I'm currently a postdoc at Cornell University, working with Jon Kleinberg. In July 2018, I will start as an assistant professor in the department of Computer Science at Cornell University.
My research develops computational frameworks for analyzing largescale and complex datasets coming from the Web, social networks, biology, and other scientific domains. This uses a combination of network science, matrix and tensor computations, data mining, machine learning, algorithm design, and highperformance computing. Lately, I have focused on developing the foundations of higherorder data analysis.
Upcoming and recent events

06.07.2018. I am organizing a minisymposium on Mining and Modeling Network Data at SIAM Discrete Mathematics '18 in Denver. 
05.04.2018. I am giving a minitutorial on Tensor Eigenvectors and Stochastic Processes with David Gleich at SIAM ALA '18 in Hong Kong. 
02.27.2017. I coorganized a minisymposium on Eigenvectors and Decompositions of Structured Tensors with David Gleich at SIAM CSE '17 in Atlanta.
Upcoming and recent talks

07.09.2018. SIAM Annual 
06.07.2018. SIAM Discrete Mathematics 
06.04.2018. Conference on Statistical Learning and Data Science / Nonparametric Statistics 
12.17.2017. CMStatistics session on provable tensor methods in machine learning [slides] 
10.27.2017. Cornell Center for Applied Math (CAM) colloquium [slides] 
10.16.2017. Data Institute SF annual conference (DSCO17) [slides] 
10.04.2017. Purdue University Center for Science of Information seminar [slides] 
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]
Papers
Preprints
Simplicial closure and higherorder link prediction.
Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg.
arXiv:1802.06916, 2018.
paper pdf code dataHigherorder clustering in networks.
Hao Yin, Austin R. Benson, and Jure Leskovec.
arXiv:1704.03913, 2018.
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Peerreviewed and published papers
A Discrete Choice Model for Subset Selection.
Austin R. Benson, Ravi Kumar, and Andrew Tomkins.
Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2018.
paper pdf code data posterLocal higherorder 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 dataMotifs in temporal networks.
Ashwin Paranjape*, Austin R. Benson*, and Jure Leskovec. (*cofirst authors)
Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2017.
paper pdf code data posterThe spacey random walk: a stochastic process for higherorder data.
Austin R. Benson, David F. Gleich, and LekHeng Lim.
SIAM Review 59:2, 321–345, 2017.
paper pdf code dataHigherorder organization of complex networks.
Austin R. Benson, David F. Gleich, and Jure Leskovec.
Science, 353.6295, 163–166, 2016.
paper pdf supplement code dataGeneral tensor spectral coclustering for higherorder data.
Tao Wu, Austin R. Benson, and David F. Gleich.
Proceedings of Neural Information Processing Systems (NIPS), 2016.
paper pdf codeOn 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 pdfModeling user consumption sequences.
Austin R. Benson, Ravi Kumar, and Andrew Tomkins.
Proceedings of the International Conference on World Wide Web (WWW), 2016.
paper pdfImproving 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 codeTensor spectral clustering for partitioning higherorder network structures.
Austin R. Benson, David F. Gleich, and Jure Leskovec.
Proceedings of the SIAM International Conference on Data Mining (SDM), 2015.
paper pdf codeA 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 codeScalable methods for nonnegative matrix factorizations of nearseparable tallandskinny 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 code data posterLearning 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 supplementA 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 codeSilent error detection in numerical timestepping schemes.
Austin R. Benson, Sven Schmit, and Robert Schreiber.
International Journal of High Performance Computing Applications, 29: 403–421, 2014.
paper pdf supplement codeDirect QR factorizations for tallandskinny 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 higherorder network analysis.
Austin Reilley Benson.
Stanford PhD thesis, 2017.
Stanford ICME Gene Golub Doctoral Dissertation Award winner .
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