{"id":39,"date":"2015-09-02T18:39:13","date_gmt":"2015-09-02T22:39:13","guid":{"rendered":"http:\/\/www.cs.fsu.edu\/vipra\/?page_id=39"},"modified":"2025-02-19T13:18:31","modified_gmt":"2025-02-19T18:18:31","slug":"publications","status":"publish","type":"page","link":"https:\/\/www.cs.fsu.edu\/vipra\/?page_id=39","title":{"rendered":"Publications"},"content":{"rendered":"

Modeling<\/strong><\/p>\n

    \n
  1. Y. Wu, S. Namilae, A. Srinivasan, A. Mubayi, and M. Scotch. Parametric analysis of SARS-CoV-2 dose-response models in transportation scenarios.<\/strong> PloS ONE. 19:6 (2024): e0301996.<\/li>\n
  2. T. Islam, A. Srinivasan, and S. Namilae. Evaluation of Parameter Sweeps for Computationally Efficient Infection Risk Analysis for Air Travel.<\/strong> Proceedings of the IEEE Aerospace Conference (AERO), (2023).<\/li>\n
  3. A. Srinivasan and S. Namilae. Infection Risk Mitigation Using Pedestrian Dynamics<\/strong>. Chapter in Architectural Factors for Infection and Disease Control,<\/strong> Editors: A. Bliss and D. Kopec. Routledge (2023).<\/li>\n
  4. S. Namilae, Y. Wu, A. Mubayi, A. Srinivasan, and M. Scotch. Reply to comments on \u201cIdentifying mitigation strategies for COVID-19 superspreading on flights using models that account for passenger movement\u201d<\/a>. Travel Medicine and Infectious Disease 51: 102453 (2023).<\/li>\n
  5. S. Namilae, Y. Wu, A. Mubayi, A. Srinivasan, and M. Scotch. Identifying mitigation strategies for COVID-19 superspreading on flights using models that account for passenger movement<\/a>. Travel Medicine and Infectious Disease 47: 102313 (2022).<\/li>\n
  6. Y. Wu, S. Namilae, A. Mubayi, M. Scotch and A. Srinivasan. Incorporating Pedestrian Movement in Computational Models of COVID-19 Spread during Air-travel.<\/strong> IEEE Aerospace Conference (AERO), pp. 1-8, 2022).<\/li>\n
  7. R. L\u00f6hner, H. Antil, A. Srinivasan, S. Idelsohn, and E. Onate. High-Fidelity Simulation of Pathogen Propagation, Transmission and Mitigation in the Built Environment<\/a>. Arch. Computat. Methods Eng. (2021).<\/li>\n
  8. Ghaffari M, Srinivasan A, Liu X, and Chakraborty S. High resolution home location prediction from Twitter activities using consensus deep learning<\/a>. Social Network Analysis and Mining, 11:95 (2021).<\/li>\n
  9. Sadeghi Lahijani M, Gayatri R, Islam T, Srinivasan A, and Namilae S. Architecture-Aware Modeling of Pedestrian Dynamics<\/a>. Journal of the Indian Institute of Science (2021).<\/li>\n
  10. Derjany P, Namilae S, and Srinivasan A. Parameter Space Exploration in Pedestrian Queue Design to Mitigate Infectious Disease Spread<\/a>. Journal of the Indian Institute of Science (2021).<\/li>\n
  11. Islam T, Sadeghi Lahijani M, Srinivasan A, Namilae S, Mubayi A, and Scotch M. From Bad to Worse: Airline Boarding Changes in Response to COVID-19<\/a>. Royal Society Open Science, 8201019201019 (2021). http:\/\/doi.org\/10.1098\/rsos.201019<\/li>\n
  12. Derjany P, Namilae S, Liu D, Srinivasan A (2020) Multiscale Model for the Optimal Design of Pedestrian Queues to Mitigate Infectious Disease Spread<\/a>. PLoS ONE 15(7): e0235891. https:\/\/doi.org\/10.1371\/journal.pone.0235891<\/li>\n
  13. M.S. Lahijani, T. Islam, A. Srinivasan, and S. Namilae. Constrained Linear Movement Model (CALM): Simulation of passenger movement in airplanes<\/a>. PLoS ONE 15(3): e0229690 (2020). https:\/\/doi.org\/10.1371\/journal.pone.0229690.<\/li>\n
  14. P. Derjany, S. Namilae, D. Liu, and A. Srinivasan. Computational Modeling Framework for the Study of Infectious Disease Spread through Commercial Air-Travel<\/a> IEEE Aerospace Conference, 2020.<\/li>\n
  15. M. Ghaffari, A. Srinivasan, and X. Liu. High-Resolution Home Location Prediction from Tweets using Deep Learning with Dynamic Structure<\/a> (Detailed version). IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). 2019.<\/li>\n
  16. M. Ghaffari, A. Srinivasan, A. Mubayi, X. Liu, and K. Viswanathan. Next-Generation High-Resolution Vector-Borne Disease Risk Assessment<\/a> (Detailed version). IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). 2019.<\/li>\n
  17. M. Ghaffari, J. Wang, A. Chari, A. Srinivasan, K. Viswanathan, A. Mubayi, and H. Chi. <\/a>Integrating Travel and Epidemic Models for Vector Borne Disease Surveillance. 7th International Conference on Innovations in Travel Modeling (ITIM). National Academies \u2013 Transportation Research Board. 2018.<\/li>\n
  18. Derjany P, Namilae S, Mubayi A, Scotch M, Srinivasan A. Effect of Pedestrian Movement on the Spread of Infectious Diseases during Air-travel<\/a>. Transportation Research Forum Proceedings, (2017).<\/li>\n
  19. Derjany P, Namilae S, Mubayi A, Scotch M, Srinivasan A. Molecular Dynamics Like Numerical Approach for Studying Infection Propagation<\/a>. Twenty Fifth International conference on composites and nano engineering, July (2017).<\/li>\n
  20. Namilae S, Derjany P, Mubayi A, Scotch M, Srinivasan A. Multiscale model for pedestrian and infection dynamics during air travel<\/a>. Physical Review E, 95(5) (2017) 052320.<\/li>\n
  21. Namilae S, Srinivasan A, Mubayi A, Scotch M, Pahle R. Self-Propelled Pedestrian Dynamics Model: Application to Passenger Movement and Infection Propagation in Airplanes<\/a>. Physica A, vol. 465 (2017) 248-260.<\/li>\n
  22. Namilae S, Srinivasan A, Sudheer C, Mubayi A, Pahle R, Scotch M. <\/a> Self-Propelled Pedestrian Dynamics Model for Studying Infectious Disease Propagation during Air-Travel. Journal of Transport and Health, 3(2) (2016) S40.<\/li>\n
  23. Magee D, Scotch M. Conceptualizing a Novel Quasi-Continuous Bayesian Phylogeographic Framework for Spatiotemporal Hypothesis Testing<\/a>. AMIA Jt Summits Transl Sci Proc. 2015 Mar 23;2015:212-216.<\/li>\n
  24. Scotch M, Suchard MA, Rabinowitz P. Analysis of Viral Genetics for Estimating Diffusion of Influenza A H6N1<\/a>. AMIA Jt Summits Transl Sci Proc. 2015 Mar 23;2015:36-40.<\/li>\n
  25. Weissenbacher D, Tahsin T, Beard R, Figaro M, Rivera R, Scotch M, Gonzalez G. Knowledge-driven geospatial location resolution for phylogeographic models of virus migration<\/a>. Bioinformatics. 2015 Jun 15;31(12):i348-56.<\/li>\n
  26. Veljkovic V, Glisic S, Muller CP, Scotch M, Branch DR, Perovic VR, Sencanski M, Veljkovic N, Colombatti A. In silico analysis suggests interaction between Ebola virus and the extracellular matrix<\/a>. Front Microbiol. 2015 Feb 19;6:135.<\/li>\n
  27. Magee D, Beard R, Suchard MA, Lemey P, Scotch M. Combining phylogeography and spatial epidemiology to uncover predictors of H5N1 influenza A virus diffusion<\/a>. Arch Virol. 2015 Jan;160(1):215-24.<\/li>\n
  28. Kane MJ, Price N, Scotch M, Rabinowitz P. Comparison of ARIMA and random forest time series models for prediction of avian influenza H5N1 outbreaks<\/a>. BMC Bioinformatics. 2014 Aug 13;15:276.<\/li>\n
  29. Scotch M, Lam TT, Pabilonia KL, Anderson T, Baroch J, Kohler D, DeLiberto TJ. Diffusion of influenza viruses among migratory birds with a focus on the Southwest United States<\/a>. Infect Genet Evol. 2014 Aug;26:185-93.<\/li>\n<\/ol>\n

    Computation<\/strong><\/p>\n

      \n
    1. N. Blackthorn, A.A. Mahyari, and A. Srinivasan. Training Variational Autoencoders for Population Synthesis in Public Health with Missing Data.<\/strong> Proceedings of the 2024 IEEE International Conference on Big Data (BigData) (pp. 4969-4973), (2024).<\/li>\n
    2. J. Coffey, R. Pahle, A. Srinivasan, S. Namilae, and M. Scotch. A Knowledge Sharing Approach to Foster Interdisciplinary Pedestrian Dynamics and Epidemiological Modeling Research and Practice.<\/strong> Proceedings of the Ninth International Congress on Information and Communication Technology (ICICT), (2024).<\/li>\n
    3. N. Farmer, A. Mahyari, and A. Srinivasan. Deep Generative Models for Constructing Synthetic Populations in Public Health Applications.<\/strong> IEEE Applied Imagery Pattern Recognition Workshop (AIPR), 2023.<\/li>\n
    4. B. Swaminathan, J. Kang, K. Vaidya, A. Srinivasan, P. Kumar, S. Byna, and D. Barbarash. Crowd cluster data in the USA for analysis of human response to COVID-19 events and policies<\/a>. Scientific Data 10:267 (2023).<\/li>\n
    5. S. Chunduri , M. Ghaffari, M.S. Lahijani, A. Srinivasan, and S. Namilae. Parallel Low Discrepancy Parameter Sweep for Public Health Policy<\/a>. IEEE\/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGrid), (2018).<\/li>\n
    6. Srinivasan A, Sudheer CD, Namilae S. Optimizing Massively Parallel Simulations of Infection Spread Through Air-Travel for Policy Analysis<\/a>. IEEE\/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGrid), (2016). 10 pages.<\/li>\n
    7. Sudheer CD, Srinivasan A. Efficient Barrier Implementation on the POWER8 Processor<\/a>. IEEE International Conference on High Performance Computing (HiPC) (2015). 9 pages.<\/li>\n
    8. Panigrahi P, Kanchiraju S, Srinivasan A, Sudheer CD, Baruah PK. Optimizing MPI Collectives on Intel MIC Through Effective Use of Cache<\/a>.<\/i> IEEE International Conference on Parallel, Distributed and Grid Computing (PDGC), (2014).<\/li>\n
    9. Sudheer CD, Krishnan S, Srinivasan A, Kent PRC. Dynamic Load Balancing for Petascale Quantum Monte Carlo Applications: The Alias Method<\/a>. Computer Physics Communications, Vol. 184, (2013) 284-292.<\/li>\n
    10. Mitra S, Sarkar S, Srinivasan A. Reuse and Refactoring of GPU Kernels to Design Complex Applications<\/a>. Proceedings of the 10th<\/sup> IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA), (2012).<\/li>\n
    11. Sudheer CD, Srinivasan A. Optimization of the Hop-Byte Metric for Efficient Topology Aware Mapping<\/a>.<\/em> Proceedings of the 19th<\/sup> IEEE International Conference on High Performance Computing (HiPC) (2012).<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

      Modeling Y. Wu, S. Namilae, A. Srinivasan, A. Mubayi, and M. Scotch. Parametric analysis of SARS-CoV-2 dose-response models in transportation scenarios. PloS ONE. 19:6 (2024): e0301996. T. Islam, A. Srinivasan, and S. Namilae. Evaluation of Parameter Sweeps for Computationally Efficient Infection Risk Analysis for Air Travel. Proceedings of the IEEE Aerospace Conference (AERO), (2023). A. Srinivasan and S. Namilae. Infection […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"template-fullwidth.php","meta":[],"_links":{"self":[{"href":"https:\/\/www.cs.fsu.edu\/vipra\/index.php?rest_route=\/wp\/v2\/pages\/39"}],"collection":[{"href":"https:\/\/www.cs.fsu.edu\/vipra\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.cs.fsu.edu\/vipra\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.cs.fsu.edu\/vipra\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cs.fsu.edu\/vipra\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=39"}],"version-history":[{"count":46,"href":"https:\/\/www.cs.fsu.edu\/vipra\/index.php?rest_route=\/wp\/v2\/pages\/39\/revisions"}],"predecessor-version":[{"id":1628,"href":"https:\/\/www.cs.fsu.edu\/vipra\/index.php?rest_route=\/wp\/v2\/pages\/39\/revisions\/1628"}],"wp:attachment":[{"href":"https:\/\/www.cs.fsu.edu\/vipra\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=39"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}