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He Zhu

Rutgers, The State University

    20092024

    Research activity per year

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    • 2024

      Explain the Explainer: Interpreting Model-Agnostic Counterfactual Explanations of a Deep Reinforcement Learning Agent

      Chen, Z., Silvestri, F., Tolomei, G., Wang, J., Zhu, H. & Ahn, H., Apr 1 2024, In: IEEE Transactions on Artificial Intelligence. 5, 4, p. 1443-1457 15 p.

      Research output: Contribution to journal › Article › peer-review

    • Reward-Guided Synthesis of Intelligent Agents with Control Structures

      Cui, G., Wang, Y., Qiu, W. & Zhu, H., Jun 20 2024, In: Proceedings of the ACM on Programming Languages. 8, 217.

      Research output: Contribution to journal › Article › peer-review

    • Safe Exploration in Reinforcement Learning by Reachability Analysis over Learned Models

      Wang, Y. & Zhu, H., 2024, Computer Aided Verification - 36th International Conference, CAV 2024, Proceedings. Gurfinkel, A. & Ganesh, V. (eds.). Springer Science and Business Media Deutschland GmbH, p. 232-255 24 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14683 LNCS).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

      Open Access
    • 2023

      Defending Observation Attacks in Deep Reinforcement Learning via Detection and Denoising

      Xiong, Z., Eappen, J., Zhu, H. & Jagannathan, S., 2023, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Proceedings. Amini, M.-R., Canu, S., Fischer, A., Guns, T., Kralj Novak, P. & Tsoumakas, G. (eds.). Springer Science and Business Media Deutschland GmbH, p. 235-250 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13715 LNAI).

      Rutgers, The State University

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    • Instructing Goal-Conditioned Reinforcement Learning Agents with Temporal Logic Objectives

      Qiu, W., Mao, W. & Zhu, H., 2023, Advances in Neural Information Processing Systems 36 - 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural information processing systems foundation, (Advances in Neural Information Processing Systems; vol. 36).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    • Verification-guided Programmatic Controller Synthesis

      Wang, Y. & Zhu, H., 2023, Tools and Algorithms for the Construction and Analysis of Systems - 29th International Conference, TACAS 2023, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022, Proceedings. Sankaranarayanan, S. & Sharygina, N. (eds.). Springer Science and Business Media Deutschland GmbH, p. 229-250 22 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13994 LNCS).

      Rutgers, The State University

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

      Open Access
    • 2022

      Graph collaborative reasoning

      Chen, H., Li, Y., Shi, S., Liu, S., Zhu, H. & Zhang, Y., Feb 11 2022, WSDM 2022 - Proceedings of the 15th ACM International Conference on Web Search and Data Mining. Association for Computing Machinery, Inc, p. 75-84 10 p. (WSDM 2022 - Proceedings of the 15th ACM International Conference on Web Search and Data Mining).

      Rutgers, The State University

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

      Open Access

    • Learn Basic Skills and Reuse: Modularized Adaptive Neural Architecture Search (MANAS)

      Chen, H., Li, Y., Zhu, H. & Zhang, Y., Oct 17 2022, CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, p. 169-179 11 p. (International Conference on Information and Knowledge Management, Proceedings).

      Rutgers, The State University

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

      Open Access

    • PROGRAMMATIC REINFORCEMENT LEARNING WITHOUT ORACLES

      Qiu, W. & Zhu, H., 2022.

      Rutgers, The State University

      Research output: Contribution to conference › Paper › peer-review

    • ReLAX: Reinforcement Learning Agent Explainer for Arbitrary Predictive Models

      Chen, Z., Silvestri, F., Wang, J., Zhu, H., Ahn, H. & Tolomei, G., Oct 17 2022, CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, p. 252-261 10 p. (International Conference on Information and Knowledge Management, Proceedings).

      Rutgers, The State University

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

      Open Access
    • 2021

      Differentiable Synthesis of Program Architectures

      Cui, G. & Zhu, H., 2021, Advances in Neural Information Processing Systems 34 - 35th Conference on Neural Information Processing Systems, NeurIPS 2021. Ranzato, M., Beygelzimer, A., Dauphin, Y., Liang, P. S. & Wortman Vaughan, J. (eds.). Neural information processing systems foundation, p. 11123-11135 13 p. (Advances in Neural Information Processing Systems; vol. 14).

      Rutgers, The State University

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    • Robustness to Adversarial Attacks in Learning-Enabled Controllers

      Xiong, Z., Eappen, J., Zhu, H. & Jagannathan, S., 2021.

      Rutgers, The State University

      Research output: Contribution to conference › Paper › peer-review

    • 2020

      Art: Abstraction Refinement-Guided Training for Provably Correct Neural Networks

      Lin, X., Zhu, H., Samanta, R. & Jagannathan, S., Sep 21 2020, Proceedings of the 20th Conference on Formal Methods in Computer-Aided Design, FMCAD 2020. Ivrii, A., Strichman, O., Hunt, W. A. & Weissenbacher, G. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 148-157 10 p. 9283658. (Proceedings of the 20th Conference on Formal Methods in Computer-Aided Design, FMCAD 2020).

      Rutgers, The State University

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    • 2019

      An inductive synthesis framework for verifiable reinforcement learning

      Zhu, H., Magill, S., Xiong, Z. & Jagannathan, S., Jun 8 2019, PLDI 2019 - Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation. McKinley, K. S. & Fisher, K. (eds.). Association for Computing Machinery, p. 686-701 16 p. (Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI)).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

      Open Access
      14 Scopus citations
    • 2018

      A data-driven CHC solver

      Zhu, H., Magill, S. & Jagannathan, S., Jun 11 2018, PLDI 2018 - Proceedings of the 39th ACM SIGPLAN Conference on Programming Language Design and Implementation. Foster, J. S. & Grossman, D. (eds.). Association for Computing Machinery, p. 707-721 15 p. (Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI)).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

      11 Scopus citations

    • A data-driven CHC solver

      Zhu, H., Magill, S. & Jagannathan, S., Jun 11 2018, In: ACM SIGPLAN Notices. 53, 4, p. 707-721 15 p.

      Research output: Contribution to journal › Article › peer-review

      5 Scopus citations
    • 2016

      Automatically learning shape specifications

      Zhu, H., Petri, G. & Jagannathan, S., Jun 2 2016, PLDI 2016 - Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation. Krintz, C. & Berger, E. (eds.). Association for Computing Machinery, p. 491-507 17 p. (Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI); vol. 13-17-June-2016).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

      Open Access
      14 Scopus citations

    • Automatically learning shape specifications

      Zhu, H., Petri, G. & Jagannathan, S., Jun 2016, In: ACM SIGPLAN Notices. 51, 6, p. 491-507 17 p.

      Research output: Contribution to journal › Article › peer-review

      Open Access
    • 2015

      Dependent array type inference from tests

      Zhu, H., Nori, A. V. & Jagannathan, S., 2015, Verification, Model Checking and Abstract Interpretation - 16th International Conference, VMCAI 2015, Proceedings. D’Souza, D., Lal, A. & Larsen, K. G. (eds.). Springer Verlag, p. 412-430 19 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 8931).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

      2 Scopus citations

    • Learning refinement types

      Zhu, H., Nori, A. V. & Jagannathan, S., Sep 2015, In: ACM SIGPLAN Notices. 50, 9, p. 400-411 12 p.

      Research output: Contribution to journal › Article › peer-review

    • Learning refinement types

      Zhu, H., Nori, A. V. & Jagannathan, S., Aug 29 2015, ICFP 2015 - Proceedings of the 20th ACM SIGPLAN International Conference on Functional Programming. Fisher, K. & Reppy, J. (eds.). Association for Computing Machinery, p. 400-411 12 p. (Proceedings of the ACM SIGPLAN International Conference on Functional Programming, ICFP; vol. 2015-August).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

      13 Scopus citations

    • Poling: SMT aided linearizability proofs

      Zhu, H., Petri, G. & Jagannathan, S., 2015, Computer Aided Verification - 27th International Conference, CAV 2015, Proceedings. Păsăreanu, C. S. & Kroening, D. (eds.). Springer Verlag, p. 3-19 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9207).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

      11 Scopus citations
    • 2013

      Compositional and lightweight dependent type inference for ML

      Zhu, H. & Jagannathan, S., 2013, Verification, Model Checking, and Abstract Interpretation - 14th International Conference, VMCAI 2013, Proceedings. Springer Verlag, p. 295-314 20 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 7737 LNCS).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

      12 Scopus citations
    • 2010

      Compositional abstraction refinement for timed systems

      He, F., Zhu, H., Hung, W. N. N., Song, X. & Gu, M., 2010, Proceedings - 2010 4th International Symposium on Theoretical Aspects of Software Engineering, TASE 2010. p. 168-176 9 p. 5587714. (Proceedings - 2010 4th International Symposium on Theoretical Aspects of Software Engineering, TASE 2010).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

      4 Scopus citations
    • 2009

      Data mining based decomposition for assume-guarantee reasoning

      Zhu, H., He, F., Hung, W. N. N., Song, X. & Gu, M., Dec 7 2009, 9th International Conference Formal Methods in Computer Aided Design, FMCAD 2009. p. 116-119 4 p. 5351134. (9th International Conference Formal Methods in Computer Aided Design, FMCAD 2009).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

      4 Scopus citations