Program Committee
- Sanjukta Bhowmick, University of North Texas
- Jee Choi, Georgia Institute of Technology
- Rezaul Chowdhury, State University of New York at Stony Brook
- Fabien Dufoulon, Lancaster University
- Lionel Eyraud-Dubois, LaBRI -- Inria Bordeaux Sud-Ouest
- Pierre Fraigniaud, Université Paris Cité and CNRS
- Quanquan Liu, Northwestern University
- Samuel McCauley, Williams College
- Othon Michail, University of Liverpool
- Achour Mostéfaoui, Université Nantes (LINA)
- Yusuke Nagasaka, Fujitsu Limited
- Lata Narayanan, Concordia University
- Manuel Penschuck, Goethe University Frankfurt
- Cynthia Phillips, Sandia National Laboratories
- Kirk Pruhs, University of Pittsburgh
- Shikha Singh, Williams College
- Vaishali Surianarayanan, UCSB
- Flavio Vella, University of Trento
- Helen Xu, Georgia Tech
- Albert-Jan Yzelman, Huawei Technologies France
Focus
- Design, analysis, and engineering of distributed and parallel algorithms
- Theoretical foundations, models, and complexity issues
- Data structures for parallel and distributed algorithms
- Emerging paradigms for parallel and distributed computation
- Theory and algorithms for emerging parallel/distributed architectures
- Lower bounds for parallel/distributed computing
- Approximation and randomized algorithms
- Algorithms for combinatorial and graph problems
- Algorithms for sparse and dense numerical linear algebra
- Algorithms and models for Big Data/Data-intensive computing
- Algorithms for routing and information dissemination in networks
- Algorithms for social networks
- Algorithms for dynamic networks
- Algorithms for cloud and edge computing
- Fault-tolerant and self-stabilizing algorithms
- Power/energy-efficient algorithms
- Tensor operations, low-rank approximation
- Theoretical aspects of dependable, secure, and privacy-preserving distributed systems
- Parallel/distributed aspects of learning and mining algorithms
- Theoretical aspects of emerging architectures
