Faculty Renewal

The new Center will not only be the focal point for the faculty renewal effort, but will also help coordinate many data science activities across Cornell. One mechanism for advancing “radical collaboration” would be to have the Center be the home for multiple 1-week boot camps prior to the start of each semester; the aim of these would be to solicit Cornell faculty proposals for a coordinated set of research initiatives that bring together Cornell faculty as well as external counterparts from our peer institutions, industry, government, and Non-Governmental Organizations (NGO) (including the rising next generation of scholars, paying particular attention to attracting as diverse a group as possible).

Coordination

The Center will play a coordinating and leading role in the pursuit of inter- and intra-institutional external funding opportunities. NSF has termed “Harnessing the Data Revolution” one of its current 10 “big ideas” and there are a growing number of cross-cutting initiatives already started and planned for the coming years. For example, Cornell is one of 10 sites for the initial round of Phase I TRIPODS grants, where it is anticipated that partnerships among “pods” of these funded teams (each spanning Computer Science, Engineering, Statistics, and Mathematics) will compete next year for 2-3 new NSF Data Science Institutes (structured along the lines that the NSF Math Sciences Research Institutes exist currently, including, for example, MSRI at Berkeley, IPAM at UCLA, and ICERM at Brown); two further NSF “institute-level” tracks for funding have already been announced with preliminary stages, one geared for building intra-institutional teams, and another geared to create inter-institutional analog (and in contrast to the “methodologically-driven” TRIPODS, these new calls promote more of a balance with being “application-driven” as well). Furthermore, there are significant opportunities for partnership with industry, NGO’s and government. Further offerings in new areas will bring data science into the classroom in new domains. Industry is eager to partner with Cornell in these domains for two primary reasons – visibility to our students, and engagement with our research talent.

Connection to Cornell Tech

Cornell Tech is an important element of any initiative in data science. Not only does its engagement mission provides many opportunities that can find their way “upstream” to Ithaca in this area, but also because this is an area in which there is already a well-developed level of coordination between these two campuses. For example, it is envisioned that, although the majority of the steady-state cohort of 9 Assistant Research Professors will be based in Ithaca, there would be tremendous benefit for having some be 80/20 and 50/50 splits with Cornell Tech. More generally, the Center will be an additional mechanism to integrate research activities in data science between the two campuses.

Educational Component

Although the Center will be primarily a research-focused entity, it will play a contributing role in the full range of Cornell educational programs. In the simplest case, there is a pressing need to establish a Graduate Field of Data Science, initially as just a minor-only field, but likely expanding to be a doctorate-granting field. There is a definite need to coordinate the development and integration of undergraduate curricula and programs across all units – the impact of the data revolution is being felt by undergraduate students in all of Cornell’s colleges, and programs should respond in a coordinated way.

Radical Collaborations

Finally, data science should interface with the data-infused aspects of other radical collaborations so as to be sure that their respective efforts are coordinated to maximum effect; this is particularly important for digital agriculture, genome biology, sustainability, and infection biology.

Each of these elements has the Center playing the role of a “focal point”. Having a corresponding space to do this will be very important. This is particularly critical in creating a “sandbox” for transdisciplinary work that would place the strongest Cornell “stamp” on it, in which the cohorts of Assistant Research Professors would create new domains for their work, by bringing scholars with diverse data science interests to rub shoulders.

The radical collaborations provide a means to build on areas of Cornell world leadership by new investments in recruiting faculty. For a discipline as interdisciplinary as data science, there is a need to also build the associated infrastructure that will help further leverage this current strength, by creating a differentiating environment into which Cornell will attract the strongest emerging scholarship. In this aspect, data science is not so different from, for example, sustainability, where Cornell already has its Atkinson Center to provide a coordinating function that all of the campus can look to for leadership.