Northwestern’s IEMS BS transforms students into operations strategists fluent in stochastic modeling, human factors, and data-driven decision science. Projects range from streamlining hospital patient flow to designing resilient supply chains for e-commerce. A professional-development seminar series connects majors with alumni at Tesla, McKinsey, and Major League Baseball analytics, while the Segal Design Institute infuses human-centered design into every optimization model.
Develop a dynamic pricing algorithm balancing profit and inventory perishability
Simulate emergency-department triage to minimize wait times and staff burnout
Optimize drone-last-mile delivery routing under stochastic demand
Design a human-factors dashboard reducing cognitive load in air-traffic control
Model risk-aware supply-chain networks for semiconductor fabs
Create a scheduling heuristic for mixed-model EV assembly lines
Analyze esports tournament formats for competitive balance using Monte Carlo
Implement real-time rail-network dispatch optimization with reinforcement learning
Evaluate fairness-efficiency trade-offs in organ-transplant allocation policies
Build a digital twin of campus energy use to test demand-response strategies
Prototype a VR ergonomics assessment tool for warehouse picking tasks
Develop portfolio-allocation models integrating ESG risk metrics
Optimize vaccination-site layouts for throughput and social distancing
Design a predictive-maintenance plan for wind-turbine fleets
Assess algorithmic bias in workforce scheduling software for shift workers
Engineer efficiency and equity in global operations with Northwestern IEMS.
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