The MODS team collaborates with researchers, students, and industry partners outside Lehigh.

  • Prof. Curtis and Prof. Shehadeh are leading a team of two doctoral students and three undergraduate students on the design and implementation of scheduling software for residency programs at hospitals.  A tool developed by team members in prior years has already been used for resident rotation scheduling at a major hospital for the past few years.  The team is currently developing a user-friendly tool for use in resident call scheduling as well, and is investigating more advanced features, such as how the tool can be relied upon to produce schedules that are robust under uncertainty.
  • Two undergraduate students, Kevin Bradigan and Shengping Huang, worked with Srinivas Rangarajan in the summer on projects involving machine learning for reaction elucidation. Kevin, in collaboration with Martin Takac’s group at MBZUAI, applied deep neural networks to develop a physics-constrained kinetic model for water gas shift reaction using experimental data collated from several hundred different studies on a range of metal alloy catalysts. The resulting kinetic model can be used in catalyst and process optimization for this chemistry. Shengping applied in-house software developed by the Rangarajan group, called RING, in combination with a machine-learned energy calculator to elucidate the reaction pathways in plastic upcycling. Insights about these pathways can enable designing optimal catalysts to maximize the yield of value-added products. Both Kevin and Shengping will continue to work on these projects in AY 22-23 as part of their senior thesis.