UC’s MS in Engineering Mathematics & Statistics trains students to construct, analyze, and optimize mathematical models underpinning modern engineering and data-driven decision making.
Bayesian hierarchical model estimating bridge-fatigue life from sensor data
Finite-volume solver accelerating wildfire spread prediction on GPUs
Spectral clustering of urban mobility networks for transit redesign
Stochastic control of autonomous-vehicle platoons under communication delays
Adjoint-based gradient optimization of aerodynamic winglets
Gaussian-process emulator of climate-model outputs for uncertainty quantification
Sparse-regression discovery of governing equations in cardiac electrophysiology
Markov-chain Monte Carlo toolkit for real-time epidemic parameter inference
Mixed-integer program scheduling battery-storage dispatch for price arbitrage
Random-matrix analysis of 5G massive-MIMO channel capacity
Neural-ODE framework modeling chemical-reactor kinetics with limited data
Multilevel Monte Carlo valuation of renewable-energy derivatives
PDE-constrained deep-learning surrogate for groundwater contaminant transport
Game-theoretic allocation of airport slots minimizing total delay
Kernel-density estimation of traffic crash hotspots incorporating weather covariates
Hybrid genetic-algorithm and gradient method for satellite constellation design
Topological data-analysis of turbulence structures in jet flows
Sequential experimental design for adaptive A/B testing in e-commerce
Workshop series teaching open-source math libraries to underrepresented students
White paper on reproducible computational modeling standards in engineering
Model, analyze, and optimize with UC’s mathematically rigorous MS.
Whether it's Machine Learning, Data Science, or Web Development, Collexa is here to support your academic journey.
"Collexa transformed my academic experience with their expert support and guidance."
Computer Science Student
Reach out to us for personalized academic assistance and take the next step towards success.
