I am a quantitative analyst at D. E. Shaw & Co. in New York City, where I work on machine learning and quantitative finance.
Before working in finance, I was an Assistant Professor of Computer Science at Cornell University. My research focused on designing numerical methods and algorithmic frameworks to enable new, better, and bigger analyses of complex data. This research was recognized with an NSF CAREER Award, a KDD best paper award, a JP Morgan Chase AI Faculty Award, and the Gene Golub Doctoral Dissertation Award, and was supported by federal research grants from the Army Research Office and the NSF. I published this research in leading journals such as Science, Science Advances, Proceedings of the National Academy of Sciences, and SIAM Review, and at the main machine learning and data science conferences, including NeurIPS, ICML, ICLR, KDD, and WWW. I also taught classes that covered data science, machine learning, network science, matrix computations, and numerical optimization.
Prior to Cornell, I spent nine formative years in the Bay Area, where I completed my PhD and MS at Stanford University and BS and BA at the University of California, Berkeley. During summers, I interned at Google (four times), Sandia National Laboratories, and HP Labs.
My old academic web site is at https://www.cs.cornell.edu/~arb/.
Research papers
Nonlinear Feature Diffusion on Hypergraphs. Francesco Tudisco, Konstantin Prokopchik, Austin R. Benson. International Conference on Machine Learning (ICML), 2022.
paper pdffauci-email: a json digest of Anthony Fauci's released emails. Austin R. Benson, Nate Veldt, David F. Gleich. International Conference on Web and Social Media (ICWSM), 2022.
paper pdf code dataDiverse and Experienced Group Discovery via Hypergraph Clustering. Ilya Amburg, Nate Veldt, Austin R. Benson. SIAM Data Mining (SDM) 2022.
paper pdf code dataHypergraph Cuts with General Splitting Functions. Nate Veldt, Austin R. Benson, Jon Kleinberg. SIAM Review (SIREV), 2022.
paper pdfA Unifying Generative Model for Graph Learning Algorithms: Label Propagation, Graph Convolutions, and Combinations. Junteng Jia, Austin R. Benson. SIAM Journal on Mathematics of Data Science (SIMODS), 2022.
paper pdf code dataUnderstanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective. Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li. Neural Information Processing Systems (NeurIPS), 2022.
paper pdfGraph-Based Methods for Discrete Choice. Kiran Tomlinson, Austin R. Benson. arXiv:2205.11365, 2022.
paper pdfGraph Neural Network Modeling of Grain-scale Anisotropic Elastic Behavior using Simulated and Measured Microscale Data. Darren C. Pagan, Calvin R. Pash, Austin R. Benson, Matthew P. Kasemer. arXiv:2205.06324, 2022.
paper pdfApproximate Decomposable Submodular Function Minimization for Cardinality-Based Components. Nate Veldt, Austin R. Benson, Jon Kleinberg. Neural Information Processing Systems (NeurIPS), 2021.
paper pdf codeCommunication-efficient 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. 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. 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. 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. International Conference on Web and Social Media (ICWSM), 2021.
paper pdf code dataHigher-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. 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, 2021.
paper pdf code dataNonlinear Higher-Order Label Spreading. Francesco Tudisco, Austin R. Benson, Konstantin Prokopchik. The Web Conference (WWW), 2021.
paper pdf code videoRandom Graphs with Prescribed K-Core Sequences: A New Null Model for Network Analysis. Katherine Van Koevering, Austin R. Benson, Jon Kleinberg. The Web Conference (WWW), 2021.
paper pdf code videoHigher Order Information Identifies Tie Strength. Arnab Sarker, Jean-Baptiste Seby, Austin R. Benson, Ali Jadbabaie. arXiv:2108.02091, 2021.
paper pdfEdge 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 codeGraph Belief Propagation Networks. Junteng Jia, Cenk Baykal, Vamsi K. Potluru, Austin R. Benson. arXiv:2106.03033, 2021.
paper pdf codeHigher-order Homophily is Combinatorially Impossible. Nate Veldt, Austin R. Benson, Jon Kleinberg. arXiv:2103.11818, 2021.
paper pdf codeBetter Set Representations For Relational Reasoning. Qian Huang, Horace He, Abhay Singh, Yan Zhang, Ser-Nam Lim, Austin R. Benson. Neural Information Processing Systems (NeurIPS), 2020.
paper pdf codeEntrywise Convergence of Iterative Methods for Eigenproblems. Vasileios Charisopoulos, Austin R. Benson, Anil Damle. Neural Information Processing Systems (NeurIPS), 2020.
paper pdf codeResidual Correlation in Graph Neural Network Regression. Junteng Jia, Austin R. Benson. 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. 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. 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 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. 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. The Web Conference (WWW), 2020.
paper pdf codeUsing cliques with higher-order spectral embeddings improves graph visualizations. Huda Nassar, Caitlin Kennedy, Shweta Jain, Caitlin Kennedy, Austin R. Benson, David F. Gleich. The Web Conference (WWW), 2020.
paper pdf code videoRetrieving Top Weighted Triangles in Graphs. Raunak Kumar, Paul Liu, Moses Charikar, Austin R. Benson. ACM International Conference on Web Search and Data Mining (WSDM), 2020.
paper pdf code dataOver-parametrized neural networks as under-determined 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 pdfNeural Jump Stochastic Differential Equations. Junteng Jia, Austin R. Benson. 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 Z-eigenvectors 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. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2019.
Best Paper Award Runner-up.
paper pdf codeGraph-based Semi-Supervised & Active Learning for Edge Flows. Junteng Jia, Michael T. Schaub, Santiago Segarra, Austin R. Benson. 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. 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 Core-Fringe Data. Austin R. Benson, Jon Kleinberg. 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. World Wide Web Conference (WWW), 2019.
paper pdf code posterRandom Spatial Network Models with Core-Periphery Structure. Junteng Jia, Austin R. Benson. 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. 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. ACM International Conference on Web Search and Data Mining (WSDM), 2019.
paper pdf codeIncrementally Updated Spectral Embeddings. Vasileios Charisopoulos, Austin R. Benson, Anil Damle. arXiv:1909.01188, 2019.
paper pdf code posterSimplicial 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 dataFound Graph Data and Planted Vertex Covers. Austin R. Benson, Jon Kleinberg. Neural Information Processing Systems (NeurIPS), 2018.
paper pdf code data posterSequences of Sets. Austin R. Benson, Ravi Kumar, Andrew Tomkins. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2018.
paper pdf code data poster videoHigher-order 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. ACM International Conference on Web Search and Data Mining (WSDM), 2018.
paper pdf code data posterLocal higher-order graph clustering. Hao Yin, Austin R. Benson, Jure Leskovec, David F. Gleich. 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. ACM International Conference on Web Search and Data Mining (WSDM), 2017.
paper pdf code data posterThe 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 dataHigher-order organization of complex networks. Austin R. Benson, David F. Gleich, Jure Leskovec. Science, 2016.
paper pdf supplement code dataGeneral tensor spectral co-clustering for higher-order data. Tao Wu, Austin R. Benson, David F. Gleich. Neural Information Processing Systems (NeurIPS), 2016.
paper pdf codeOn the relevance of irrelevant alternatives. Austin R. Benson, Ravi Kumar, Andrew Tomkins. International Conference on World Wide Web (WWW), 2016.
paper pdfModeling user consumption sequences. Austin R. Benson, Ravi Kumar, Andrew Tomkins. 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 higher-order network structures. Austin R. Benson, David F. Gleich, Jure Leskovec. SIAM International Conference on Data Mining (SDM), 2015.
paper pdf code videoA framework for practical parallel fast matrix multiplication. Austin R. Benson, Grey Ballard. ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2015.
paper pdf codeScalable methods for nonnegative matrix factorizations of near-separable tall-and-skinny matrices. Austin R. Benson, Jason D. Lee, Bartek Rajwa, David F. Gleich. Neural Information Processing Systems (NeurIPS), 2014.
Spotlight Presentation
paper pdf code data posterLearning multifractal structure in large networks. Austin R. Benson, Carlos Riquelme, Sven Schmit. 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 time-stepping schemes. Austin R. Benson, Sven Schmit, Robert Schreiber. International Journal of High Performance Computing Applications (IJHPCA), 2014.
paper pdf supplement codeDirect QR factorizations for tall-and-skinny matrices in MapReduce architectures. Austin R. Benson, David F. Gleich, James Demmel. IEEE International Conference on Big Data (IEEE BigData), 2013.
paper pdf code
Teaching material
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.
- 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). There is also an expanded arXiv version with more references.
- SIAM ALA '18 tutorial on Tensor Eigenvectors and Stochastic Processes (with David Gleich).
[web] [slides] [code]