Georgia Tech’s Mathematics BS marries pure rigor with computational muscle. After conquering real analysis and abstract algebra, students leap into numerical PDEs on CUDA clusters, topological data-analysis of social graphs, and stochastic calculus for fintech derivatives. Undergraduate research seminars pair majors with faculty cracking cryptographic lattices or mapping neural manifolds, while the Applied Math Clinic solves live problems for NASA, CDC, and Google. Graduates leave fluent in proof assistants, Python/Julia stacks, and the art of translating theorems into disruptive algorithms.
Graph-theoretic community detection in cryptocurrency transaction networks
Finite-element solver for viscoelastic soft-robot actuators
Homology-based anomaly detector in high-dimensional sensor streams
Stochastic differential-equation model of option-pricing under jump diffusion
Proof-assistant formalization of Gödel’s completeness theorem
Quantum-walk algorithm exploration on planar graphs
Bayesian inverse problem for geothermal-reservoir parameter estimation
Optimal transport framework for image-style transfer metrics
Markov-chain mixing-time study of political redistricting maps
Sparse Fourier transform compression of EEG seizure data
Game-theoretic analysis of vaccine allocation under limited supply
Random-matrix statistics of mm-wave MIMO channel capacity
Number-field sieve implementation benchmarking on ARM clusters
Neural-ODE surrogate model for turbulent-flow prediction
Integer-programming timetable for campus shuttle optimization
Turn abstract theory into algorithms that reshape the world.
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