Mathematician
Mathematician

Biography

As a graduate student at the Georgia Institute of Technology, Young studied the mathematical properties of complex networks such as the world wide web and social networks, as well as the combinatorial properties of partially ordered sets. After graduating with his PhD in Algorithms, Combinatorics, and Optimization in 2008, Young worked with Dr. Fan Chung at the University of California, San Diego to understand the emergence of paradoxical behaviors in selfish routing on networks with an underlying expansion property. After completing his post-doctoral studies, he joined the faculty of the Department of Mathematics at the University of Louisville, where he continued his research into properties of models for complex networks and combinatorics of partial orders. Since joining Pacific Northwest National Laboratory in 2015, Young has applied combinatorial and algorithmic techniques to a variety of application areas, including the mathematics of topological quantum computation, anomaly detection in cyber-systems, graphical models for the transmission layer of the grid, and the design of network topologies for next-generation supercomputers. Since 2020, he has been a team lead in PNNL’s Physical and Computational Sciences directorate and is currently serving as the lead for the Algorithms, Combinatorics, and Optimization team.

Research Interest

  • Spectral graph theory
  • Random graphs
  • Hypergraphs
  • Partially ordered sets (posets)
  • Combinatorial algorithms
  • Randomized algorithms
  • Approximation algorithms
  • Randomized linear algebra
  • Network science
  • High performance computing (HPC)
  • HPC topologies

Education

  • PhD in algorithms, combinatorics and optimization, Georgia Institute of Technology
  • MS in operations research, Georgia Institute of Technology
  • MS in applied mathematics, Georgia Institute of Technology
  • BS in mathematics, Rose-Hulman Institute of Technology

Affiliations and Professional Service

  • Society for Industrial and Applied Mathematics
  • American Mathematical Society
  • Program Committee, Workshop on Modelling and Mining Networks
  • Committee on Science Policy, Society for Industrial and Applied Mathematics (2017—2020)

Publications

2023

  • Aksoy S.G., R. Bennink, Y. Chen, J. Frias, Y.R. Gel, W.W. Kay, and U. Naumann, et al. 2023. "Seven open problems in applied combinatorics." Journal of Combinatorics 14, no. 4:559-601. PNNL-SA-182814. doi:10.4310/JOC.2023.v14.n4.a8
  • Dey A., S.J. Young, and Y. Gel. 2023. “From Delaunay triangulation to topological data analysis: Generation of more realisitic synthetic grid networks.” Journal of the Royal Statistical Society – Series A (Statistics in Society) 186, no. 3:335-354. PNNL-SA-169366. doi:10.1093/jrsssa/qnad066
  • Nielson F.F., B. Kay, S.J. Young, S.M. Colby, R.S. Renslow, and T.O. Metz. 2023. “Similarity Downselection: Finding the n Most Dissimilar Molecular Conformers for Reference-Free Metabolomics.” Metabolites 13, no. 1:Art. No. 105. PNNL-SA-157372. doi:10.3390/metabo13010105
  • Young S.J., J.D. Suetterlein, J.S. Firoz, J.B. Manzano Franko, and K.J. Barker. 2023. “Finding Your Niche: An Evolutionary Approach to HPC Topologies.” In 2023 IEEE High Performance Extreme Computing Conference (HPEC 2023). PNNL-SA-189932.

2022

  • Aksoy S.G., A. Hagberg, C.A. Joslyn, B. Kay, E. Purvine, and S.J. Young. 2022. "Models and Methods for Sparse (Hyper) Network Science in Business, Industry, and Government." Notices of the American Mathematical Society 69, no. 2:287-291. PNNL-SA-168162. doi:10.1090/noti2424
  • Keller M.T., A. Trenk, and S.J. Young. 2022. "Dimension of Restricted Classes of Interval Orders." Graphs and Combinatorics 38, no. 5:Art. No. 137. PNNL-SA-152654. doi:10.1007/s00373-022-02543-6
  • Nowak K.E., C.M. Ortiz Marrero, and S.J. Young. 2022. "On the Structure of Isometrically Embeddable Metric Spaces." Electronic Journal of Linear Algebra 38. PNNL-SA-126943. doi:10.13001/ela.2022.6891
  • Young S.J. 2022. "The Weighted Spectrum of the Universal Cover and an Alon-Boppana Result for the Normalized Laplacian." Journal of Combinatorics 13, no. 1:23-40. PNNL-SA-123083. doi:10.4310/JOC.2022.v13.n1.a2
  • Young S.J., S.G. Aksoy, J.S. Firoz, R. Gioiosa, T.J. Hagge, M.C. Kempton, and J. Escobedo Contreras, et al. 2022. "SpectralFly: Ramanujan Graphs as Flexible and Efficient Interconnection Networks." In IEEE International Parallel and Distributed Processing Symposium (IPDPS 2022), May 30-June 03, 2022, Virtual, Online, 1040-1050. Los Alamitos, California:IEEE Computer Society. PNNL-SA-160551. doi:10.1109/IPDPS53621.2022.00105

2021

  • Aksoy S.G., P. Bruillard, S.J. Young, and M. Raugas. 2021. “Ramanujan graphs and the spectral gap of supercomputing topologies.” Journal of Supercomputing 77, 1177-1213. PNNL-SA-147472. doi:10.1007/s11227-020-03291-1
  • Aksoy S.G., E. Purvine, and S.J. Young. 2021. "Directional Laplacian Centrality for Cyber Situational Awareness." Digital Threats: Research and Practice 2, no. 4:1-28. PNNL-SA-155008. doi:10.1145/3450286
  • Aksoy S.G., M. Kempton, and S.J. Young. 2021. "Spectral Threshold for Extremal Cyclic Edge-Connectivity." Graphs and Combinatorics 37, no. 6:2079-2093. PNNL-SA-151831. doi:10.1007/s00373-021-02333-6
  • Biró C., B.O. Bosek, H.C. Smith, W.T. Trotter, R. Wang, and S.J. Young. 2021. “Planar posets that are accessible from below have dimension at most 6.” Order 38, no. 1:21-36. PNNL-SA-144431. doi:10.1007/s11083-020-09525-4
  • Roy S., S.G. Aksoy, S. Sarkar, P. Wang, and S.J. Young. 2021. "Structural Controllability Assessment for Inverter-Based Microgrids." In North American Power Symposium (NAPS 2021), November 14-16, 2021, College Station, TX, 1-6. Piscataway, New Jersey:IEEE. PNNL-SA-165688. doi:10.1109/NAPS52732.2021.9654687

2020

  • Keller M.T., and S.J. Young. 2020. "Hereditary Semiorders and Enumeration of Semiorders by Dimension." The Electronic Journal of Combinatorics 27, no. 1:Article No. P1.50. PNNL-SA-130793. doi:10.37236/8140

2019

  • Aksoy S.G., K.E. Nowak, and S.J. Young. 2019. "A Linear-Time Algorithm and Analysis of Graph Relative Hausdorff Distance." SIAM Journal on Mathematics of Data Science 1, no. 4:647-666. PNNL-SA-141641. doi:10.1137/19M1248224
  • Aksoy S.G., K.E. Nowak, E. Purvine, and S.J. Young. 2019. "Relative Hausdorff distance for network analysis." Applied Network Science 4, no. 1:80. PNNL-SA-141621. doi:10.1007/s41109-019-0198-0

2018

  • Hodas N.O., J. Hunter, S.J. Young, and K. Lerman. 2018. “Model of cognitive dynamics predicts performance on standardized tests.” Journal of Computational Social Science 1, no. 2:295-312. doi:10.1007/s42001-018-0025-x
  • Young S.J., Y.V. Makarov, R. Diao, M. Halappanavar, M.R. Vallem, R. Fan, and R. Huang, et al. 2018. "Topological Power Grid Statistics from a Network-of-Networks Perspective." In IEEE Power & Energy Society General Meeting (PESGM 2018), August 5-10, 2018, Portland, OR. Piscataway, New Jersey:IEEE. PNNL-SA-130492. doi:10.1109/PESGM.2018.8586475
  • Young S.J., Y.V. Makarov, R. Diao, R. Fan, R. Huang, J.G. O'Brien, and M. Halappanavar, et al. 2018. "Synthetic Power Grids from Real World Models." In IEEE Power & Energy Society General Meeting (PESGM 2018), August 5-10, 2018, Portland, OR. Piscataway, New Jersey:IEEE. PNNL-SA-130491. doi:10.1109/PESGM.2018.8585792

2017

  • Keller M.T., and S.J. Young. 2017. "Combinatorial Reductions for the Stanley Depth of I and S/I." The Electronic Journal of Combinatorics 24, no. 3:Article No. P3.48. PNNL-SA-121188. doi:10.37236/6783

2016

  • Biró C., M.T. Keller, and S.J. Young. 2016. “Posets with cover graph of pathwidth two have bounded dimension.” Order 33, no. 2:195-212. doi:10.1007/s11083-015-9359-7

2015

  • Radcliffe M. and S.J. Young. 2015. “Connectivity and giant component of stochastic Kronecker graphs.” Journal of Combinatorics 6, no. 4:457-482. doi:10.4310/JOC.2015.v6.n4.a4

2014

  • Bonato A., D.F. Gleich, M. Kim, D. Mitsche, P. Pralat, Y. Tian, and S.J. Young. 2014. “Dimensionality of social networks using motifes and eigenvalues.” PLoS One 9, no. 9:Art. No. e106052. doi:10.1371/journal.pone.0106052
  • Radcliffe M. and S.J. Young. 2014. “The spectra of multiplicative attribute graphs.” Linear Algebra and its Applications 462, 39-58. doi:10.1016/j.laa.2014.07.047

2013

  • Balogh J., G. Kemkes, C. Lee, and S.J. Young. 2013. “Towards a weighted version of the Hajnal-Szemerédi theorem.” Combinatorics, Probability, & Computing 22, no. 3:346-350. doi:10.1017/S0963548313000059

2012

  • Chung F., S.J. Young, and W. Zhao. 2012. “Braess’s paradox in expanders.” Random Structures & Algorithms 41, no. 4:451-468. doi:10.1002/rsa.20457
  • Streib N., S.J. Young, and J. Sokol. 2012. “A Major League Baseball team uses operations research to improve draft preparation.” Interfaces 42, no. 4:119-130. doi:10.1287/inte.1100.0552

2011

  • Howard D.M. and S.J. Young. 2011. “When linear and weak discrepancy are equal.” Discrete Mathematics 311, no.4:252-257. doi:10.1016/j.disc.2010.11.003
  • Keller M.T., Y.-H. Shen, N. Streib, and S.J. Young. 2011. “On the Stanley depth of squarefee Veronese ideals.” Journal of Algebraic Combinatorics 33, no. 2:313-324. doi:10.1007/s10801-010-0249-1

2010

  • Biró C., D.M. Howard, M.T. Keller, W.T. Trotter, and S.J. Young. 2010. “Interval partitions and Stanley depth.” 2010. Journal of Combinatorial Theory – Series A 117, no. 4:475-482. doi:10.1016/j.jcta.2009.07.008
  • Chung F. and S.J. Young. 2010. “Braess’s paradox in large sparse graphs.” In Lecture notes in Computer Science (Internet and Network Economics) 6484:194-208. doi:10.1007/978-3-642-17572-5_16
  • Keller M.T. and S.J. Young. 2010. “Degree bounds for linear discrepancy of interval orders and disconnected posets.” Discrete Mathematics 310, no: 15-16:2198-2203. doi:10.1016/j.disc.2010.04.016

2009

2008

  • Young S.J. and E. Scheinerman. 2008. “Directed random dot product graphs.” Internet Mathematics 5, no. 1-2:91-111.

2007

  • Howard D.M., M.T. Keller, and S.J. Young. 2007. “A characterization of partially ordered sets with linear discrepancy equal to 2.” Order 24, no. 3:139-157. doi:10.1007/s11083-007-9065-1
  • Young S.J. and E.R. Scheinerman. 2007. “Random dot product graphs for social networks.” In Lecture Notes in Computer Science (Algorithms and models for the web graph) 4863:138-149. doi:10.1007/978-3-540-77004-6_11