Education Duke University Ph.D. in Computer Science, January, 2009. Thesis Title: Small and Stable Descriptors of Distributions for Geometric Statistical Problems. Advisor: Pankaj K. Agarwal. Rice University Bachelor of Science in Computer Science, May 2003. Bachelor of Arts in Mathematics, May 2003. Research Experience University of Utah, School of Computing (Assistant Professor) (2011-present) University of Utah, School of Computing (Postdoctoral CI Fellow) (2009-2011) Duke University, Department of Computer Science (Postdoctoral Associate) (2009) Duke University, Department of Computer Science (Research Assistant) (2003-2009) Yahoo! Research (Research Intern) (Summer 2007) AT&T Research (Visiting Researcher) (Summer/Winter 2005) Rice University, Department of Computer Science (Research Assistant) (2000-2003) The Charles Stark Draper Laboratory, Inc. (Research Scientist) (2002-2003) Fellowships and Awards NSF CAREER Award. (2014) Best Paper Award at MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings. (2011) CCC-CRA-NSF Computing Innovation Fellowship. (2009) 2 year postdoctoral fellowship — 60 awarded among all graduating computer scientists in US Best Student Paper at International Conference on Automata, Languages and Programming (ICALP). (2008) Distinguished Department Service Award (Duke Computer Science). (2008) For 5 years of department service — never before awarded Outstanding Department Service Award (Duke Computer Science). (2006) NSF Graduate Research Fellowship. (2004-2007) 3 year full graduate fellowship James B. Duke Fellowship. (2003-2007) 4 years partial Duke graduate fellowship C. S. Draper Laboratory Fellowship. (2003-2007) 4 year full graduate fellowship — declined James S. Waters Creativity Award. (2002) Annual Rice Undergraduate Research Award NASA/Texas Space Grant Consortium Undergraduate Scholarship. (2002) Annual Texas Undergraduate Research Award Brown Undergraduate Research Internship Award. (May 2001, September 2001) Rice Undergraduate Research Award, won twice Book Chapters and Surveys [S1] Coresets and Sketches (to appear). Jeff M. Phillips. Handbook of Discrete and Computational Geometry, 3rd edition, CRC Press, Chapter 49. 2016. [S2] A Gentle Introduction to the Kernel Distance. Jeff M. Phillips and Suresh Venkatasubramanian. arXiv:1103.1625, March 2011. Conference/Journal Publications [C1] Streaming Kernel Principal Component Analysis. Mina Ghashami, Daniel Perry, and Jeff M. Phillips. International Conference on Artificial Intelligence and Statistics (AISTATS), [31%] May 2016. arXiv:1512.05059, December 2015. [C2] Subsampling in Smooth Range Spaces. Jeff M. Phillips and Yan Zheng. Algorithmic Learning Theory (ALT), [50%] October 2015. [C3] L∞ Error and Bandwidth Selection for Kernel Density Estimates of Large Data. Jeff M. Phillips and Yan Zheng. ACM Conference on Knowledge Discovery and Data Mining (KDD), [19%] August 2015. [C4] Geometric Inference on Kernel Density Estimates. Jeff M. Phillips, Bei Wang, and Yan Zheng. International Symposium on Computational Geometry (SoCG), [38%] June 2015. arXiv:1307.7760, January 2014. [C5] Improved Practical Matrix Sketching with Guarantees. Mina Ghashami, Amey Desai, and Jeff M. Phillips. 22nd Annual European Symposium on Algorithms (ESA), [25%] September 2014. extended version as arXiv:1501.06561, January 2015.