Deeparnab Chakrabarty received his B. Tech. from IIT Bombay in 2003 and Ph.D. from Georgia Institute of Technology in 2008. His graduate adviser was Vijay V. Vazirani. After stints at the universities of Waterloo and Pennsylvania, he crossed the pond again to join Microsoft Research in Bangalore where he has been a researcher since 2011. He is interested in understanding efficient algorithms using the lens of optimization and has worked on approximation algorithms, property testing, and on algorithmic questions arising in game theory and economics.

C. Seshadhri (Seshadhri Comandur according to his passport, and Sesh according to his friends) follows the common naming style of South India, the native land of his parents. In three of his early papers, including one cited in this bibliography, his name appears as S. Comandur. The interested reader is invited to consult the OAQ (Occasionally Asked Questions) section of his website for more details. Sesh got his B. Tech. from IIT Kanpur in 2003 and his Ph.D. from Princeton University in 2008. His Ph.D. advisor was Bernard Chazelle. He spent two years at IBM Almaden, and in 2010 he became a member of technical staff at Sandia National Laboratories, Livermore, California. In 2015 he joins the faculty of the University of California at Santa Cruz. This paper was written during his time at Sandia. His research focuses on how random sampling can be used for algorithms for massive inputs. In theory, this manifests itself as work in property testing. In practice, this has led to research on algorithms for massive real-world graphs. He is increasingly interested in algorithmics beyond the worst-case, and bridging the gap between theory and practice for big data applications.