Laboratory for Interactive Optimization and Learning

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Overview and

Research Objective

Information, Learning, and Decision-Making

The next revolution will be the seamless integration of machines and the digital world: the creation of fully-integrated, high-performance cyber-physical systems and other entities. This fusion will heavily rely on inference from observational data and automated decision making based on derived information and intelligence: the combination of optimization and machine learning.

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The Analytics Feedback Loop:

Integrating Data, Learning, and Decision-Making

Overview and Research Objective.


Traditionally, data was collected and used to validate a model hypothesis, which in turn, once verified, formed the basis for decision-making and optimization. With the abundance of data and computational power we can, for the first time, afford an integrated perspective of data, learning, and decisions, where data is directly considered in the decision-making problems through state-of-the-art machine learning. Overcoming the traditional approach of optimizing against a proxy provides faster and more relevant decisions as well as a more direct risk-mitigation in decision making.


The Laboratory for Interactive Optimization and Learning performs research at the intersection of optimization and machine learning in order to devise improved algorithms to be used and deployed in the context of real-world problems and industry-application. To date we have successfully deployed analytics methodology in more than 20 real-world projects in various capacities. The applications of interest span various areas, including logistics and supply chain management, manufacturing, predictive analytics, big data, digital services, energy, transportation, and medical and healthcare systems. We complement our application-oriented research with a significant foundational research portfolio, which is informed by and informs applications and drives innovation in our methodologies.  


We closely collaborate with faculty from various units at Georgia Tech including:

- Institute for Robotics and Intelligent Machines (IRIM)

- Algorithms and Randomness Center (ARC)

- Center for Next Generation Logistics (C4NGL)

- Technology Transition Lab (TTL)

- School of Industrial and Systems Engineering (ISyE)

- School of Interactive Computing (IC)





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