MHEFI Scholarship Winners: Where Are They Now?
Finding Answers in Algorithms: Seyed Shahab Mofidi, Rensselaer Polytechnic Institute
Seyed Shahab Mofidi envisions a time in the not-too-distant future when online shoppers click their mouse and take delivery of their purchases just minutes later. And as a senior data and operations research scientist at MHI member Honeywell Intelligrated in Atlanta, he is focused on making that future a reality.
Mofidi builds mathematical models and algorithms to make automated warehouses and distribution centers run more efficiently. His company provides automated material handling solutions and an intelligent software platform called a warehouse execution system to integrate the various components. Armed with Mofidi’s algorithms and modeling, the software uses real-time data to make complex decisions about how to optimize warehouse operations.
“Our software system basically orchestrates the entire distribution operation in a warehouse, and my role is to build advanced decision-support tools that enhance the operational efficiencies and throughput,” he said.
Using Focused Research to Solve Optimization Problems: Austin Buchanan, Oklahoma State University
The MHEFI and Austin Buchanan share an important trait—they both are focused on helping the next generation of leaders in the material handling industry achieve their goals.
Buchanan, 30, returned to his alma mater, Oklahoma State, in 2015 as an assistant professor in the industrial engineering and management (IEM) program. He now teaches undergraduate courses in facilities and material handling system design, engineering economy and operations research and graduate-level courses in network flows and integer programming.
His research focuses on solving optimization problems, especially those relating to networks and connectivity over distance. Recently, he worked on problems such as finding the best math model for designing a wireless sensor network, the best way to enforce low-diameter constraints in cluster detection models and the best way to enforce contiguity constraints in political districting models.