SIAM International Conference on Data Mining Student Travel Awards 2012

Northeastern University, Boston MA

Investigators

Abstract

SIAM International Conference on Data Mining Student Travel Awards 2012, PI: Jennifer Dy, Northeastern University. The project provides NSF Student Travel Fellowships to graduate students enrolled in PhD programs in data mining or closely related areas to attend and participate in the 2012 SIAM Data Mining (SDM 2012) Conference organized by the Society for Industrial and Applied Mathematics (SIAM) in cooperation with the American Statistical Association in Anaheim, California, USA from April 26 to 28, 2012. Special efforts will be made to attract women and members of groups that are underrepresented within the data mining research community. The NSF student travel award recipients will be able to attend the plenary and contributed talks, workshops and tutorials that are part of SDM 2012, as well as a Doctoral Forum. The Doctoral Forum is designed to allow doctoral students who are at an early stage in their research careers to present their work, interact with their peers from other universities as well as receive one-on-one mentoring from leading data mining researchers. Intellectual Merit. Participation in premier research conferences is an essential component of research-based advanced training of Ph.D. students in data mining. The SDM 2012 Doctoral Student Forum provides an opportunity for Ph.D. candidates to receive constructive feedback and mentoring from established researchers in data mining. Such interactions serve to broaden the training of students, enhance the quality of the dissertation research performed by the students at their home institutions, and ultimately, help them make informed decisions that advance their long-term career objectives. Broader Impact. Data mining is playing an increasingly important role in many emerging data-rich applications ranging from computational biology to computer-assisted discovery and counterterrorism efforts. The award will help broaden the representation of women and members of underrepresented minority groups within the Data Mining research community. It also contributes to the training of a cadre of new generation scientists equipped with sophisticated tools to extract knowledge from data in areas that are growing in importance in our increasingly digital, interconnected world.