Sandia National Laboratories
Ali Pinar

Ali Pinar's Homepage

I work on various applications that involve graphs. Recently I have been working on modeling large scale graphs such as those of social networks, cyber networks. I have been also looking at power systems with focus on vulnerability analysis , and resilient network design. My early work was on traditional applications of combinatorial scientific computing such as sparse matrix computations and parallel computing, where the combinatorial algorithms work on the back stage to play an enabling role. Recently, I have started looking at areas where combinatorial problems are directly associated with scientific and engineering goals.

Before joining Sandia, I worked at Lawrence Berkeley National Laboratory between Oct 2001 and Oct 2008. And before that I received my PhD. in Computer science with the option of computational science and engineering from University of Illinois at Urbana Champaign (1997--2001), my M.S. and B.S. in Computer Science from Bilkent University, Turkey, in 1994 and 1996, respectively.

For more information about my work, you can look at my CV ...

Recent Activities

Recent Publications

Modeling and Analysis of Graphs

  • E. Sariyuce and A. Pinar, "Butterfly Effect: Peeling Bipartite Networks," submitted for conference publication, 2016. arXiv:1611:02756

  • A.Pinar, C. Seshadhri, and V. Vishal, "ESCAPE: Efficiently Counting All 5- Vertex Subgraphs," submitted for conference publication, 2016. arXiv:1610:09411

  • S. Aksoy, T. Kolda, and A. Pinar, "Measuring and Modeling Graphs with Community Structure," submitted for journal publication, arXiv:1607.08673

  • E. Sariyuce and A. Pinar, "Fast Hierarchy Construction for Dense Subgraphs" to appear in VLDB 2017. arXiv:1610.01961

  • S. Soundarajan, T. Eliassi-Rad, B. Gallagher, and A. Pinar, "MaxReach: Reduc- ing Network Incompleteness through Node Probes," in Proc. ASONAM 2016.

  • G. Ballard, T. Kolda, A. Pinar, and C. Seshadhri, "Diamond Sampling for Approximate Maximum All-pairs Dot-product (MAD) Search," to appear in ICDM 2015; preprint available as arXiv:1506:03872

  • E. Sariyuce, C. Seshadhri, A. Pinar, and U. Catalyurek,Finding Overlapping and Hierarchical Dense Subgraphs using Nuclear Decompositions, arXiv:1411.3312

  • S. Soundarajan, T. Eliassi-Rad B. Gallagher, and A. Pinar, Strategies for Probing Incomplete Graphs, 2014.

  • M. Jha, A. Pinar, and C. Seshadhri, Path Sampling: A Fast and Provable Method for Estimating 4-Vertex Subgraph Counts, arXiv:1411.4942

  • M. Jha, C. Seshadhri, and A. Pinar, Counting Triangles in Real-World Graph Streams: Dealing with Repeated Edges and Time Windows, arXiv:1310:7665

  • C. Seshadhri, A. Pinar, N. Durak, and T. Kolda, Directed closure measures for networks with reciprocity, arXiv:1302:6220

  • C. Peng, T. Kolda, and A. Pinar, Accelerating Community Detection by Using k-core subgraphs, arXiv:1403.2226

  • M. Jha, C. Seshadhri, and A. Pinar, A space efficient streaming algorithm for estimating transitivity and triangle counts using the birthday paradox, to ap- pear in ACM Transactions on Knowledge Discovery from Data, preprint available as arXiv:1212.2264.

  • J. Ray, A. Pinar, and C. Seshadhri, A stopping criterion for Markov chains when generating independent random graphs, to appear in Journal of Compex Networks, preprint available as arXiv:1210.8184.

  • C. Seshadhri, A. Pinar, and T. Kolda, Wedge Sampling for Computing Clustering Coefficients and Triangle Counts on Large Graphs, in Statistical Analysis and Data Mining special issue for Best of SDM 2013, Vol:7, No:4, pages:294-307, preprint available as arXiv:1309:3321>

  • K. Subbian, A. Singhal, T. Kolda, A. Pinar, and J. Srivastava, Dynamics of Trust Reciprocation in Multi-Relational Networks, Proc. the IEEE/ACM International Conference on Social Networks Analysis and Mining (ASONAM~2013). preprint available as arXiv:1303.6385

  • M. Jha, C. Seshadhri, and A. Pinar, A Space Efficient Streaming Algorithm for Triangle Counting using the Birthday Paradox, Proc. KDD~13; preprint available as arXiv:1212.2264 .

  • N. Durak, T. Kolda, A. Pinar, and C. Seshadhri, A Scalable Null Model to Match All Degree Distributions: In, Out, and Reciprocal, to appear in Proc. Second IEEE W. Network Science; also available as arXiv:1210.5288

  • K. Subbian, A. Singhal, T. Kolda, A. Pinar, and J. Srivastava, On Reciprocity in Massively Multi-player Online Game Networks, arXiv:1303:6385

  • C. Seshadhri, A. Pinar, and T.Kolda, An In-Depth Analysis of Stochastic Kronecker Graphs, to appear in Journal of the ACM. Available at arxiv. Earlier version appeared in ICDM 11. (pdf)

  • C. Seshadhri, A. Pinar, and T. Kolda, Triadic Measures on Graphs: The Power of Wedge Sampling, arXiv:1202.5230, to appear in Proc. SDM 13.

  • N. Durak, T. Kolda, A. Pinar, and C. Seshadhri, A Scalable directed graph model with reciprocal edges, arXiv:1210.5288.

  • N. Durak, A. Pinar, T. Kolda, and C. Seshadhri, Degree Relations of Triangles in Real-world Networks and Models, arxiv link shorter version to appear in ACM CIKM 12

  • C. Seshadhri, T. Kolda, and A. Pinar, Community structure and scale-free collections of Erdos--Renyi graphs, Physical Review E Vol. 85, No.5
  • J. Ray, A. Pinar, and C. Sehadhri, Are we there yet? When to stop a Markov chain while generating random graphs, WAW 12.

  • A. Pinar, C. Seshadhri, and T.Kolda, The Similarity between Stochastic Kronecker and Chung-Lu Graph Models, SDM'12. preprint available as arXiv:1110.4925

Complex Networks

  • C. Quinn, A. Pinar, J. Gao, and L. Su, "Sparse Approximations of Directed Information Graphs," in Proc. IEEE International Symposium on Information Theory (ISIT), 2016.

  • J. Cheng, R. Chen, H. Najm, A. Pinar, C. Safta, and J. Watson, "Distributionally Robust Optimization with Principal Component Analysis," submitted for journal publication.

  • J. Cheng, R. Chen, H. Najm, A. Pinar, C. Safta, and J.~Watson, "Chance Constrained Economic Dispatch Problem with Renewable Energy and Energy Storage,"

  • C. Safta, R. Chen, H. Najm, A. Pinar, and J.~Watson, "Efficient Uncertainty Quantification in Stochastic Economic Dispatch," IEEE T. Power Systems, preprint available as: arXiv:1508.04731

  • C. Quinn, A. Pinar, and N. Kiyavash, "Bounded Degree Approximations of Stochastic Networks," submitted for kournal publication, preprint available as: arXiv:1506.04767

  • R. Chen, N. Fan, A. Pinar, and J. Watson, Contingency-Constrained Unit Commitment with Post-Contingency Corrective Recourse, to appear in Annals of Operations Research, available as arXiv:1404.2964

  • Cosmin Safta, Richard L. Chen, Habib N. Najm, Ali Pinar, Jean-paul Watson, Toward Using Surrogates to Accelerate Solution of Stochastic Electricity Grid Operations Problems, arXiv:1407.2232

  • R. Chen, A. Cohn, N. Fan, and A. Pinar, "Contingency-Risk Informed Power System Design," in IEEE T. Power Systems, Vol. 29, No. 5, pages: 2087-2096, preprint available as arXiv:1305.0780

  • C. Quinn, A. Pinar, and N. Kiyavash, Optimal Bounded-Degree Approximations of Joint Distributions of Networks of Stochastic Processes, in Proc.of ISIT 13.

  • A. Pinar, J. Meza, V. Donde, and B. Lesieutre, Optimization Strategies for the Vulnerability Analysis of the Power Grid, SIAM Journal on Optimization, Vol. 20, No. 4, pages 1786--1810, 2010. (pdf)

High Performance Computing

  • J. Bennett, A. Bhagatwala, J. Chen, C. Seshadhri, A. Pinar, and M. Salloum, "Trigger Detection for Adaptive Scientific Workflows Using Percentile Sampling," SIAM Journal on Scientific Computing, preprint available as: arXiv:1506.08258

  • M. Salloum, J. Bennett, A. Pinar, A. Bhagatwala, and Jacqueline H. Chen, "Enabling adaptive scientific workflows via trigger detection," to appear in Proc. ISAV 2015: In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization, 2015; preprint available as: arXiv:1508.04731

  • T. Kolda, A. Pinar, T. Plantenga, and C. Seshadhri, A Scalable Generative Graph Model with Community Structure, to appear in SIAM J. Scientific Computing, preprint available as arXiv:1302.6636

  • T. Kolda, A.Pinar, T. Plantenga, C. Seshadhri, and C. Task, Counting Triangles in Massive Graphs with MapReduce, to appear in SIAM J. Scientific Computing; preprint available as arXiv:1301.5887

  • D. Thompson, J. Bennett, C. Seshadhri, and A. Pinar, A provably-robust sampling method for generating colormaps of large data, in Proc. IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV), 2013.

  • E. Kayaaslan, A. Pinar, U. Catalyurek, and C. Aykanat, Partitioning Hypergraphs in Scientific Computing Applications through Vertex Separators on Graphs;, SIAM Scientific Computing, to appear. (pdf)

  • C. Janssen, H. Adalsteinsson, S. Cranford, J. Kenny, A. Pinar, D. Evensky, and J. Mayo, A Simulator for Large-scale Parallel Computer Architectures, International Journal of Distributed Systems and Technology (pdf)

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Ali Pinar
Phone: (925) 294 4683
Fax: (925) 294 2234

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Twitter: @alipinar9