AI/Machine Learning

Every day, we are creating more and more data. Most of today's
Socio-Economic-Policy and Scientific applications/ create TeraB data
every year and some even creates over 10s of TeraB and this will
increase in coming years and will reach PetaB data. Mining these
information and creating evolutionary computing-based decision tree from
imprecise-perception-based /Socio-Economic-Policy-Scientific/ will be an
important area of research.

Project Summary: Prof. Jordan's group works in a number of fundamental topics in machine learning, including graphical modeling, clustering, classification, dimension reduction, spectral analysis, independent component analysis, reinforcement learning and link analysis.The group also works on applications of machine learning, in areas such as distributed computer systems, natural language processing, signal processing, genomics, proteomics, robot control, information retrieval, image analysis, analog circuit design and software engineering.