SSE Degree Concentrations

Concentrations are focused areas of study that provide students with a critical level of expertise in a particular domain within SSE, preparing the student for employment or graduate school in that domain. To satisfy the requirements for a concentration, students must complete at least four courses from the selected concentration as detailed below.  

*Students may only pursue one Concentration. Please note: Students who are submatriculating MUST meet all of the concentration requirements BEFORE obtaining their undergraduate degree.

Form to declare a concentration

Robotics

Must Complete the following course:

ESE 421 Control For Autonomous Robots

Select 3 from the following courses: 

ESE 500 Linear Systems Theory

ESE 505 Feedback Control Design and Analysis

ESE 512 Dynamical Systems for Engineering and Biological Applications

ESE 619 Model Predictive Control

MEAM 520 Introduction to Robotics

MEAM 620 Advanced Robotics

Data Science and Artificial Intelligence

Must Complete the following course:

ESE 305 Foundations of Data Science

Select 3 from the following courses: 

ESE 545 Data Mining: Learning from Massive Datasets

ESE 546 Priniples of Deep Learning

ESE 650 Learning in Robotics

CIS 520 Machine Learning

CIS 545 Big Data Analytics

NETS 312 Theory of Networks

ECON 262 Market Design

Decision Science

Decision Science (DS) is an interdisciplinary field that uses analytical methods to support better decisions. It employs techniques from probability, statistics and mathematical optimization. The concentration will equip students with the foundational knowledge and technical expertise need to deal with complex decision-making problems in organizations ranging from petrochemicals to airlines, finance, e-commerce, logistics, and government. The DS concentration will equip students with the foundational knowledge and technical expertise that enables data-driven insights to help organizations make better decisions.

Must Complete the following course:

ESE 504 Intro to Linear, Nonlinear and Integer Optimization

Select 3 from the following courses: 

ESE 545 Data Mining: Learning from Massive Datasets

ESE 605 Modern Convex Optimization

NETS 312 Theory of Networks

OIDD 224 Analytics for Service Operations

OIDD 353 Mathematical Modeling and its Application in Finance

CIS 515 Fundamentals of Linear Algebra and Optimization

ESE 550 Advance Transportation Seminar, Air Transportation Planning

STAT 476 Applied Probability Models in Marketing

at most one from the following options:

  • MATH 432 Game Theory
  • NETS 412 Algorithmic Game Theory
  • ECON 212 Game Theory
  • ECON 682 Game Theory and its Applications