{"id":11,"date":"2015-11-03T15:53:38","date_gmt":"2015-11-03T20:53:38","guid":{"rendered":"https:\/\/test.eng.ufl.edu\/faculty-site\/?page_id=11"},"modified":"2026-02-06T12:02:10","modified_gmt":"2026-02-06T17:02:10","slug":"publications","status":"publish","type":"page","link":"https:\/\/faculty.eng.ufl.edu\/smart-autonomy-lab\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"\n

Journal Articles<\/h3>\n\n\n\n
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  1. Z. Xuan, Y. Wang, “How hard is it to solve constrained sc-LTL planning problems?<\/a>,” submitted to IEEE Transactions on Automatic Control, 2025.<\/li>\n
  2. N. Smith, Y. Wang, “Data driven Supervisory Control under Sensor and Actuator Attacks via Spectral Learning<\/a>,” submitted to IEEE Transactions on Automatic Control, 2025.<\/li>\n
  3. Y. Wang, H. Sibai, M. Yen, S. Mitra, and G. E. Dullerud, \u201cDifferentially private algorithms for statistical verification of cyber-physical systems,\u201d IEEE Open Journal of Control Systems, vol. 1, pp. 294-305, 2022.<\/li>\n
  4. Y. Wang, N. Roohi, M. West, M. Viswanathan, and G. E. Dullerud, \u201cVerifying stochastic hybrid systems with temporal logic specifications via model reduction,\u201d ACM Transactions on Embedded Computing Systems, vol. 20, no. 6, p. 113:1-113:27, 2021.<\/li>\n
  5. Y. Wang, X. Bi, and A. Qu, \u201cA logistic factorization model for recommender systems with multinomial responses,\u201d Journal of Computational and Graphical Statistics, vol. 29, no. 2, pp. 396\u2013404, 2020.<\/li>\n
  6. Y. Wang, M. Zarei, B. Bonakdarpour, and M. Pajic, \u201cStatistical verification of hyperproperties for cyber-physical systems,\u201d ACM Transactions on Embedded Computing Systems, vol. 18, no. 5s, pp. 1\u201323, 2019.<\/li>\n
  7. Y. Wang, N. Roohi, M. West, M. Viswanathan, and G. E. Dullerud, \u201cStatistical verification of PCTL using antithetic and stratified samples,\u201d Formal Methods in System Design, vol. 54, pp. 145\u2013163, 2019.<\/li>\n
  8. Y. Wang, N. Roohi, G. E. Dullerud, and M. Viswanathan, \u201cStability analysis of switched linear systems defined by regular languages,\u201d IEEE Transactions on Automatic Control, vol. 62, no. 5, pp. 2568\u20132575, 2017.<\/li>\n
  9. Y. Wang, Z. Huang, S. Mitra, and G. E. Dullerud, \u201cDifferential privacy in linear distributed control systems: entropy minimizing mechanisms and performance tradeoffs,\u201d IEEE Transactions on Control of Network Systems, vol. 4, no. 1, pp. 118\u2013130, 2017.<\/li>\n<\/ol>\n
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    Conference Proceedings<\/h3>\n\n\n\n
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    1. Z. Xuan, A. K. Bozkurt, M. Pajic, Y. Wang, “On the Uniqueness of Solution for the Bellman Equation of LTL Objectives<\/a>,” in Proceedings of Machine Learning Research, 2024.<\/li>\n
    2. M. Yen, G. E. Dullerud, Y. Wang, “Statistical Verification of Traffic Systems with Expected Differential Privacy,” in American Control Conference, 2023, pp. 3496-3501.<\/li>\n
    3. Y. Wang, Q. Gao, and M. Pajic, \u201cLearning monotone dynamics by neural networks,\u201d in American Control Conference, 2022, p. to appear.<\/li>\n
    4. A. Khazraei, S. Hallyburton, Q. Gao, Y. Wang, and M. Pajic, \u201cLearning-based vulnerability analysis of cyber-physical systems,\u201d in ACM\/IEEE International Conference on Cyber-Physical Systems, Milan, Italy, 2022, pp. 259\u2013269.<\/li>\n
    5. Y. Wang, M. Zarei, B. Bonakdarpoor, and M. Pajic, \u201cProbabilistic conformance for cyber-physical systems,\u201d in ACM\/IEEE 12th International Conference on Cyber-Physical Systems, 2021, pp. 55\u201366.<\/li>\n
    6. Y. Wang, S. Nalluri, B. Bonakdarpour, and M. Pajic, \u201cStatistical model checking for hyperproperties,\u201d in IEEE Computer Security Foundations Symposium, Dubrovnik, Croatia, 2021, pp. 1\u201316.<\/li>\n
    7. A. K. Bozkurt, Y. Wang, M. Zavlanos, and M. Pajic, \u201cModel-free reinforcement learning for stochastic games with linear temporal logic objectives,\u201d in IEEE International Conference on Robotics and Automation, 2021, pp. 10649\u201310655.<\/li>\n
    8. A. K. Bozkurt, Y. Wang, and M. Pajic, \u201cSecure planning against stealthy attacks via model-free reinforcement learning,\u201d in IEEE International Conference on Robotics and Automation, 2021, pp. 10656\u201310662.<\/li>\n
    9. A. K. Bozkurt, Y. Wang, and M. Pajic, \u201cModel-free learning of safe yet effective controllers,\u201d in IEEE Conference on Decision and Control, 2021, pp. 6560\u20136565.<\/li>\n
    10. M. Zarei, Y. Wang, and M. Pajic, \u201cStatistical verification of learning-based cyber-physical systems,\u201d in ACM International Conference on Hybrid Systems: Computation and Control, Sydney, Australia, 2020, pp. 1\u20137.<\/li>\n
    11. Y. Wang, N. Roohi, M. West, M. Viswanathan, and G. E. Dullerud, \u201cStatistically model checking PCTL specifications on Markov decision processes via reinforcement learning,\u201d in IEEE Conference on Decision and Control, 2020, pp. 1392–1397.<\/li>\n
    12. Y. Wang and M. Pajic, \u201cHyperproperties for robotics: motion planning via HyperLTL,\u201d in IEEE International Conference on Robotics and Automation, Paris, France, 2020, pp. 8462\u20138468.<\/li>\n
    13. N. Roohi, Y. Wang, M. West, G. E. Dullerud, and M. Viswanathan, \u201cSTMC: statistical model checker with stratified and antithetic sampling,\u201d in Computer aided verification, Cham, 2020, pp. 448\u2013460.<\/li>\n
    14. K. H. Kim et al., \u201cSecurity analysis against spoofing attacks for distributed UAVs,\u201d in Workshop on Decentralized IoT Systems and Security, San Diego, 2020, pp. 1\u20136.<\/li>\n
    15. M. Elfar, Y. Wang, and M. Pajic, \u201cContext-aware temporal logic for probabilistic systems,\u201d in International Symposium on Automated Technology for Verification and Analysis, Hanoi, Vietnam, 2020, pp. 215\u2013232.<\/li>\n
    16. A. K. Bozkurt, Y. Wang, M. Zavlanos, and M. Pajic, \u201cControl synthesis from linear temporal logic specifications using model-free reinforcement learning,\u201d in IEEE International Conference on Robotics and Automation, Paris, France, 2020, pp. 10349\u201310355.<\/li>\n
    17. Y. Wang, M. Zarei, B. Bonakdarpour, and M. Pajic, \u201cStatistical verification of hyperproperties for cyber-physical systems,\u201d ACM Transactions on Embedded Computing Systems, vol. 18, no. 5s, pp. 1\u201323, 2019.<\/li>\n
    18. Y. Wang and M. Pajic, \u201cSupervisory control of discrete event systems in the presence of sensor and actuator attacks,\u201d in IEEE Conference on Decision and Control, Nice, France, 2019, pp. 5350\u20135355.<\/li>\n
    19. Y. Wang and M. Pajic, \u201cAttack-resilient supervisory control with intermittently secure communication,\u201d in IEEE Conference on Decision and Control, Nice, France, 2019, pp. 2015\u20132020.<\/li>\n
    20. M. Elfar, Y. Wang, and M. Pajic, \u201cSecurity-aware synthesis using delayed-action games,\u201d in International Conference on Computer-Aided Verification (CAV), New York, NY, 2019, pp. 180\u2013199.<\/li>\n
    21. Y. Wang, N. Roohi, M. West, M. Viswanathan, and G. E. Dullerud, \u201cStatistical verification of PCTL using stratified samples,\u201d in IFAC Conference on Analysis and Design of Hybrid Systems, IFAC-PapersOnLine, Oxford, UK, 2018, vol. 51, pp. 85\u201390.<\/li>\n
    22. Y. Wang, S. Mitra, and G. E. Dullerud, \u201cDifferential privacy and minimum-variance unbiased estimation in multi-agent control systems,\u201d in IFAC World Congress, IFAC-PapersOnLine, 2017, vol. 50, pp. 9521\u20139526.<\/li>\n
    23. N. Roohi, Y. Wang, M. West, G. E. Dullerud, and M. Viswanathan, \u201cStatistical verification of the toyota powertrain control verification benchmark,\u201d in ACM International Conference on Hybrid Systems: Computation and Control (HSCC), New York, NY, USA, 2017, pp. 65\u201370.<\/li>\n
    24. Y. Wang, N. Roohi, M. West, M. Viswanathan, and G. E. Dullerud, \u201cVerifying continuous-time stochastic hybrid systems via Mori-Zwanzig model reduction,\u201d in IEEE Conference on Decision and Control, 2016, pp. 3012\u20133017.<\/li>\n
    25. Y. Wang, H. Hale Matthew, M. Egerstedt, and G. E. Dullerud, \u201cDifferentially private objective functions in distributed cloud-based optimization,\u201d in IEEE Conference on Decision and Control, 2016, pp. 3688\u20133694.<\/li>\n
    26. Z. Huang, Y. Wang, S. Mitra, and G. E. Dullerud, \u201cController synthesis for linear dynamical systems with adversaries,\u201d in ACM Symposium and Bootcamp on the Science of Security, Pittsburgh, PA, 2016, pp. 53\u201362.<\/li>\n
    27. Y. Wang, N. Roohi, M. West, M. Viswanathan, and G. E. Dullerud, \u201cStatistical verification of dynamical systems using set oriented methods,\u201d in ACM International Conference on Hybrid Systems: Computation and Control, New York, NY, USA, 2015, pp. 169\u2013178.<\/li>\n
    28. Y. Wang, N. Roohi, M. West, M. Viswanathan, and G. E. Dullerud, \u201cA Mori-Zwanzig and MITL based approach to statistical verification of continuous-time dynamical systems,\u201d in IFAC Conference on Analysis and Design of Hybrid Systems, Atlanta, GA, 2015, vol. 48, pp. 267\u2013273.<\/li>\n
    29. Z. Huang, Y. Wang, S. Mitra, G. E. Dullerud, and S. Chaudhuri, \u201cController synthesis with inductive proofs for piecewise linear systems: an SMT-based algorithm,\u201d in IEEE Conference on Decision and Control, 2015, pp. 7434\u20137439.<\/li>\n
    30. Y. Wang, N. Roohi, G. E. Dullerud, and M. Viswanathan, \u201cStability of linear autonomous systems under regular switching sequences,\u201d in IEEE Conference on Decision and Control, 2014, pp. 5445\u20135450.<\/li>\n
    31. Y. Wang, Z. Huang, S. Mitra, and G. E. Dullerud, \u201cEntropy-minimizing mechanism for differential privacy of discrete-time linear feedback systems,\u201d in IEEE Conference on Decision and Control, 2014, pp. 2130\u20132135.<\/li>\n
    32. Z. Huang, Y. Wang, S. Mitra, and G. E. Dullerud, \u201cOn the cost of differential privacy in distributed control systems,\u201d in International Conference on High Confidence Networked Systems, 2014, pp. 105\u2013114.<\/li>\n<\/ol>\n

      Workshop Presentations<\/h3>\n
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      1. N. Smith, N. Hirsch, and Y. Wang, “Human-feedback guided reinforcement learning for unknown temporal tasks via weighted finite automata<\/a>,” in\u00a0 International Conference on Machine Learning.<\/li>\n<\/ol>\n<\/div>\n\n\n","protected":false},"excerpt":{"rendered":"

        Journal Articles Z. Xuan, Y. Wang, “How hard is it to solve constrained sc-LTL planning problems?,” submitted to IEEE Transactions on Automatic Control, 2025. N. Smith, Y. Wang, “Data driven Supervisory Control under Sensor and Actuator Attacks via Spectral Learning,” submitted to IEEE Transactions on Automatic Control, 2025. Y. Wang, H. Sibai, M. Yen, S. […]<\/p>\n","protected":false},"author":468,"featured_media":0,"parent":0,"menu_order":4,"comment_status":"closed","ping_status":"closed","template":"page-templates\/page-sidebar-none.php","meta":{"_acf_changed":false,"inline_featured_image":false,"featured_post":"","footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-11","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/faculty.eng.ufl.edu\/smart-autonomy-lab\/wp-json\/wp\/v2\/pages\/11","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/faculty.eng.ufl.edu\/smart-autonomy-lab\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/faculty.eng.ufl.edu\/smart-autonomy-lab\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/faculty.eng.ufl.edu\/smart-autonomy-lab\/wp-json\/wp\/v2\/users\/468"}],"replies":[{"embeddable":true,"href":"https:\/\/faculty.eng.ufl.edu\/smart-autonomy-lab\/wp-json\/wp\/v2\/comments?post=11"}],"version-history":[{"count":3,"href":"https:\/\/faculty.eng.ufl.edu\/smart-autonomy-lab\/wp-json\/wp\/v2\/pages\/11\/revisions"}],"predecessor-version":[{"id":645,"href":"https:\/\/faculty.eng.ufl.edu\/smart-autonomy-lab\/wp-json\/wp\/v2\/pages\/11\/revisions\/645"}],"wp:attachment":[{"href":"https:\/\/faculty.eng.ufl.edu\/smart-autonomy-lab\/wp-json\/wp\/v2\/media?parent=11"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}