Data Analytics

Data analytics is a way to use data and facts to help address engineering, scientific, and business challenges. The focus is on making the best use of advanced computational and data processing tools in order to inform decision-making. A variety of technical challenges and opportunities have arisen with the emergence of ‘big data’: large volumes of unstructured data in the form of text, images, videos, etc.

The operations research group’s expertise covers theoretical, computational, and applied research in data analytics. We develop methodologies and best practices for data-driven decision-making, motivated by a broad set of real-world problems.  All forms of analytics are considered: descriptive, predictive, and prescriptive.

 

Methodologies

  • Interpretable Statistical Learning
    • Convex and nonconvex penalties for feature selection
  • Machine Learning
    • Large-scale algorithms
  • Prescriptive Analytics and Data-Driven Decision Making

Applications

  • Cyber Security
  • Energy Systems
  • Genome Association Studies
  • Healthcare
  • Manufacturing
  • Transportation and Mobility

Concentration Faculty

 


Theodore Allen   |   Güzin Bayraksan   |   Chen Chen   |   Sam Davanloo   |   Parinaz Naghizadeh   |   Marc Posner   |   Cathy Xia