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 higher-order network analysis in the article How Big Data Carried Graph Theory Into New Dimensions.
• I am very honored to receive an NSF CAREER Award.
• Higher-order 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 high-level overview of the emergence, mathematics, and opportunities of the higher-order 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: Higher-Order 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]

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.
• Higher-order 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]

Preprints

• Higher Order Information Identifies Tie Strength.
  Arnab Sarker, Jean-Baptiste Seby, Austin R. Benson, Ali Jadbabaie.
  arXiv:2108.02091, 2021.
  paper pdf

• fauci-email: a json digest of Anthony Fauci's released emails.
  Austin R. Benson, Nate Veldt, David F. Gleich.
  arXiv:2108.01239, 2021.
  paper pdf code data

• Edge Proposal Sets for Link Prediction.
  Abhay Singh, Qian Huang, Sijia Linda Huang, Omkar Bhalerao, Horace He, Ser-Nam Lim, Austin R. Benson.
  arXiv:2106.15810, 2021.
  paper pdf code

• Graph Belief Propagation Networks.
  Junteng Jia, Cenk Baykal, Vamsi K. Potluru, Austin R. Benson.
  arXiv:2106.03033, 2021.
  paper pdf code

• A Nonlinear Diffusion Method for Semi-supervised Learning on Hypergraphs.
  Francesco Tudisco, Konstantin Prokopchik, Austin R. Benson.
  arXiv:2103.14867, 2021.
  paper pdf

• Higher-order Homophily is Combinatorially Impossible.
  Nate Veldt, Austin R. Benson, Jon Kleinberg.
  arXiv:2103.11818, 2021.
  paper pdf code

• Over-parametrized neural networks as under-determined linear systems.
  Austin R. Benson, Anil Damle, Alex Townsend.
  arXiv:2010.15959, 2020.
  paper pdf

• A simple bipartite graph projection model for clustering in networks.
  Austin R. Benson, Paul Liu, Hao Yin.
  arXiv:2007.00761, 2020.
  paper pdf code

• Augmented Sparsifiers for Generalized Hypergraph Cuts with Applications to Decomposable Submodular Function Minimization.
  Austin R. Benson, Jon Kleinberg, Nate Veldt.
  arXiv:2007.08075, 2020.
  paper pdf

• Hypergraph Clustering for Finding Diverse and Experienced Groups.
  Ilya Amburg, Nate Veldt, Austin R. Benson.
  arXiv:2006.05645, 2020.
  paper pdf code data

• Incrementally Updated Spectral Embeddings.
  Vasileios Charisopoulos, Austin R. Benson, Anil Damle.
  arXiv:1909.01188, 2019.
  paper pdf code poster

Accepted and published research papers

• Hypergraph Cuts with General Splitting Functions.
  Nate Veldt, Austin R. Benson, Jon Kleinberg.
  To appear in SIAM Review (SIREV), 2022.
  paper pdf

• Approximate Decomposable Submodular Function Minimization for Cardinality-Based Components.
  Nate Veldt, Austin R. Benson, Jon Kleinberg.
  To appear at Neurips, 2021.
  paper pdf code

• A 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 data

• Communication-efficient distributed eigenspace estimation.
  Vasileios Charisopoulos, Austin R. Benson, Anil Damle.
  SIAM Journal on Mathematics of Data Science (SIMODS), 2021.
  paper pdf code

• Generative hypergraph clustering: from blockmodels to modularity.
  Philip S. Chodrow, Nate Veldt, Austin R. Benson.
  Science Advances, 2021.
  paper pdf code data

• The 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 code

• Choice 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 code

• Learning 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 data

• Expertise 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 data

• Higher-order 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 Out-performs Graph Neural Networks.
  Qian Huang, Horace He, Abhay Singh, Ser-Nam Lim, Austin R. Benson.
  Proceedings of the International Conference on Learning Representations (ICLR), 2021.
  paper pdf code

• Planted Hitting Set Recovery in Hypergraphs.
  Ilya Amburg, Jon Kleinberg, Austin R. Benson.
  Journal of Physics: Complexity (Special Issue on Higher-Order Structures in Networks and Network Dynamical Systems), 2021.
  paper pdf code data

• Nonlinear Higher-Order Label Spreading.
  Francesco Tudisco, Austin R. Benson, Konstantin Prokopchik.
  Proceedings of The Web Conference (WWW), 2021.
  paper pdf code video

• Random Graphs with Prescribed K-Core 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 video

• Better Set Representations For Relational Reasoning.
  Qian Huang, Horace He, Abhay Singh, Yan Zhang, Ser-Nam Lim, Austin R. Benson.
  Advances in Neural Information Processing Systems (NeurIPS), 2020.
  paper pdf code

• Entrywise Convergence of Iterative Methods for Eigenproblems.
  Vasileios Charisopoulos, Austin R. Benson, Anil Damle.
  Advances in Neural Information Processing Systems (NeurIPS), 2020.
  paper pdf code

• Residual 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 data

• Choice 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 slides

• Neighborhood and PageRank methods for pairwise link prediction.
  Huda Nassar, Austin Benson, David F. Gleich.
  Social Network Analysis and Mining (SNAM), 2020
  paper pdf code

• Network Interpolation.
  Thomas Reeves, Anil Damle, Austin R. Benson.
  SIAM Journal on Mathematics of Data Science (SIMODS), 2020.
  paper pdf code

• Measuring Directed Triadic Closure with Closure Coefficients.
  Hao Yin, Austin R. Benson, Johan Ugander.
  Network Science, 2020.
  paper pdf code

• Random Walks on Simplicial Complexes and the normalized Hodge 1-Laplacian.
  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 data

• Frozen 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 code

• Using cliques with higher-order 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 video

• Retrieving 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 data

• Neural Jump Stochastic Differential Equations.
  Junteng Jia, Austin R. Benson.
  Advances in Neural Information Processing Systems (NeurIPS), 2019.
  paper pdf code poster

• Modeling and Analysis of Tagging Networks in Stack Exchange Communities.
  Shangdi Yu, Xiang Fu, Austin R. Benson.
  Journal of Complex Networks, 2019.
  paper pdf code data

• Computing tensor Z-eigenvectors with dynamical systems.
  Austin R. Benson, David F. Gleich.
  SIAM Journal on Matrix Analysis and Applications (SIMAX), 2019.
  paper pdf code

• Unsupervised learning of dislocation motion.
  Darren C. Pagan, Thien Q. Phan, Jordan S. Weaver, Austin R. Benson, Armand J. Beaudoin.
  Acta Materialia, 2019.
  paper pdf

• Automated 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 pdf

• Pairwise 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 Runner-up.
  paper pdf code

• Graph-based Semi-Supervised & 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 video

• Network 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 video

• Three hypergraph eigenvector centralities.
  Austin R. Benson.
  SIAM Journal on Mathematics of Data Science (SIMODS), 2019.
  paper pdf code

• Link Prediction in Networks with Core-Fringe Data.
  Austin R. Benson, Jon Kleinberg.
  Proceedings of the World Wide Web Conference (WWW), 2019.
  paper pdf code poster

• Choosing 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 poster

• Random Spatial Network Models with Core-Periphery Structure.
  Junteng Jia, Austin R. Benson.
  Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2019.
  paper pdf code data poster

• Sampling 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 data

• The 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 code

• Simplicial closure and higher-order 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 data

• Found Graph Data and Planted Vertex Covers.
  Austin R. Benson, Jon Kleinberg.
  Advances in Neural Information Processing Systems (NeurIPS), 2018.
  paper pdf code data poster

• Sequences 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 video

• Higher-order clustering in networks.
  Hao Yin, Austin R. Benson, Jure Leskovec.
  Physical Review E (PRE), 2018.
  paper pdf code

• A 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 poster

• Local higher-order 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 video

• Motifs 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 poster

• The spacey random walk: a stochastic process for higher-order data.
  Austin R. Benson, David F. Gleich, Lek-Heng Lim.
  SIAM Review (SIREV), 2017.
  paper pdf code data

• Higher-order organization of complex networks.
  Austin R. Benson, David F. Gleich, Jure Leskovec.
  Science, 2016.
  paper pdf supplement code data

• General tensor spectral co-clustering for higher-order data.
  Tao Wu, Austin R. Benson, David F. Gleich.
  Advances in Neural Information Processing Systems (NeurIPS), 2016.
  paper pdf code

• On the relevance of irrelevant alternatives.
  Austin R. Benson, Ravi Kumar, Andrew Tomkins.
  Proceedings of the International Conference on World Wide Web (WWW), 2016.
  paper pdf

• Modeling user consumption sequences.
  Austin R. Benson, Ravi Kumar, 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, Oded Schwartz.
  SIAM Journal on Matrix Analysis and Applications (SIMAX), 2016.
  paper pdf code

• Tensor spectral clustering for partitioning higher-order network structures.
  Austin R. Benson, David F. Gleich, Jure Leskovec.
  Proceedings of the SIAM International Conference on Data Mining (SDM), 2015.
  paper pdf code video

• A 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 code

• Scalable methods for nonnegative matrix factorizations of near-separable tall-and-skinny 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 poster

• Learning 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 video

• A 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 code

• Silent error detection in numerical time-stepping schemes.
  Austin R. Benson, Sven Schmit, Robert Schreiber.
  International Journal of High Performance Computing Applications (IJHPCA), 2014.
  paper pdf supplement code

• Direct QR factorizations for tall-and-skinny 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 higher-order network analysis.
  Austin Reilley Benson.
  Stanford PhD thesis, 2017.
  Stanford ICME Gene Golub Doctoral Dissertation Award winner.
  paper pdf