The project supports graduate student participation in the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2011). Specifically, the project supports travel to the conference for students who might not otherwise be able to attend the conference because of financial reasons. The recipients of student travel fellowships will have an opportunity to attend the conference, associated workshops and tutorials on emerging research topics, as well as a doctoral consortium that provides a venue for the students to have one-on-one discussions and receive mentoring from some of the leading researchers in data mining, machine learning, and related topics. The project offers natural integration of research and education and contributes to the training of a new generation of researchers in an area of growing importance and impact in not only Computer Science but also a variety of data-driven disciplines.
1 Overview The grant is used to support for US students to attend ACM SIGKDD conference 2011. The annual ACM SIGKDD conference is the premier international forum for data mining researchers and practitioners from academia, industry, and government to share their ideas, research results and experiences. KDD 2011 features keynote presentations, oral paper presentations, poster sessions, workshops, tutorials, panels, exhibits, demonstrations, and the KDD Cup competition. KDD 2011 is held on August 21-24 in San Diego, CA and has attracted hundreds of practitioners and academic data miners converging on the one location. Strong student participation is a long-running tradition of KDD conference. To encourage and support students to attend the conference, we are funded with $20,000 from NSF in this grant. 2 Expense Summary This grant supports 27 students in total with $850 or $500 equivalent award. The total budget request from NSF is $20,000. In addition, SIGKDD matches the funding from NSF to support student registration, student activities including doctoral forum/poster session and to solicit other student travel support from company sponsorship. SIGKDD conference has also received student travel support from companies including IBM and Google. 3 Selection Criteria and Awardee List Travel awards are selected based on the following selection priority by the conference organizing committee: 1. Student authors to KDD conference: a. We will give the priority to the students who do not have any funding support from either their institutions or their advisors. b. We will give the priority to the ones whose paper received the highest score. 2. If there is funding left, we will give it to non-author students, as long as they have at least one paper in a major data mining or database conference (KDD, PKDD, ICDM, PAKDD, SDM, SIGMOD, VLDB, ICDE, ICML, NIPS), with priorities ranking as follows: a. Female and minority students b. Students who helped on organizing the workshops as student reviewers c. Students who published in the related topics on large scale data mining. The awardee supported by this NSF grant include: Aditya Menon (UCSD), Alina Ene (UCSD) Chong Wang (Princeton), Chunyu Luo (Rutgers), Dan Zhang (Purdue), Mahashweta Das (UT Arlington), Debprakash Patnaik (Virginia Tech), Feng Chen (Virginia Tech), Galileo Namata (U Maryland), Liangjie Hong (Lehigh Univ.), Jianhui Chen (ASU), Kai-Wei Chang (UIUC), Khalid Elarini (CMU), Mao Ye (Penn State), Parik-shit Ram (Georgia Tech), Pritam Gundecha (ASU), Xiangnan Kong (UIC), Xiaoxiao Shi (UIC), Yucheng Low (CMU), Vinod Vydiswaran (UIUC), Dashun Wang (Northeastern Univ.), Xueyuan Zhou (U Chicago), Saurabh Kataria (Penn State), Cho-Jui Hsieh (UT Austin), Eric Yi Liu (UNC), Jiayu Zhou (ASU), Huahua Wang (UMN). 4 Mentoring program All award recipients are invited to present at a special doctorate poster session about their overall research, which is independent to the presentations on their KDD papers or posters. Senior KDD researchers are matched to the student to provide mentoring advice regarding students’ research during this doctorate event. 5 Broad Impact The student support award funded by this grant has attract many US students to participate in this conference and present their works, and encouraged them to focus on the extremely promising research direction of data mining as their thesis research. More than 10% of the supported students are female and minority students
