Information


       

Schedule

Invited Speakers

  • Sepehr Assadi (University of Pennsylvania)

    Sepehr Assadi is a PhD student in Computer science at University of Pennsylvania, advised by Sanjeev Khanna. His research interests are primarily on theoretical foundations of big data analysis and in particular streaming and distributed algorithms and lower bounds. He is also interested in areas of approximation and online algorithms, communication complexity, and algorithmic game theory. He obtained his B.Sc degree from Sharif University of Technology in 2013. Sepehr has received the best paper awards at WINE 2015 and SPAA 2017, and the best student paper award at PODS 2017.

  • Vladimir Braverman (Johns Hopkins University)

    Vladimir Braverman is an Assistant Professor in the Department of Computer Science in the Whiting School of Engineering at the Johns Hopkins University. He received his PhD from UCLA in 2011. His main research interests include streaming and sketching algorithms. His research has been supported by DARPA, NSF, Google, Cisco, and Nvidia. Braverman received NSF CAREER Award in 2017.

  • Ken Clarkson (IBM Research, Almaden)

    Ken Clarkson has been a Research Staff Member at the IBM Almaden Research Center since 2007, and is manager of the theory group there. He was a Member of Technical Staff at Bell Labs from 1984 until 2007, after receiving his Ph.D. in computer science from Stanford University and BA in mathematics from Pomona College. His research has largely been in geometric algorithms and numerical linear algebra, with a sabbatical on tools for cellular basestation optimization. He was principal investigator for a DARPA project on sketching-based matrix computations, the recipient of Best Paper Awards at the Vehicular Technology Conference 2006 and STOC 2013, and is a Fellow of the ACM. He has held a First-Class Radio-Telephone Operator's License.

  • Huy Nguyen (Northeastern University)

    Huy Le Nguyen is an Assistant Professor of Computer Science in the College of Computer and Information Science at Northeastern University. Prior to joining Northeastern, he was a Research Assistant Professor at the Toyota Technological Institute in Chicago and before that, a Google Research Fellow at the Simons Institute at University of California, Berkeley. He received his PhD in Computer Science from Princeton University. Professor Nguyen is broadly interested in the design and analysis of algorithms, with an emphasis on algorithmic techniques for massive data sets and machine learning.

  • Michael Kapralov (École Polytechnique Fédérale de Lausanne)

    Michael Kapralov is an Assistant Professor in the School of Computer and Communication Sciences at EPFL. Michael obtained his Ph.D. from Stanford University in 2012, after which he spent two years as a postdoc in the Theory of Computation Group at MIT CSAIL, and a year as a Herman Goldstine Postdoctoral Fellow at the IBM T.J. Watson Research Center. He is broadly interested in theoretical computer science, with an emphasis on theoretical foundations of big data analysis. Most of his algorithmic work is in sublinear algorithms, where specific directions include streaming, sketching, sparse recovery and Fourier sampling.

  • Eric Price (University of Texas, Austin)

    Eric Price

Organizers and Support

Organizers:

  • Andrew McGregor (University of Massachusetts, Amherst)

    Andrew McGregor is an Associate Professor at the University of Massachusetts, Amherst. He received a B.A. degree and the Certificate of Advance Study in Mathematics from the University of Cambridge and a Ph.D. from the University of Pennsylvania. He also spent a couple of years as a post-doc at UC San Diego and Microsoft Research SVC. He is interested in many areas of theoretical computer science and specializes in data stream algorithms, linear sketching, and communication complexity. He received the NSF Career Award in 2010.

  • David Woodruff (Carnegie Mellon University)

    David Woodruff is an Associate Professor at Carnegie Mellon University in the School of Computer Science. Prior to that he spent ten years at the IBM Almaden Research Center, which he joined in 2007 after completing his Ph.D. at MIT in theoretical computer science. His research interests include communication complexity, data stream algorithms, machine learning, numerical linear algebra, sketching, and sparse recovery. He is the author of the book "Sketching as a Tool for Numerical Linear Algebra". He is a recipient of the 2014 Presburger Award and Best Paper Awards at STOC 2013 and PODS 2010. At IBM he was a member of the Academy of Technology and a Master Inventor.

  • Grigory Yaroslavtsev

    Grigory Yaroslavtsev is an assistant professor of Computer Science at Indiana University. Prior to that he was a postdoctoral fellow at the Warren Center for Network and Data Sciences at the University of Pennsylvania. He was previously a Postdoctoral Fellow in Mathematics at Brown University, ICERM. He received his Ph.D. in Theoretical Computer Science in 2014 from Pennsylvania State University and an M.Sc. in Applied Mathematics and Physics from the Academic University of the Russian Academy of Sciences in 2010. Grigory works on efficient algorithms for sparsification, summarization and testing properties of large data, including approximation, parallel and online algorithms, learning theory and property testing, communication and information complexity and private data release.