Austin R. Benson

I'm a postdoc at Cornell University in the Department of Computer Science. In July 2018, I will start as an assistant professor in the department.

My research develops computational frameworks for analyzing large-scale and complex datasets coming from the Web, social networks, biology, and other scientific domains. This involves a combination of network science, matrix and tensor computations, data mining, machine learning, algorithm design, and high-performance computing.

Curriculum Vitae

Contact

arb@cs.cornell.edu
413B Bill & Melinda Gates Hall
@austinbenson
arbenson

07.01.2017. I graduated from Stanford and moved to Cornell CS!
02.27.2017. David Gleich and I co-organized a minisymposium on eigenvectors and decompositions of structured tensors at SIAM CSE17.

Upcoming and recent talks

12.16.2017. CMStatistics session on provable tensor methods in machine learning.
10.27.2017. Cornell Center for Applied Math (CAM) colloquium.
10.15.2017. Data Institute SF annual conference (DSCO17).
10.04.2017. Purdue University.
09.18.2017. Cornell Scientific Computing and Numerics (SCAN) seminar. [slides]
07.13.2017. SIAM workshop on network science. [slides]
06.17.2017. Householder Symposium on Numerical Linear Algebra. [slides]

Preprints and accepted papers

Higher-order clustering in networks.
Hao Yin, Austin R. Benson, and Jure Leskovec.
arXiv:1704.03913, 2017.
paper pdf

Peer-reviewed and published papers

Local higher-order graph clustering.
Hao Yin, Austin R. Benson, Jure Leskovec, and David F. Gleich.
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017.
paper pdf code data
Motifs in temporal networks.
Ashwin Paranjape*, Austin R. Benson*, and Jure Leskovec. (*co-first authors)
Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2017.
paper pdf poster pdf code data
The spacey random walk: a stochastic process for higher-order data.
Austin R. Benson, David F. Gleich, and Lek-Heng Lim.
SIAM Review (Research Spotlights) 59:2, 321–345, 2017.
paper pdf code
Higher-order organization of complex networks.
Austin R. Benson, David F. Gleich, and Jure Leskovec.
Science, 353.6295, 163–166, 2016.
paper pdf supplement code data
General tensor spectral co-clustering for higher-order data.
Tao Wu, Austin R. Benson, and David F. Gleich.
Proceedings of Neural Information Processing Systems (NIPS), 2016.
paper pdf code
On the relevance of irrelevant alternatives.
Austin R. Benson, Ravi Kumar, and Andrew Tomkins.
Proceedings of the International Conference on World Wide Web (WWW), 2016.
paper pdf
Modeling user consumption sequences.
Austin R. Benson, Ravi Kumar, and Andrew Tomkins.
Proceedings of the International Conference on World Wide Web (WWW), 2016.
paper pdf
Improving the numerical stability of fast matrix multiplication.
Grey Ballard, Austin R. Benson, Alex Druinksy, Benjamin Lipshitz, and Oded Schwartz.
SIAM Journal on Matrix Analysis and Applications, 37:4, 1382–1418, 2016.
paper pdf code
Tensor spectral clustering for partitioning higher-order network structures.
Austin R. Benson, David F. Gleich, and Jure Leskovec.
Proceedings of the SIAM International Conference on Data Mining (SDM), 2015.
paper pdf code
A framework for practical parallel fast matrix multiplication.
Austin R. Benson and Grey Ballard.
Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2015.
paper pdf code
Scalable methods for nonnegative matrix factorizations of near-separable tall-and-skinny matrices.
Austin R. Benson, Jason D. Lee, Bartek Rajwa, and David F. Gleich.
Proceedings of Neural Information Processing Systems (NIPS), 2014.
Selected for spotlight presentation.
paper pdf poster pdf code data
Learning multifractal structure in large networks.
Austin R. Benson, Carlos Riquelme, and Sven Schmit.
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2014.
paper pdf supplement
A parallel directional Fast Multipole Method.
Austin R. Benson, Jack Poulson, Kenneth Tran, Björn Engquist, and Lexing Ying.
SIAM Journal on Scientific Computing, 36:4, C335–C352, 2014.
paper pdf code
Silent error detection in numerical time-stepping schemes.
Austin R. Benson, Sven Schmit, and Robert Schreiber.
International Journal of High Performance Computing Applications, 29: 403–421, 2014.
paper pdf supplement code
Direct QR factorizations for tall-and-skinny matrices in MapReduce architectures.
Austin R. Benson, David F. Gleich, and James Demmel.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData), 2013.
paper pdf code

Theses

Tools for higher-order network analysis.
Austin Reilley Benson.
Stanford PhD thesis, 2017.
Stanford ICME Gene Golub Doctoral Dissertation Award winner.
paper pdf