Georgia Tech’s MS-Math fuses proof-heavy foundations with GPUs and cloud notebooks. Students formalize theorems in Lean, build neural-PDE surrogates for turbulence, and price exotic derivatives with stochastic calculus on CUDA clusters. Industrial seminars from Sandia, Two Sigma, and NVIDIA show careers where pure rigor meets billion-dollar stakes.
Graph homology detector for misinformation network pruning
Finite-element solver for viscoelastic soft-robot actuators
Optimal transport metric for bias in ML feature spaces
Stochastic differential-equation model of epidemiological spikes
Proof-assistant formalization of cryptographic hardness assumptions
Sparse Fourier transform compression of high-rate seismic data
Random-matrix analysis of mmWave MIMO channel capacity
Game-theoretic study of carbon credit auction dynamics
GPU-accelerated Navier–Stokes solver for microfluidic chips
Neural-ODE surrogate for orbital debris propagation
Integer programming timetable for campus shuttle optimization
Topology optimization of acoustic metamaterial panels
Bayesian inverse model for geothermal reservoir parameters
Quantum walk algorithm exploration on irregular graphs
Fractal dimension study of urban sprawl using Landsat imagery
Translate abstract proofs into algorithms that reshape industries.
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