This interdisciplinary BS program at UMD combines mathematics, computer science, and physical sciences to train students in the modeling, simulation, and analysis of complex systems. Students learn to apply computational techniques and numerical methods in scientific and engineering contexts, making it ideal for careers in tech, research, and data-intensive fields. Core topics include differential equations, scientific computing, optimization, and high-performance computing. The program is suited for students aspiring to pursue advanced degrees or R&D roles.
Simulating traffic flow using partial differential equations
Building a numerical solver for heat distribution in 2D materials
Optimization of energy usage in smart grids
High-performance computing simulation of protein folding
Mathematical modeling of infectious disease spread
Real-time tsunami modeling using finite element analysis
Algorithmic trading strategies based on stochastic modeling
Numerical approximation of solutions to nonlinear systems
Simulation of planetary orbits using Newtonian mechanics
Designing AI for solving differential equations symbolically
Parallel computation of fluid dynamics simulations
Mathematical modeling of urban heat islands
Cryptographic algorithms and number theory in secure computing
Machine learning for solving inverse mathematical problems
Building a weather forecasting model using historical datasets
Modeling biological neural networks using ODEs
Image reconstruction in medical tomography using matrix algorithms
Bayesian computation for parameter estimation in physics
Simulation of epidemic intervention strategies using agent-based modeling
Quantum computing applications in mathematical optimization
Blend mathematics, computation, and science in a program built for future innovators.
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