Aram Bahrini

Teaching Assistant Professor and Deloitte Scholar

Contact

4036 A Business Instructional Facility

515 Gregory Dr

Champaign, IL 61820

Listings

Educational Background

Ph.D., Systems Engineering, University of Virginia, 2023
M.S., Mathematics, University of British Columbia, 2019
M.S., Industrial & Manufacturing Systems Engineering, Kansas State University, 2017

Positions Held

Assistant Professor of Business Administration, Business Administration, University of Illinois at Urbana-Champaign, 2023 to present
Lecturer, Systems Engineering, University of Virginia, 2022-2022
Teacher, AP-Statistics, Yes Institution, 2020-2023
Research Affiliate, Systems Engineering-Link Lab, University of Virginia, 2019-2023
2nd Lieutenant, Logistics Unit, Information Department, Army Ground Forces, 2012-2013
Consultant in Integrated Management System based on ISO9001, ISO14001, & ISO18001, Integrated Management System, Aryan Ravesh Firm, 2011-2014

Recent Publications

Martin, G., Yang, P., Bahrini, A., Bajpai, P., Benli?, K., Downey, J., Li, Y., Liang, X., Parvardi, A., Simpson, R., White, E., & Yip, C. (2025). An annotated bibliography for comparative prime number theory. Expositiones Mathematicae, Elsevier BV, 125644. link >
Abdoli, N., Bahrini, A., & Riggs, R. (2024). A novel approach for multi-objective truck scheduling problems in a cross-docking center. International Journal of System Assurance Engineering and Management, Springer Science and Business Media LLC, 15 (12), 5497-5527. link >
Abbasimehr, H., Behboodi, A., & Bahrini, A. (2024). A novel hybrid model to forecast seasonal and chaotic time series. Expert Systems with Applications, Elsevier, 239 122461. link >
Hossein, A., Paki, R., & Bahrini, A. (2023). A novel XGBoost-based featurization approach to forecast renewable energy consumption with deep learning models. Sustainable Computing: Informatics and Systems, Elsevier, 38 100863. link >
Torkayesh, A., Babaee Tirkolaee, E., Bahrini, A., Pamucar, D., & Khakbaz, A. (2023). A systematic literature review of MABAC method and applications: An outlook for sustainability and circularity. Informatica, IOS Press, 34 (2), 415-448. link >
Baglione, A., Lihua, C., Bahrini, A., Posey, I., Boukhechba, M., & Chow, P. (2022). Understanding the relationship between mood symptoms and mobile app engagement among patients with breast cancer using machine learning: Case study. JMIR Medical Informatics, JMIR Publications, 10 (6), e30712. link >

Other Publications

Articles

Abbasimehr, H., & Bahrini, A. (2021). An analytical framework based on the recency, frequency, and monetary model and time series clustering techniques for dynamic segmentation. Expert Systems with Applications, Elsevier, 192 116373. link >
Hossein, A., Paki, R., & Bahrini, A. (2021). A novel approach based on combining deep learning models with statistical methods for COVID-19 time series forecasting. Neural Computing and Applications, Springer London, 34 1-15. link >
Bahrini, A., Riggs, R., & Esmaeili, M. (2021). Social Choice Rules, Fallback Bargaining, and Related Games in Common Resource Conflicts. Journal of Hydrology, Elsevier, 602 126663. link >
Abbasimehr, H., Paki, R., & Bahrini, A. (2021). Improving the performance of deep learning models using statistical features: The case study of COVID-19 forecasting. Wireless Network, Wiley Online Library, 15. link >
Abbasimehr, H., & Bahrini, A. (2021). Improving churn prediction using imperialist competitive algorithm for feature selection in telecom. International Journal of Business Information Systems, Inderscience.
Mohammadi, M., & Bahrini, A. (2019). A Nash–Stackelberg equilibrium model for internet and network service providers in the demand market—a scenario-based approach. Wireless Network, Springer Nature, 26 (1), 12.
Esmaeili, M., Bahrini, A., & Shayanrad, S. (2015). Using game theory approach to interpret stable policies for Iran’s oil and gas common resources conflicts with Iraq and Qatar. Journal of Industrial Engineering International, Springer Nature, 11 543-554. link >

Conference Proceedings

Bahrini, A., Khamoshifar, M., Abbasimehr, H., Riggs, R., Esmaeili, M., Mastali Majdabadkohne, R., & Pasehvar, M. (2023). ChatGPT: Applications, opportunities, and threats. ( pp. 274-279). 2023 Systems and Information Engineering Design Symposium (SIEDS), USA: IEEE. link >
Jain, A., Bahrini, A., Nour, E., Patel, H., Riggleman, ., Wittmann, T., Measells, K., Dowdell, K., Riggs, S., & Riggs, R. (2023). Improving Patient Flow in a Healthcare Clinic Post COVID-19: A Data Validation and Exploratory Analysis Approach. ( pp. 119-124). 2023 Systems and Information Engineering Design Symposium (SIEDS), USA: IEEE. link >
Dozier, C., Schmid, A., Huffman, B., Cusack, M., Saas, S., Wu, W., Bahrini, A., Riggs, R., Dowdell, K., & Measells, K. (2022). Optimization of Patient Flow and Process for a Primary Care Clinic During the COVID-19 Pandemic. ( pp. 282-287). 2022 Systems and Information Engineering Design Symposium (SIEDS), USA: IEEE. link >

Honors and Awards

Deloitte Scholar, University of Illinois at Urbana-Champaign, 2024 to present
Teachers Ranked as Excellent, UIUC Center for Innovation in Teaching & Learning, 2023-2023

Service

Session chair IEEE Systems and Information Engineering Design Symposium (SIEDS), 2023 IEEE Systems and Information Engineering Design Symposium (SIEDS), 2023 to present, 2024-2024
Ad Hoc Reviewer, Chaos, Solitons and Fractals, 2023 to present
Ad Hoc Reviewer, Expert Systems with Applications, 2023 to present
Ad Hoc Reviewer, Big Data, 2022 to present
Ad Hoc Reviewer, Chemosphere, 2022 to present
Ad Hoc Reviewer, Computational and Applied Mathematics, 2022 to present
Ad Hoc Reviewer, Computer Methods in Biomechanics and Biomedical Engineering, 2022 to present
Ad Hoc Reviewer, European Journal of Operational Research, 2022 to present
Ad Hoc Reviewer, Systems MDPI, 2022 to present
Ad Hoc Reviewer, Isa Transactions, 2022 to present
Ad Hoc Reviewer, Japan Journal of Industrial and Applied Mathematics, 2022 to present
Ad Hoc Reviewer, Journal of Water Resources Planning and Management, 2022 to present
Ad Hoc Reviewer, Operations Research and Decisions, 2022 to present
Session chair IEEE Systems and Information Engineering Design Symposium (SIEDS), 2022 IEEE Systems and Information Engineering Design Symposium (SIEDS), 2022 to present
Ad Hoc Reviewer, Water Resource Research, 2022 to present
Ad Hoc Reviewer, Wireless Network, 2022 to present
Ad Hoc Reviewer, WORK: A Journal of Prevention, Assessment & Rehabilitation, 2021 to present
Ad Hoc Reviewer, Journal of Hydrology, 2021 to present
Ad Hoc Reviewer, Optimization and Engineering, 2021 to present
Ad Hoc Reviewer, Multimedia Tools and Applications, 2021 to present
Ad Hoc Reviewer, Annals of Operations Research, 2021 to present
Ad Hoc Reviewer, Sustainable Cities and Society, 2021 to present
Ad Hoc Reviewer, Expert Systems, 2021 to present
Ad Hoc Reviewer, IEEE Transactions on Industrial Informatics, 2021 to present
Ad Hoc Reviewer, Information Processing & Management, 2021 to present
Ad Hoc Reviewer, International Journal of Biomathematics, 2021 to present
Ad Hoc Reviewer, IEEE Access, 2020 to present
Ad Hoc Reviewer, Numerical Methods for Partial Differential Equations, 2020 to present
Ad Hoc Reviewer, Mathematical Methods in the Applied Sciences, 2020 to present
Ad Hoc Reviewer, Journal of Thermal Analysis and Calorimetry, 2020 to present
Ad Hoc Reviewer, Engineering with Computers, 2020 to present
Ad Hoc Reviewer, Group Decision and Negotiation, 2019 to present
Ad Hoc Reviewer, Safety and Health at Work, 2018 to present
Ad Hoc Reviewer, International Journal of Systems Assurance Engineering and Management, 2018 to present
Ad Hoc Reviewer, Journal of Quality Engineering and Production Optimization, 2018 to present
Ad Hoc Reviewer, International Journal of Production Research, 2016 to present
Ad Hoc Reviewer, Journal of Industrial Engineering International, 2016 to present
Session chair, INFORMS 2024, 2024-2024
Session chair for SC24. Digital Supply Chains, 2023 INFORMS Annual Meeting, 2023-2023

Teaching Interests

BADM 210: Business Analytics I
BADM 211: Business Analytics II
BADM 378: Logistics Management
BADM 453: Business Intelligence
BADM 557: Topics in Business Intelligence

Research Interests

Methods: Mathematical modeling, optimization, game theory, machine learning, forecasting, artificial intelligence
Applications: Resource management, supply chain management, healthcare systems, business analytics, data analytics

Current Courses

Business Analytics II (BADM 211) Builds on the foundation from the Business Analytics I (BADM 210), synthesizes concepts through hands-on application and project-based learning. Focuses on data acquisition, organization, analysis and visualization in a business setting. Expanding on the use of statistics in generating basic inferences to predictive modeling Identify opportunities for improving business decisions using data, conduct relevant analysis of the gathered and cleaned data, and finally, interpret and present analysis outcomes to decision makers. Using statistical tools and software applications to identify business problems, acquire relevant data, and generate analytic solutions using advanced analytics techniques and tools for generating insights. Introduces the students to analyzing, learning, and prediction using advanced analytics techniques and tools for generating business insights. This course will provide a practical introduction to various techniques regarding clustering, text mining, classification and decision trees, and time series analysis. Finally, the course will introduce advanced and emerging topics in predictive analytics.
Logistics Management (BADM 378) Treats the total flow of materials from their acquisition as basic or unprocessed supplies to delivery of the finished product, as well as the related counter-flows of information that both record and control material movement. Major topics include forecasting material requirements; transportation planning; order processing system; raw material, in-process and finished goods inventory management; packaging; in plant and field warehousing; location theory (space, time, and cost trade- offs); communications; and control.
Business Intelligence (BADM 453) Provides a conceptual and practical overview of analytical tools, techniques, and practices used to support data-driven decision making in organizations. Topics include data visualization, data mining, machine learning techniques and business intelligence programming languages.
Topics in Bus Intelligence (BADM 557) In recent years, an increasing number of companies, large and small, have begun to utilize big data and associated analytics methods to gain information and support their decision-making. This course will introduce students to the basic principles and technology foundations of data mining, focusing on business applications of machine learning. Different topics such as different algorithms and software may be covered in different semesters.