Program Overview

Computational Decision Science and Operations Research (M.S.)

The Computational Decision Science and Operations Research (CDSOR) program is designed to provide students with the skills and knowledge necessary to analyze huge quantities of data and make better decisions using algorithms, machine learning, and optimization techniques.

Program Overview

Computational decision science helps meet the need for decision processes that can parse voluminous data and make recommendations based on that data. The program allows students to analyze huge quantities of data while helping organizations make better decisions using algorithms, machine learning, and optimization techniques that interpret the data.

Techniques and Applications

Some examples of techniques used in computational decision science include:

• AT&T has used optimization techniques to plan its high-speed network.
• GE has used optimization to improve train scheduling with multiple data points and schedule constraints.
• UPS has used route optimization to reduce the cost of parcel delivery while improving the accuracy of their results by learning routing data.
• A California hospital chain has used machine learning techniques and prescriptive analysis to reduce patient re-admissions.

The Analytic Sequence

The road to optimized decisions involves the three phases of analytics:

• Descriptive analytics, which aids in the analysis of historic data to identify patterns using tools from data wrangling, statistics, and data mining.
• Predictive analysis, which helps predict future trends and probabilities of events, and determines relationships in the data using tools from machine learning and statistical learning.
• Prescriptive analysis, which utilizes data to determine the best course of action.

Program Details

The CDSOR program helps students identify future trends that lead to determination of the best decisions, actions, or outcomes. The program provides the foundations of prescriptive science and trains students in computational and mathematical discovery of decision processes. Students will be able to apply techniques learned in CDSOR to applications in multiple industries.

Program Director

The program is directed by Sanjiv Kapoor, Professor of Computer Science.

Program Outcomes

The CDSOR program will train students in computational and mathematical discovery of decision processes, and students will be able to apply techniques learned in CDSOR to applications in multiple industries. The program provides the foundations of prescriptive science and utilizes techniques from multiple technical areas, including fundamental techniques from statistics, algorithm design, mathematical modeling, and optimization theory and techniques, as well as applications that include machine learning, AI, and data mining.