West Lafayette

General Information

The Computational Science and Engineering track focuses on using computation to model, simulate, analyze, and optimize complex systems arising in science, engineering, and data-driven applications. This track is designed to prepare you for careers in industry and research, as well as for graduate study, in areas that rely on mathematical modeling, numerical computation, algorithms, and large-scale software systems.

Coursework and Topics

Students completing this track explore topics including:

• Ordinary differential equations and mathematical modeling
• Numerical methods and numerical linear algebra
• Algorithm design and analysis
• Optimization and operations research
• Data mining, machine learning, and bioinformatics
• Parallel, concurrent, and systems-level computing

The required coursework ensures breadth across mathematics, algorithms, and systems, while electives allow students to tailor the track toward numerical analysis, optimization, parallel computing, robotics, artificial intelligence, or theoretical foundations.

Graduate Pathways

Jobs and activities for students graduating from this track may include:

• Computational Science and Engineering Industry Roles – working on simulation software, numerical libraries, performance-critical code, and computational modeling tools.
• Data Science and Machine Learning Applications – developing algorithms and systems for data mining, bioinformatics, information retrieval, and large-scale data analysis.
• Engineering and Scientific Software Development – building and maintaining software for modeling, simulation, and analysis in areas such as aerospace, energy, materials science, and biomedical engineering.
• High-Performance and Parallel Computing – designing and optimizing parallel and distributed algorithms for multicore processors, GPUs, and large computing systems.
• Research Laboratories and National Labs – working in applied research environments focused on scientific computing, modeling, and large-scale simulation (often with a graduate degree).
• Graduate School – pursuing an MS or PhD in computer science, computational science and engineering, applied mathematics, data science, or engineering disciplines, leading to careers in research labs, industry R&D, and academia.

All major required courses, all track requirements and track selectives, and their pre-requisites, regardless of department, must be completed with a grade of C or better.

Notes:

• At least four (4) of the seven (7) classes for this track must be CS classes.
• No course can be counted both for required and elective credit. This is true for all tracks.