Data Science

Harnessing the Power of “Big Data” Heading link

test

LAS is exploring the intersection of theoretical and experimental research in the field of Data Science.

  • GPU Computer Cluster

    The College recently invested in a high-performance GPU cluster to enable large scale number analysis. This computer system is now among the most powerful computers in the world. Among the early users will be Professor and LAS Endowed Chair in the Natural Sciences Huan-Xiang Zhou, whose work on protein structure and interaction depends on the theoretical prediction of dynamics of proteins and protein complexes within their native environment. Similarly, large scale analysis of structure-activity relationships of new drugs and their putative targets will now be possible.

  • Innovative Collaborations

    Beyond chemistry, we anticipate that researchers in the natural sciences and social science will be able to extend their work and collaborate with established investigators in areas of medicine, business, and industry. We envision that this new capability will open up various cross-disciplinary opportunities for research at LAS and across campus.

  • Transunion® Partnership

    Our Statisticians and Computer Scientists in the Department of Mathematics, Statistics, and Computer Science are active in theoretical and methodological research in data science, as well as its application in medicine and finance.  In addition, through a generous endowment from TransUnion, a Chicago-based information firm, we will be recruiting a TransUnion Professor, who will be housed in our Department of Mathematics, Statistics, and Computer Science, to help foster Data Science research and education efforts at our University.

LAS recently invested in Nvidia Tesla GPU Computing capabilities that will compliment UIC’s existing high performance computing cluster (HPC). Nvidia Tesla is specifically designed for HPC and exhibits superior performance and high reliability. Touching each of the LAS research strengths, the NVIDIA® Tesla™ GPU will enable a wide variety of research questions to progress in ways that were previously impractical due to technological limitations.