The emergence of Data Science has led to a flourishing of initiatives, centers, degrees, programs and organizational units at educational and research institutions around the world. The demand for data science know-how from students, parents, scientists and employers is strong and getting stronger. However, the interdisciplinary nature of the topic and the lack of a consensus around its definition raise challenges for its implementation in the modern university setting.
Faculty and graduate students are invited to a roundtable discussion with Gyana R. Parija, IBM’s Manager of Analytics & Optimization Research and Global Research Lead, Collaborative Cognition Research at IBM Research. At this roundtable, Gyana will discuss recent IBM research initiatives in AI, and then explore areas of mutual interest for possible collaboration. Please consider attending if your research interests include these topics.
Today, most application developers write code without much regard for how quickly it will run. Moreover, once the code is written, it is rare for it to be reengineered to run faster. But two technology trends of historic proportions are instigating a resurgence in software performance engineering, the art of making code run fast. The first is the emergence of cloud computing, where the economics of renting computation, as opposed to buying it, heightens the utility of application speed.