UF’s MS in Industrial and Systems Engineering trains students to optimize manufacturing, logistics, healthcare, and service systems using quantitative modeling and simulation. Topics include operations research, human factors, machine learning, and systems design. Graduates lead in industries that require precision, scalability, and data-driven planning.
Simulation of patient flow optimization in emergency departments using discrete-event modeling
Thesis on machine learning for predictive maintenance in manufacturing lines
Supply chain resilience modeling under multiple global disruption scenarios
Design of a dashboard for real-time production and quality tracking in factories
Human-computer interaction study on wearable technology use in industrial settings
Queueing analysis of customer service systems in high-volume retail stores
Integer programming model for scheduling nurses in rotating shifts with preferences
Optimization of warehouse layout for faster picking and reduced travel time
Cyber-physical system design for adaptive traffic signal control in urban areas
Monte Carlo simulation of inventory systems with variable demand and lead times
Comparative study of Kanban vs. CONWIP systems in lean manufacturing
Decision support tool for prioritizing healthcare resource allocation during pandemics
Data-driven modeling of vehicle routing with time windows for food delivery services
Ergonomic evaluation of manual assembly workstations using motion capture
Design of a smart transportation model integrating real-time GPS and IoT sensors
Workload balancing model for multiproduct assembly lines with task variability
Safety system redesign in construction zones using human error probability modeling
Heuristic algorithms for NP-hard facility location problems in logistics networks
Evaluation of crowd movement algorithms for event safety planning
Optimization model for multi-modal freight transport in the Southeastern U.S.
Lead complex systems innovation with modeling, optimization, and human-centered design.
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