Austin R. Benson
Assistant Professor of Computer Science
Field Member of Applied Math and Data Science
Cornell University
arb@cs.cornell.edu
413B Bill & Melinda Gates Hall
@austinbenson
arbenson
Broadly, my research focuses on developing numerical, computational,
and algorithmic frameworks for analyzing complex data in an effort
to better understand how the world is connected and how people make
decisions.
[Curriculum Vitae]
My research is generously supported by the Army Research Office and the National Science Foundation.
News and events
 Quanta Magazine covered some of our work on higherorder network analysis in the article How Big Data Carried Graph Theory Into New Dimensions.
 I am very honored to receive an NSF CAREER Award.
 Higherorder Network Analysis Takes Off, Fueled by Old Ideas and New Data (with David Gleich and Des Higham) was published in SIAM News and gives a highlevel overview of the emergence, mathematics, and opportunities of the higherorder network analysis research area.
Upcoming and recent talks

07.21.2021. Minisymposium on Graph Theory and Machine Learning at SIAM Conference on Discrete Mathematics. [slides] 
07.20.2021. Conference of the International Society for Clinical Biostatistics. [slides] 
07.14.2021. EURO 2021: European Conference on Operational Research. [slides] 
07.02.2021. HONS 2021: HigherOrder Models in Network Science (satellite at NetSci/Networks). [slides] 
06.28.2021. DynaMo: Dynamics and motifs (satellite at NetSci/Networks). [slides] 
05.17.2021. GrAPL 2021: IPDPS Workshop on Graphs, Architectures, Programming, and Learning. [slides] 
05.07.2021. Worcester Polytechnic Institute. [slides] 
03.12.2021. Machine Learning with Graphs at Northeastern. [slides] 
02.23.2021. RelationalAI. [slides] 
01.09.2021. Session on Applied Combinatorial Methods at JMM. [slides]
Teaching & Education
Cornell classes
SP 2021. CS 4220/Math 4260: Numerical Analysis: Linear and Nonlinear Problems.FA 2020. CS 6210: Matrix Computations.SP 2020. CS 6241: Numerical Methods for Data Science.FA 2019. CS 2850/INFO 2040/ECON 2040/SOC 2090: Networks.SP 2019. CS 6241: Numerical Methods for Data Science.FA 2018. CS 2850/INFO 2040/ECON 2040/SOC 2090: Networks.
Expository material
 Cornell SoNIC workshop: research lab notebooks.
 Higherorder Network Analysis Takes Off, Fueled by Old Ideas and New Data article in SIAM News 2021 (with David Gleich and Des Higham).
 SIAM ALA '18 tutorial on Tensor Eigenvectors and Stochastic Processes (with David Gleich).
[web] [slides] [code]
Papers
Preprints
Higher Order Information Identifies Tie Strength.
Arnab Sarker, JeanBaptiste Seby, Austin R. Benson, Ali Jadbabaie.
arXiv:2108.02091, 2021.
paper pdffauciemail: a json digest of Anthony Fauci's released emails.
Austin R. Benson, Nate Veldt, David F. Gleich.
arXiv:2108.01239, 2021.
paper pdf code dataEdge Proposal Sets for Link Prediction.
Abhay Singh, Qian Huang, Sijia Linda Huang, Omkar Bhalerao, Horace He, SerNam Lim, Austin R. Benson.
arXiv:2106.15810, 2021.
paper pdf codeGraph Belief Propagation Networks.
Junteng Jia, Cenk Baykal, Vamsi K. Potluru, Austin R. Benson.
arXiv:2106.03033, 2021.
paper pdf codeA Nonlinear Diffusion Method for Semisupervised Learning on Hypergraphs.
Francesco Tudisco, Konstantin Prokopchik, Austin R. Benson.
arXiv:2103.14867, 2021.
paper pdfHigherorder Homophily is Combinatorially Impossible.
Nate Veldt, Austin R. Benson, Jon Kleinberg.
arXiv:2103.11818, 2021.
paper pdf codeOverparametrized neural networks as underdetermined linear systems.
Austin R. Benson, Anil Damle, Alex Townsend.
arXiv:2010.15959, 2020.
paper pdfA simple bipartite graph projection model for clustering in networks.
Austin R. Benson, Paul Liu, Hao Yin.
arXiv:2007.00761, 2020.
paper pdf codeAugmented Sparsifiers for Generalized Hypergraph Cuts with Applications to Decomposable Submodular Function Minimization.
Austin R. Benson, Jon Kleinberg, Nate Veldt.
arXiv:2007.08075, 2020.
paper pdfIncrementally Updated Spectral Embeddings.
Vasileios Charisopoulos, Austin R. Benson, Anil Damle.
arXiv:1909.01188, 2019.
paper pdf code poster
Accepted and published research papers
Diverse and Experienced Group Discovery via Hypergraph Clustering.
Ilya Amburg, Nate Veldt, Austin R. Benson.
To appear at SIAM Data Mining (SDM) 2022.
paper pdf code dataHypergraph Cuts with General Splitting Functions.
Nate Veldt, Austin R. Benson, Jon Kleinberg.
To appear in SIAM Review (SIREV), 2022.
paper pdfA Unifying Generative Model for Graph Learning Algorithms: Label Propagation, Graph Convolutions, and Combinations.
Junteng Jia, Austin R. Benson.
To appear in SIAM Journal on Mathematics of Data Science (SIMODS), 2021.
paper pdf code dataApproximate Decomposable Submodular Function Minimization for CardinalityBased Components.
Nate Veldt, Austin R. Benson, Jon Kleinberg.
Advances in Neural Information Processing Systems (NeurIPS), 2021.
paper pdf codeCommunicationefficient distributed eigenspace estimation.
Vasileios Charisopoulos, Austin R. Benson, Anil Damle.
SIAM Journal on Mathematics of Data Science (SIMODS), 2021.
paper pdf codeGenerative hypergraph clustering: from blockmodels to modularity.
Philip S. Chodrow, Nate Veldt, Austin R. Benson.
Science Advances, 2021.
paper pdf code dataThe Generalized Mean Densest Subgraph Problem.
Nate Veldt, Austin R. Benson, Jon Kleinberg.
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2021.
paper pdf codeChoice Set Confounding in Discrete Choice.
Kiran Tomlinson, Johan Ugander, Austin R. Benson.
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2021.
paper pdf codeLearning Interpretable Feature Context Effects in Discrete Choice.
Kiran Tomlinson, Austin R. Benson.
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2021.
paper pdf code dataExpertise and Dynamics within Crowdsourced Musical Knowledge Curation: A Case Study of the Genius Platform.
Derek Lim, Austin R. Benson.
Proceedings of International Conference on Web and Social Media (ICWSM), 2021.
paper pdf code dataHigherorder Network Analysis Takes Off, Fueled by Old Ideas and New Data.
Austin R. Benson, David F. Gleich, Desmond J. Higham.
SIAM News, 2021.
article [expanded arXiv version]Combining Label Propagation and Simple Models Outperforms Graph Neural Networks.
Qian Huang, Horace He, Abhay Singh, SerNam Lim, Austin R. Benson.
Proceedings of the International Conference on Learning Representations (ICLR), 2021.
paper pdf codePlanted Hitting Set Recovery in Hypergraphs.
Ilya Amburg, Jon Kleinberg, Austin R. Benson.
Journal of Physics: Complexity (Special Issue on HigherOrder Structures in Networks and Network Dynamical Systems), 2021.
paper pdf code dataNonlinear HigherOrder Label Spreading.
Francesco Tudisco, Austin R. Benson, Konstantin Prokopchik.
Proceedings of The Web Conference (WWW), 2021.
paper pdf code videoRandom Graphs with Prescribed KCore Sequences: A New Null Model for Network Analysis.
Katherine Van Koevering, Austin R. Benson, Jon Kleinberg.
Proceedings of The Web Conference (WWW), 2021.
paper pdf code videoBetter Set Representations For Relational Reasoning.
Qian Huang, Horace He, Abhay Singh, Yan Zhang, SerNam Lim, Austin R. Benson.
Advances in Neural Information Processing Systems (NeurIPS), 2020.
paper pdf codeEntrywise Convergence of Iterative Methods for Eigenproblems.
Vasileios Charisopoulos, Austin R. Benson, Anil Damle.
Advances in Neural Information Processing Systems (NeurIPS), 2020.
paper pdf codeResidual Correlation in Graph Neural Network Regression.
Junteng Jia, Austin R. Benson.
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2020.
paper pdf code data [(G)PyTorch implementation from Junwen Bai and Yucheng Lu.]Minimizing Localized Ratio Cut Objectives in Hypergraphs.
Nate Veldt, Austin R. Benson, Jon Kleinberg.
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2020.
paper pdf code dataChoice Set Optimization Under Discrete Choice Models of Group Decisions.
Kiran Tomlinson, Austin R. Benson.
Proceedings of the International Conference on Machine Learning (ICML), 2020.
paper pdf code data slidesNeighborhood and PageRank methods for pairwise link prediction.
Huda Nassar, Austin Benson, David F. Gleich.
Social Network Analysis and Mining (SNAM), 2020
paper pdf codeNetwork Interpolation.
Thomas Reeves, Anil Damle, Austin R. Benson.
SIAM Journal on Mathematics of Data Science (SIMODS), 2020.
paper pdf codeMeasuring Directed Triadic Closure with Closure Coefficients.
Hao Yin, Austin R. Benson, Johan Ugander.
Network Science, 2020.
paper pdf codeRandom Walks on Simplicial Complexes and the normalized Hodge 1Laplacian.
Michael T. Schaub, Austin R. Benson, Paul Horn, Gabor Lippner, Ali Jadbabaie.
SIAM Review (SIREV), 2020.
paper pdf [Editor's overview]Clustering in graphs and hypergraphs with categorical edge labels.
Ilya Amburg, Nate Veldt, Austin R. Benson.
Proceedings of The Web Conference (WWW), 2020.
paper pdf code dataFrozen Binomials on the Web: Word Ordering and Langauge Conventions in Online Text.
Katherine Van Koevering, Austin R. Benson, Jon Kleinberg.
Proceedings of The Web Conference (WWW), 2020.
paper pdf codeUsing cliques with higherorder spectral embeddings improves graph visualizations.
Huda Nassar, Caitlin Kennedy, Shweta Jain, Caitlin Kennedy, Austin R. Benson, David F. Gleich.
Proceedings of The Web Conference (WWW), 2020.
paper pdf code videoRetrieving Top Weighted Triangles in Graphs.
Raunak Kumar, Paul Liu, Moses Charikar, Austin R. Benson.
Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2020.
paper pdf code dataNeural Jump Stochastic Differential Equations.
Junteng Jia, Austin R. Benson.
Advances in Neural Information Processing Systems (NeurIPS), 2019.
paper pdf code posterModeling and Analysis of Tagging Networks in Stack Exchange Communities.
Shangdi Yu, Xiang Fu, Austin R. Benson.
Journal of Complex Networks, 2019.
paper pdf code dataComputing tensor Zeigenvectors with dynamical systems.
Austin R. Benson, David F. Gleich.
SIAM Journal on Matrix Analysis and Applications (SIMAX), 2019.
paper pdf codeUnsupervised learning of dislocation motion.
Darren C. Pagan, Thien Q. Phan, Jordan S. Weaver, Austin R. Benson, Armand J. Beaudoin.
Acta Materialia, 2019.
paper pdfAutomated Grain Yield Behavior Classification.
Darren C. Pagan, Jakob Kaminsky, Wesley A. Tayon, Kelly E. Nygren, Armand J. Beaudoin, Austin R. Benson.
The Journal of The Minerals, Metals & Materials Society (JOM), 2019.
paper pdfPairwise Link Prediction.
Huda Nassar, Austin R. Benson, David F. Gleich.
Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2019.
Best Paper Award Runnerup .
paper pdf codeGraphbased SemiSupervised & Active Learning for Edge Flows.
Junteng Jia, Michael T. Schaub, Santiago Segarra, Austin R. Benson.
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2019.
paper pdf code poster videoNetwork Density of States.
Kun Dong, Austin R. Benson, David Bindel.
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2019.
Best Paper Award .
paper pdf code poster videoThree hypergraph eigenvector centralities.
Austin R. Benson.
SIAM Journal on Mathematics of Data Science (SIMODS), 2019.
paper pdf codeLink Prediction in Networks with CoreFringe Data.
Austin R. Benson, Jon Kleinberg.
Proceedings of the World Wide Web Conference (WWW), 2019.
paper pdf code posterChoosing to grow a graph: Modeling network formation as discrete choice.
Jan Overgoor, Austin R. Benson, Johan Ugander.
Proceedings of the World Wide Web Conference (WWW), 2019.
paper pdf code posterRandom Spatial Network Models with CorePeriphery Structure.
Junteng Jia, Austin R. Benson.
Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2019.
paper pdf code data posterSampling Methods for Counting Temporal Motifs.
Paul Liu, Austin R. Benson, Moses Charikar.
Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2019.
paper pdf code dataThe Local Closure Coefficient: A New Perspective On Network Clustering.
Hao Yin, Austin R. Benson, Jure Leskovec.
Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2019.
paper pdf codeSimplicial closure and higherorder link prediction.
Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, Jon Kleinberg.
Proceedings of the National Academy of Sciences (PNAS), 2018.
paper pdf supplement code dataFound Graph Data and Planted Vertex Covers.
Austin R. Benson, Jon Kleinberg.
Advances in Neural Information Processing Systems (NeurIPS), 2018.
paper pdf code data posterSequences of Sets.
Austin R. Benson, Ravi Kumar, Andrew Tomkins.
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2018.
paper pdf code data poster videoHigherorder clustering in networks.
Hao Yin, Austin R. Benson, Jure Leskovec.
Physical Review E (PRE), 2018.
paper pdf codeA Discrete Choice Model for Subset Selection.
Austin R. Benson, Ravi Kumar, 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, David F. Gleich.
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017.
paper pdf code data videoMotifs in temporal networks.
Ashwin Paranjape, Austin R. Benson, Jure Leskovec.
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, LekHeng Lim.
SIAM Review (SIREV), 2017.
paper pdf code dataHigherorder organization of complex networks.
Austin R. Benson, David F. Gleich, Jure Leskovec.
Science, 2016.
paper pdf supplement code dataGeneral tensor spectral coclustering for higherorder data.
Tao Wu, Austin R. Benson, David F. Gleich.
Advances in Neural Information Processing Systems (NeurIPS), 2016.
paper pdf codeOn the relevance of irrelevant alternatives.
Austin R. Benson, Ravi Kumar, Andrew Tomkins.
Proceedings of the International Conference on World Wide Web (WWW), 2016.
paper pdfModeling user consumption sequences.
Austin R. Benson, Ravi Kumar, 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, Oded Schwartz.
SIAM Journal on Matrix Analysis and Applications (SIMAX), 2016.
paper pdf codeTensor spectral clustering for partitioning higherorder network structures.
Austin R. Benson, David F. Gleich, Jure Leskovec.
Proceedings of the SIAM International Conference on Data Mining (SDM), 2015.
paper pdf code videoA framework for practical parallel fast matrix multiplication.
Austin R. Benson, 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, David F. Gleich.
Advances in Neural Information Processing Systems (NeurIPS), 2014.
Selected for spotlight presentation .
paper pdf code data posterLearning multifractal structure in large networks.
Austin R. Benson, Carlos Riquelme, Sven Schmit.
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2014.
paper pdf supplement videoA parallel directional Fast Multipole Method.
Austin R. Benson, Jack Poulson, Kenneth Tran, Björn Engquist, Lexing Ying.
SIAM Journal on Scientific Computing (SISC), 2014.
paper pdf codeSilent error detection in numerical timestepping schemes.
Austin R. Benson, Sven Schmit, Robert Schreiber.
International Journal of High Performance Computing Applications (IJHPCA), 2014.
paper pdf supplement codeDirect QR factorizations for tallandskinny matrices in MapReduce architectures.
Austin R. Benson, David F. Gleich, 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 .
paper pdf