Shaya Sheikh
Title: Associate Professor
Department: Supply Chain and Business Analytics
Campus: New York City
Area(s) of Expertise: Business Analytics, Data-Driven Models, Energy Supply Chain
Education Credentials: Ph.D.
Joined New York Tech: 2015
Shaya Sheikh obtained his Ph.D. from Case Western Reserve University in 2013. He worked as a scheduling and optimization scientist at Lancaster Laboratories and as a visiting professor at the University of Baltimore before joining New York Institute of Technology in 2015.
Currently, he serves as an associate professor of business and supply chain analytics in the School of Management. His research interests include the energy supply chain, scheduling, and the application of state-of-the-art, data-driven models for a variety of business challenges.
Sheikh has authored more than 40 research papers in highly ranked peer-reviewed journals and conference proceedings such as Decision Support Systems, Energy, International Journal of Production Research, Applied Mathematical Modeling, Computers & Industrial Engineering, Journal of Intelligent Manufacturing, International Journal of Advanced Manufacturing Technology, Operations Research Perspective, Journal of Wireless Networks, and IEEE international conferences. In addition, he serves as an editorial board member for several journals covering management and business analytics.
He is also the session chair for top international conferences such as INFORMS and POMS, and a co-chair, organizer, and committee member for several others. A prominent figure at international conferences in his field, Sheikh is regularly invited to speak, provide keynote remarks, and/or participate as a reviewer/panelist to grant and award-funding agencies. He also serves as an invited and ad-hoc reviewer for more than 15 top journals in the energy and business analytics fields.
Recent Projects and Research
- "Supply Chain Design under Disruptions Risks and Carbon Emissions," Institutional Support for Research and Creativity (ISRC) Grant, $10,135.61.
- "Big Data Driven Energy Management in Solar Powered Smart Homes," Institutional Support for Research and Creativity (ISRC) Grant, $8,139.96.
Selected Publications and Presentations
Journal Publications
- Vosoughi, S., S. Sheikh, E. Kamel, A. Jafari (2024) "Analyzing Energy Performance in American Low-Income Households Using A Data-Driven Approach," Journal of Building Engineering, Volume 89, 109305.
- Sheikh, S., M. Rabiee, M. Nasir, A. Oztekin (2022) "An Integrated Decision Support System for Multi-Target Forecasting: A Case Study of Energy Load Prediction For a Solar-Powered Residential House," Computers and Industrial Engineering, Volume 166, 107966.
- Jabbari, M., S. Sheikh, M. Rabiee, A. Oztekin (2022). A Collaborative Decision Support System for Multi-Criteria Automatic Clustering: A Framework Development. Decision Support Systems, Volume 153, February 2022, 113671.
Kayvanfar, V., M. R. Akbari Jokar, M. Rafiee, S. Sheikh, R. Iranzad (2021). A New Model for Operating Room Scheduling with Elective Patient Strategy. INFOR: Information Systems and Operational Research, Volume 59, Issue 2, 309–332.
Kamel, E., S. Sheikh, X. Huang, (2020). Data-Driven Predictive Models For Residential Building Energy Use Based on The Segregation of Heating and Cooling Days. Energy, Volume 206, 118045.
Blind Peer-Reviewed Published Conference Proceedings
- S. Sheikh, E. Kamel, and A. Jafari (2023) "The Impact of Affordable Home Features on Energy Burden in Low-Income Households in the U.S.," ASCE International Conference on Computing (i3CE2023), June 25–28, Oregon State University, Corvallis, Oregon.
- Kamel, E, S. Sheikh (2020) "Typical Meteorological Year and Actual Weather Data in Data-Driven Machine Learning Models for Residential Building Energy Use," ASHRAE Transactions, 2020.
- Sheikh, S., I. Gharib, S. Bigdeli, V. Kayvanfar (2019) "Identification of Dominant Customer Behavior Patterns among Different Sectors over Time; A Case Study," 2019 IEOM, Toronto, Canada.
Honors and Awards
- Conference Co-Chair, International Conference on Industrial Engineering (ICINDE'17) Hong Kong, 15–17 March, 2017.
- Best Track Paper Award, 2015 IEOM Conference, Orlando, Florida.
Courses Taught at New York Tech
- QANT 201 Managerial Statistics
- QANT 300 Operations Management
- QANT 405 Management Science
- QANT 501 Statistics (M.B.A.)
- QANT 510 Operations Management (M.B.A.)
- QANT 520 Management Science (M.B.A.)
- QANT 620 Multiple Criteria Decision Models (M.B.A.)
- QANT 630 Operations and Supply Chain Management (M.B.A.)
- BUSI 650 Business Analytics and Decision Making
- QANT 750 Simulation (M.B.A.)
- MGMT 785 Decision Support Systems (M.B.A.)