Ph.D. advisor I) Qatar University, Qatar, Department of Mathematics, Statistics & Physics-. ➢ Dr. Farhad Pourpanah (Ph.D. advisor II) Department of Electrical and Computer Engineering, University of Windsor, Windsor, Canada-.