Dept: Industrial and Manufacturing Systems Engineering
Keywords: Optimization, large-scale computation, resource allocation, text analysis, deep learning.
We live in an era of data explosion. The rapid advances in sensor, communication and storage technologies has made data acquisition more ubiquitous than at any time in the past. It is estimated that the digital information to be created in 2020 will be 44 times greater than it was in 2009, reaching a total of 44 ZB (1ZB=109 TB). We are inevitably facing an information dilemma, in which the excessive amount of data available cannot be fully processed to yield useful and actionable information.
My research aims at resolving our modern-day information dilemma from the standpoint of mathematical modeling and optimization. It revolves around a central question: How can data represented in the forms such as signals, images, and time series, be effectively modeled and processed with unprecedented scale. Theoretically, I have been advocating for approaching big data problems using non-convex models and algorithms. Practically, I have worked closely with national labs and leading industry companies to apply my modeling and optimization expertise to large-scale data acquisition, delivery and analytics applications, such as designing next generation 5G network system, text and document analysis, applications of deep learning, etc.
Email: mingyi at iastate.edu, Phone: 4-2943