UC’s MS in Applied Mathematics develops expertise in differential equations, numerical analysis, and optimization, preparing graduates for careers in research, finance, tech, and engineering.
PDE model simulating wildfire spread under variable wind fields
Optimization algorithm for equitable vaccine-distribution logistics
Spectral method solver accelerating quantum-chemistry calculations
Stochastic differential model of cryptocurrency price dynamics
Finite-element simulation of earthquake-induced soil liquefaction
Machine-learning-enhanced multigrid methods for climate models
Game-theoretic resource allocation in edge-computing networks
Inverse-problem approach to medical-image reconstruction in MRI
Combinatorial algorithm scheduling satellite constellations for Earth observation
Numerical bifurcation analysis of epidemiological compartment models
Data-driven reduced-order models for turbulence in wind-farm flow
Graph-theory study optimizing power-grid resilience to cascading failures
Hybrid neural-PDE solver for battery-degradation prediction
Monte-Carlo method estimating financial risk under heavy-tail returns
Topology optimization of lightweight aerospace truss structures
Mathematical model of crowd dynamics in emergency evacuations
Sparse-matrix library benchmarking on GPU clusters
Control-theory design for autonomous drone swarm formation
Markov-chain analysis of ecological metapopulation stability
Workshop series teaching open-source math software to local schools
Solve big problems with UC’s mathematically rigorous MS.
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