Amin Keramati, PhD
- Assistant Professor
PhD, Transportation & Logistics
North Dakota State University (ND)
I am currently an assistant professor of supply chain management at Widener University. I believe my main role in the classroom is a facilitator of the complexity of data analysis and supply chain management knowledge. Subsequently, I tailor the material to overcome the technical difficulty in the courses and I focus on how the course content can be relevant to the students’ future careers. My teaching interests lie in the areas of enterprise resource planning, decision analytics, database management systems, transportation & logistics systems, project management, and data analytics.
I received a PhD degree in transportation and logistics with a concentration in logistics and supply chain systems from North Dakota State University. Prior to joining the Widener University, I was a graduate research assistant of a transportation and logistics focused research and education center known as the Upper Great Plains Transportation Institute (UGPTI). As a graduate research assistant, I was working on federally funded projects like Mountain-Plains Consortium project (MPC- [#550]) which was the expansion of my dissertation involving “Safety Support System for Highway-Rail Grade Crossing”.
In general, exploring and developing new mathematical, statistical, and machine learning approaches to solve transportation, supply chain and logistics complex problems are among my current and future research objectives. Moreover, I am open to conduct cutting-edge research ideas including those involving multi-discipline expertise to come up with new perspectives and solutions to existing complex problems. Relevant areas of my current and future research include: data mining & statistical analysis, decision-making supported by big data, transportation network analytics, project scheduling problems, machine learning algorithms for smart manufacturing, and accident analysis.
- Keramati, A., Lu, P., Ren, Y., Tolliver, D., & Ai, C. (2021). Investigating the effectiveness of safety countermeasures at highway-rail at-grade crossings using a competing risk model. Journal of Safety Research.
- Keramati, A., Lu, P., Iranitalab, A., Pan, D., & Huang, Y. (2020). A crash severity analysis at highway-rail grade crossings: the random survival forest method. Accident Analysis & Prevention, 144, 105683.
- Keramati, A., Lu, P., Tolliver, D., & Wang, X. (2020). Geometric effect analysis of highway-rail grade crossing safety performance. Accident Analysis & Prevention, 138, 105470.
- Keramati, A., Esmaeilian, M., & Rabieh, M. (2015). Developing a Model for Project Scheduling with Limited resources and Budget with Considering Discounted Cash Flows through Fixed Prioritization Method. Asian Journal of Research in Business Economics and Management, 5(1), 212–220.
Student Paper Award, American Association of State Highway and Transportation Officials (2017)