SIAM International Conference on Data Mining Student Travel Awards 2012

2012年暹罗国际数据挖掘学生旅行奖，PI：Jennifer Dy，东北大学。该项目为注册数据挖掘或密切相关领域博士项目的研究生提供NSF学生旅行奖学金，以参加由工业与应用数学学会(SIAM)与美国统计协会于2012年4月26日至28日在美国加利福尼亚州阿纳海姆举办的2012年SIAM数据挖掘(SDM 2012)会议。将特别努力吸引妇女和在数据挖掘研究界任职人数不足的群体成员。NSF学生旅行奖获得者将能够参加全体会议并贡献演讲、研讨会和教程，这些都是SDM 2012的一部分，以及一个博士论坛。博士论坛旨在让处于研究生涯早期的博士生展示自己的工作，与其他大学的同行互动，并从领先的数据挖掘研究人员那里获得一对一的指导。参加首屈一指的研究会议是博士生数据挖掘研究型高级培训的重要组成部分。SDM 2012博士生论坛为博士生提供了一个机会，从数据挖掘领域的知名研究人员那里获得建设性的反馈和指导。这种互动有助于拓宽学生的培训范围，提高学生在本国机构进行的论文研究的质量，并最终帮助他们做出明智的决定，以推进他们的长期职业目标。更广泛的影响。数据挖掘在许多新兴的数据丰富的应用中发挥着越来越重要的作用，从计算生物学到计算机辅助发现和反恐努力。该奖项将有助于扩大妇女和数据挖掘研究社区中代表性不足的少数群体的成员的代表性。它还有助于培训配备了先进工具的新一代科学家队伍，以便从我们日益数字化和相互联系的世界中日益重要的领域的数据中提取知识。

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.