Data-driven decision-making facing complex data environment

In this talk, we present the key challenges in data-driven decision-making when faced with a complex data environment. Traditionally, most data-driven decision-support tools are developed in a static fashion, meaning they consider a set of fixed, well-structured data to derive inferences or decisions. Nevertheless, even though these decision-making tools are rigorous and mathematically sound, they have not often been effective due to the dynamic nature and underlying complexity of the data in practice. 
We design and develop novel, fast, and robust algorithms and frameworks for complex data-driven problems to tackle key challenges in the area of e-commerce and services. We devise integrated learning and optimization techniques to solve such problems. 

Hoda Bidkhori is an expert in data analytics and optimization, particularly, data-driven decision-making. She received her Ph.D. from the Massachusetts Institute of Technology (MIT). She spent four years as a postdoctoral researcher and a lecturer in operations research and statistics at MIT, working with leading experts in optimization and data analytics. She won the competitive Lagrange DARPA Grant in 2018, which supports part of her research. She won the Roger Family Prizes for excellent mentorship at the undergraduate research program at MIT in 2007, 2008, and 2009.