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Jyotirmoy V. Deshmukh
Jyotirmoy Deshmukh
Person information
- affiliation: University of Southern California, Los Angeles, CA, USA
- affiliation (former): Toyota Technical Center, Gardena, CA, USA
- affiliation (former): University of Texas at Austin, USA
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2020 – today
- 2024
- [j17]Mohammad Hekmatnejad, Bardh Hoxha, Jyotirmoy V. Deshmukh, Yezhou Yang, Georgios Fainekos:
Formalizing and evaluating requirements of perception systems for automated vehicles using spatio-temporal perception logic. Int. J. Robotics Res. 43(2): 203-238 (2024) - [j16]Xin Qin, Yuan Xia, Aditya Zutshi, Chuchu Fan, Jyotirmoy V. Deshmukh:
Statistical Verification using Surrogate Models and Conformal Inference and a Comparison with Risk-Aware Verification. ACM Trans. Cyber Phys. Syst. 8(2): 22 (2024) - [c82]Sam Williams, Jyotirmoy Deshmukh:
Potential Games on Cubic Splines for Multi-Agent Motion Planning of Autonomous Agents. AAMAS 2024: 2555-2557 - [c81]Sheryl Paul, Jyotirmoy V. Deshmukh:
Survival of the Fittest: Evolutionary Adaptation of Policies for Environmental Shifts. ECAI 2024: 3268-3275 - [c80]Yiqi Zhao, Bardh Hoxha, Georgios Fainekos, Jyotirmoy V. Deshmukh, Lars Lindemann:
Robust Conformal Prediction for STL Runtime Verification under Distribution Shift. ICCPS 2024: 169-179 - [c79]Sheryl Paul, Anand Balakrishnan, Xin Qin, Jyotirmoy V. Deshmukh:
Multi-agent Path Finding for Timed Tasks Using Evolutionary Games. QEST+FORMATS 2024: 302-321 - [c78]Vidisha Kudalkar, Navid Hashemi, Shilpa Mukhopadhyay, Swapnil Mallick, Christof Budnik, Parinitha Nagaraja, Jyotirmoy V. Deshmukh:
Sampling-Based and Gradient-Based Efficient Scenario Generation. RV 2024: 70-88 - [i45]Yiqi Zhao, Xinyi Yu, Jyotirmoy V. Deshmukh, Lars Lindemann:
Conformal Predictive Programming for Chance Constrained Optimization. CoRR abs/2402.07407 (2024) - [i44]Michael Collins, Jyotirmoy V. Deshmukh, Dristi Dinesh, Mukund Raghothaman, Srivatsan Ravi, Yuan Xia:
Superflows: A New Tool for Forensic Network Flow Analysis. CoRR abs/2403.01314 (2024) - [i43]Navid Hashemi, Bardh Hoxha, Danil V. Prokhorov, Georgios Fainekos, Jyotirmoy Deshmukh:
Scaling Learning based Policy Optimization for Temporal Tasks via Dropout. CoRR abs/2403.15826 (2024) - [i42]Navid Hashemi, Lars Lindemann, Jyotirmoy V. Deshmukh:
Statistical Reachability Analysis of Stochastic Cyber-Physical Systems under Distribution Shift. CoRR abs/2407.11609 (2024) - [i41]Lars Lindemann, Yiqi Zhao, Xinyi Yu, George J. Pappas, Jyotirmoy V. Deshmukh:
Formal Verification and Control with Conformal Prediction. CoRR abs/2409.00536 (2024) - [i40]Jyotirmoy Deshmukh, Bettina Könighofer, Dejan Nickovic, Filip Cano:
Safety Assurance for Autonomous Mobility (Dagstuhl Seminar 24071). Dagstuhl Reports 14(2): 95-119 (2024) - 2023
- [j15]Aniruddh Gopinath Puranic, Jyotirmoy V. Deshmukh, Stefanos Nikolaidis:
Learning Performance Graphs From Demonstrations via Task-Based Evaluations. IEEE Robotics Autom. Lett. 8(1): 336-343 (2023) - [j14]Jyotirmoy Deshmukh, Dejan Nickovic:
Introduction to the Special Issue on Runtime Verification. Int. J. Softw. Tools Technol. Transf. 25(4): 427-429 (2023) - [c77]Lars Lindemann, Xin Qin, Jyotirmoy V. Deshmukh, George J. Pappas:
Conformal Prediction for STL Runtime Verification. Allerton 2023: 1 - [c76]Navid Hashemi, Xin Qin, Jyotirmoy V. Deshmukh, Georgios Fainekos, Bardh Hoxha, Danil V. Prokhorov, Tomoya Yamaguchi:
Risk-Awareness in Learning Neural Controllers for Temporal Logic Objectives. ACC 2023: 4096-4103 - [c75]Navid Hashemi, Xin Qin, Lars Lindemann, Jyotirmoy V. Deshmukh:
Data-Driven Reachability Analysis of Stochastic Dynamical Systems with Conformal Inference. CDC 2023: 3102-3109 - [c74]Navid Hashemi, Justin Ruths, Jyotirmoy V. Deshmukh:
Convex Optimization-Based Policy Adaptation to Compensate for Distributional Shifts. CDC 2023: 5376-5383 - [c73]Anand Balakrishnan, Stefan Jaksic, Edgar A. Aguilar, Dejan Nickovic, Jyotirmoy V. Deshmukh:
Model-Free Reinforcement Learning for Spatiotemporal Tasks Using Symbolic Automata. CDC 2023: 6834-6840 - [c72]Xin Qin, Navid Hashemi, Lars Lindemann, Jyotirmoy V. Deshmukh:
Conformance Testing for Stochastic Cyber-Physical Systems. FMCAD 2023: 294-305 - [c71]Navid Hashemi, Bardh Hoxha, Tomoya Yamaguchi, Danil V. Prokhorov, Georgios Fainekos, Jyotirmoy Deshmukh:
A Neurosymbolic Approach to the Verification of Temporal Logic Properties of Learning-enabled Control Systems. ICCPS 2023: 98-109 - [c70]Lars Lindemann, Xin Qin, Jyotirmoy V. Deshmukh, George J. Pappas:
Conformal Prediction for STL Runtime Verification. ICCPS 2023: 142-153 - [c69]Xin Qin, Nikos Aréchiga, Jyotirmoy Deshmukh, Andrew Best:
Robust Testing for Cyber-Physical Systems using Reinforcement Learning. MEMOCODE 2023: 36-46 - [c68]Yuriy Biktairov, Jyotirmoy Deshmukh:
SOL: Sampling-based Optimal Linear bounding of arbitrary scalar functions. NeurIPS 2023 - [c67]Swapnil Mallick, Shuvam Ghosal, Anand Balakrishnan, Jyotirmoy Deshmukh:
Safety Monitoring for Pedestrian Detection in Adverse Conditions. RV 2023: 389-399 - [i39]Navid Hashemi, Bardh Hoxha, Tomoya Yamaguchi, Danil V. Prokhorov, Georgios Fainekos, Jyotirmoy Deshmukh:
A Neurosymbolic Approach to the Verification of Temporal Logic Properties of Learning enabled Control Systems. CoRR abs/2303.05394 (2023) - [i38]Navid Hashemi, Justin Ruths, Jyotirmoy V. Deshmukh:
Convex Optimization-based Policy Adaptation to Compensate for Distributional Shifts. CoRR abs/2304.02324 (2023) - [i37]Xin Qin, Navid Hashemi, Lars Lindemann, Jyotirmoy V. Deshmukh:
Conformance Testing for Stochastic Cyber-Physical Systems. CoRR abs/2308.06474 (2023) - [i36]Navid Hashemi, Xin Qin, Lars Lindemann, Jyotirmoy V. Deshmukh:
Data-Driven Reachability Analysis of Stochastic Dynamical Systems with Conformal Inference. CoRR abs/2309.09187 (2023) - [i35]Aniruddh Gopinath Puranic, Jyotirmoy V. Deshmukh, Stefanos Nikolaidis:
Signal Temporal Logic-Guided Apprenticeship Learning. CoRR abs/2311.05084 (2023) - [i34]Yiqi Zhao, Bardh Hoxha, Georgios Fainekos, Jyotirmoy V. Deshmukh, Lars Lindemann:
Robust Conformal Prediction for STL Runtime Verification under Distribution Shift. CoRR abs/2311.09482 (2023) - [i33]Yuan Xia, Jyotirmoy V. Deshmukh, Mukund Raghothaman, Srivatsan Ravi:
Data-Driven Template-Free Invariant Generation. CoRR abs/2312.17527 (2023) - 2022
- [j13]Selma Saidi, Dirk Ziegenbein, Jyotirmoy V. Deshmukh, Rolf Ernst:
Guest Editors' Introduction: Special Issue on Autonomous Systems Design. IEEE Des. Test 39(1): 5-7 (2022) - [j12]Selma Saidi, Dirk Ziegenbein, Jyotirmoy V. Deshmukh, Rolf Ernst:
Autonomous Systems Design: Charting a New Discipline. IEEE Des. Test 39(1): 8-23 (2022) - [c66]Panagiotis Kyriakis, Jyotirmoy V. Deshmukh, Paul Bogdan:
Learning from Demonstrations under Stochastic Temporal Logic Constraints. ACC 2022: 2598-2603 - [c65]Anand Balakrishnan, Stefan Jaksic, Edgar A. Aguilar, Dejan Nickovic, Jyotirmoy Deshmukh:
Poster Abstract: Model-Free Reinforcement Learning for Symbolic Automata-encoded Objectives. HSCC 2022: 26:1-26:2 - [c64]Aniruddh Gopinath Puranic, Jyotirmoy Deshmukh, Stefanos Nikolaidis:
Poster Abstract: Learning from Demonstrations with Temporal Logics. HSCC 2022: 29:1-29:2 - [c63]Xin Qin, Yuan Xian, Aditya Zutshi, Chuchu Fan, Jyotirmoy V. Deshmukh:
Statistical Verification of Cyber-Physical Systems using Surrogate Models and Conformal Inference. ICCPS 2022: 116-126 - [c62]Panagiotis Kyriakis, Jyotirmoy Deshmukh, Paul Bogdan:
Pareto Policy Adaptation. ICLR 2022 - [e5]Jyotirmoy V. Deshmukh, Klaus Havelund, Ivan Perez:
NASA Formal Methods - 14th International Symposium, NFM 2022, Pasadena, CA, USA, May 24-27, 2022, Proceedings. Lecture Notes in Computer Science 13260, Springer 2022, ISBN 978-3-031-06772-3 [contents] - [i32]Anand Balakrishnan, Stefan Jaksic, Edgar A. Aguilar, Dejan Nickovic, Jyotirmoy Deshmukh:
Model-Free Reinforcement Learning for Symbolic Automata-encoded Objectives. CoRR abs/2202.02404 (2022) - [i31]Aniruddh Gopinath Puranic, Jyotirmoy V. Deshmukh, Stefanos Nikolaidis:
Learning Performance Graphs from Demonstrations via Task-Based Evaluations. CoRR abs/2204.05909 (2022) - [i30]Mohammad Hekmatnejad, Bardh Hoxha, Jyotirmoy V. Deshmukh, Yezhou Yang, Georgios Fainekos:
Formalizing and Evaluating Requirements of Perception Systems for Automated Vehicles using Spatio-Temporal Perception Logic. CoRR abs/2206.14372 (2022) - [i29]Sara Mohammadinejad, Jesse Thomason, Jyotirmoy V. Deshmukh:
Interactive Learning from Natural Language and Demonstrations using Signal Temporal Logic. CoRR abs/2207.00627 (2022) - [i28]Navid Hashemi, Xin Qin, Jyotirmoy V. Deshmukh, Georgios Fainekos, Bardh Hoxha, Danil V. Prokhorov, Tomoya Yamaguchi:
Risk-Awareness in Learning Neural Controllers for Temporal Logic Objectives. CoRR abs/2210.07439 (2022) - [i27]Lars Lindemann, Xin Qin, Jyotirmoy V. Deshmukh, George J. Pappas:
Conformal Prediction for STL Runtime Verification. CoRR abs/2211.01539 (2022) - [i26]Sheryl Paul, Jyotirmoy V. Deshmukh:
Multi Agent Path Finding using Evolutionary Game Theory. CoRR abs/2212.02010 (2022) - 2021
- [j11]Aniruddh Gopinath Puranic, Jyotirmoy V. Deshmukh, Stefanos Nikolaidis:
Learning From Demonstrations Using Signal Temporal Logic in Stochastic and Continuous Domains. IEEE Robotics Autom. Lett. 6(4): 6250-6257 (2021) - [j10]Dejan Nickovic, Xin Qin, Thomas Ferrère, Cristinel Mateis, Jyotirmoy Deshmukh:
Specifying and detecting temporal patterns with shape expressions. Int. J. Softw. Tools Technol. Transf. 23(4): 565-577 (2021) - [c61]Mingxi Cheng, Chenzhong Yin, Junyao Zhang, Shahin Nazarian, Jyotirmoy Deshmukh, Paul Bogdan:
A General Trust Framework for Multi-Agent Systems. AAMAS 2021: 332-340 - [c60]Sara Mohammadinejad, Jyotirmoy V. Deshmukh, Laura Nenzi:
Mining Interpretable Spatio-Temporal Logic Properties for Spatially Distributed Systems. ATVA 2021: 91-107 - [c59]Gaurav Gupta, Chenzhong Yin, Jyotirmoy V. Deshmukh, Paul Bogdan:
Non-Markovian Reinforcement Learning using Fractional Dynamics. CDC 2021: 1542-1547 - [c58]Sara Mohammadinejad, Brandon Paulsen, Jyotirmoy V. Deshmukh, Chao Wang:
DiffRNN: Differential Verification of Recurrent Neural Networks. FORMATS 2021: 117-134 - [c57]Mingxi Cheng, Junyao Zhang, Shahin Nazarian, Jyotirmoy Deshmukh, Paul Bogdan:
Trust-aware Control for Intelligent Transportation Systems. IV 2021: 377-384 - [c56]Anand Balakrishnan, Jyotirmoy Deshmukh, Bardh Hoxha, Tomoya Yamaguchi, Georgios Fainekos:
PerceMon: Online Monitoring for Perception Systems. RV 2021: 297-308 - [c55]Ezio Bartocci, Jyotirmoy Deshmukh, Cristinel Mateis, Eleonora Nesterini, Dejan Nickovic, Xin Qin:
Mining Shape Expressions with ShapeIt. SEFM 2021: 110-117 - [i25]Aniruddh Gopinath Puranic, Jyotirmoy V. Deshmukh, Stefanos Nikolaidis:
Learning from Demonstrations using Signal Temporal Logic. CoRR abs/2102.07730 (2021) - [i24]Sara Mohammadinejad, Jyotirmoy V. Deshmukh, Laura Nenzi:
Mining Interpretable Spatio-temporal Logic Properties for Spatially Distributed Systems. CoRR abs/2106.08548 (2021) - [i23]Gaurav Gupta, Chenzhong Yin, Jyotirmoy V. Deshmukh, Paul Bogdan:
Non-Markovian Reinforcement Learning using Fractional Dynamics. CoRR abs/2107.13790 (2021) - [i22]Anand Balakrishnan, Jyotirmoy Deshmukh, Bardh Hoxha, Tomoya Yamaguchi, Georgios Fainekos:
PerceMon: Online Monitoring for Perception Systems. CoRR abs/2108.08289 (2021) - [i21]Ezio Bartocci, Jyotirmoy Deshmukh, Cristinel Mateis, Eleonora Nesterini, Dejan Nickovic, Xin Qin:
Mining Shape Expressions with ShapeIt. CoRR abs/2109.11999 (2021) - [i20]Mingxi Cheng, Junyao Zhang, Shahin Nazarian, Jyotirmoy Deshmukh, Paul Bogdan:
Trust-aware Control for Intelligent Transportation Systems. CoRR abs/2111.04248 (2021) - 2020
- [j9]Ezio Bartocci, Jyotirmoy Deshmukh, Felix Gigler, Cristinel Mateis, Dejan Nickovic, Xin Qin:
Mining Shape Expressions From Positive Examples. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(11): 3809-3820 (2020) - [c54]Aniruddh Gopinath Puranic, Jyotirmoy Deshmukh, Stefanos Nikolaidis:
Learning from Demonstrations using Signal Temporal Logic. CoRL 2020: 2228-2242 - [c53]Xin Qin, Jyotirmoy V. Deshmukh:
Clairvoyant Monitoring for Signal Temporal Logic. FORMATS 2020: 178-195 - [c52]Sara Mohammadinejad, Jyotirmoy V. Deshmukh, Aniruddh Gopinath Puranic, Marcell Vazquez-Chanlatte, Alexandre Donzé:
Interpretable classification of time-series data using efficient enumerative techniques. HSCC 2020: 9:1-9:10 - [c51]Selma Saidi, Dirk Ziegenbein, Jyotirmoy V. Deshmukh, Rolf Ernst:
EDA for Autonomous Behavior Assurance. ICCAD 2020: 81:1-81:3 - [c50]Sara Mohammadinejad, Jyotirmoy V. Deshmukh, Aniruddh Gopinath Puranic:
Mining Environment Assumptions for Cyber-Physical System Models. ICCPS 2020: 87-97 - [c49]Tomoya Yamaguchi, Bardh Hoxha, Danil V. Prokhorov, Jyotirmoy V. Deshmukh:
Specification-guided Software Fault Localization for Autonomous Mobile Systems. MEMOCODE 2020: 1-12 - [e4]Sebastian Steinhorst, Jyotirmoy V. Deshmukh:
2nd International Workshop on Autonomous Systems Design, ASD 2020, March 13, 2020, Grenoble, France (Virtual Conference). OASIcs 79, Schloss Dagstuhl - Leibniz-Zentrum für Informatik 2020, ISBN 978-3-95977-141-2 [contents] - [e3]Aaron D. Ames, Sanjit A. Seshia, Jyotirmoy Deshmukh:
HSCC '20: 23rd ACM International Conference on Hybrid Systems: Computation and Control, Sydney, New South Wales, Australia, April 21-24, 2020. ACM 2020, ISBN 978-1-4503-7018-9 [contents] - [e2]Jyotirmoy Deshmukh, Dejan Nickovic:
Runtime Verification - 20th International Conference, RV 2020, Los Angeles, CA, USA, October 6-9, 2020, Proceedings. Lecture Notes in Computer Science 12399, Springer 2020, ISBN 978-3-030-60507-0 [contents] - [i19]Chuchu Fan, Xin Qin, Jyotirmoy V. Deshmukh:
Parameter Searching and Partition with Probabilistic Coverage Guarantees. CoRR abs/2004.00279 (2020) - [i18]Sara Mohammadinejad, Jyotirmoy V. Deshmukh, Aniruddh Gopinath Puranic:
Mining Environment Assumptions for Cyber-Physical System Models. CoRR abs/2005.08435 (2020) - [i17]Sara Mohammadinejad, Brandon Paulsen, Chao Wang, Jyotirmoy V. Deshmukh:
DiffRNN: Differential Verification of Recurrent Neural Networks. CoRR abs/2007.10135 (2020) - [i16]Parv Kapoor, Anand Balakrishnan, Jyotirmoy V. Deshmukh:
Model-based Reinforcement Learning from Signal Temporal Logic Specifications. CoRR abs/2011.04950 (2020)
2010 – 2019
- 2019
- [j8]Panagiotis Kyriakis, Jyotirmoy V. Deshmukh, Paul Bogdan:
Specification Mining and Robust Design under Uncertainty: A Stochastic Temporal Logic Approach. ACM Trans. Embed. Comput. Syst. 18(5s): 96:1-96:21 (2019) - [c48]Sicun Gao, James Kapinski, Jyotirmoy V. Deshmukh, Nima Roohi, Armando Solar-Lezama, Nikos Aréchiga, Soonho Kong:
Numerically-Robust Inductive Proof Rules for Continuous Dynamical Systems. CAV (2) 2019: 137-154 - [c47]Anand Balakrishnan, Aniruddh Gopinath Puranic, Xin Qin, Adel Dokhanchi, Jyotirmoy V. Deshmukh, Heni Ben Amor, Georgios Fainekos:
Specifying and Evaluating Quality Metrics for Vision-based Perception Systems. DATE 2019: 1433-1438 - [c46]Meng Wu, Jingbo Wang, Jyotirmoy Deshmukh, Chao Wang:
Shield Synthesis for Real: Enforcing Safety in Cyber-Physical Systems. FMCAD 2019: 129-137 - [c45]Xin Qin, Jyotirmoy V. Deshmukh:
Predictive monitoring for signal temporal logic with probabilistic guarantees: poster abstract. HSCC 2019: 266-267 - [c44]Anand Balakrishnan, Jyotirmoy V. Deshmukh:
Structured reward functions using STL: poster abstract. HSCC 2019: 270-271 - [c43]Jyotirmoy V. Deshmukh, James Kapinski, Tomoya Yamaguchi, Danil V. Prokhorov:
Learning Deep Neural Network Controllers for Dynamical Systems with Safety Guarantees: Invited Paper. ICCAD 2019: 1-7 - [c42]Anand Balakrishnan, Jyotirmoy V. Deshmukh:
Structured Reward Shaping using Signal Temporal Logic specifications. IROS 2019: 3481-3486 - [c41]Dejan Nickovic, Xin Qin, Thomas Ferrère, Cristinel Mateis, Jyotirmoy V. Deshmukh:
Shape Expressions for Specifying and Extracting Signal Features. RV 2019: 292-309 - [c40]Xin Qin, Jyotirmoy V. Deshmukh:
Preview of predictive monitoring for signal temporal logic with probabilistic guarantees. SNR 2019: 19-21 - [i15]Sara Mohammadinejad, Jyotirmoy V. Deshmukh, Aniruddh Gopinath Puranic, Marcell Vazquez-Chanlatte, Alexandre Donzé:
Interpretable Classification of Time-Series Data using Efficient Enumerative Techniques. CoRR abs/1907.10265 (2019) - [i14]Meng Wu, Jingbo Wang, Jyotirmoy Deshmukh, Chao Wang:
Shield Synthesis for Real: Enforcing Safety in Cyber-Physical Systems. CoRR abs/1908.05402 (2019) - [i13]Kolby Nottingham, Anand Balakrishnan, Jyotirmoy V. Deshmukh, Connor Christopherson, David Wingate:
Using Logical Specifications of Objectives in Multi-Objective Reinforcement Learning. CoRR abs/1910.01723 (2019) - [i12]Xin Qin, Nikos Aréchiga, Andrew Best, Jyotirmoy V. Deshmukh:
Automatic Testing and Falsification with Dynamically Constrained Reinforcement Learning. CoRR abs/1910.13645 (2019) - [i11]Jyotirmoy V. Deshmukh, Oded Maler, Dejan Nickovic:
Specification Formalisms for Modern Cyber-Physical Systems (Dagstuhl Seminar 19071). Dagstuhl Reports 9(2): 48-72 (2019) - 2018
- [j7]Ayca Balkan, Paulo Tabuada, Jyotirmoy V. Deshmukh, Xiaoqing Jin, James Kapinski:
Underminer: A Framework for Automatically Identifying Nonconverging Behaviors in Black-Box System Models. ACM Trans. Embed. Comput. Syst. 17(1): 20:1-20:28 (2018) - [c39]Cumhur Erkan Tuncali, James Kapinski, Hisahiro Ito, Jyotirmoy V. Deshmukh:
Reasoning about safety of learning-enabled components in autonomous cyber-physical systems. DAC 2018: 30:1-30:6 - [c38]Jyotirmoy V. Deshmukh, Panagiotis Kyriakis, Paul Bogdan:
Stochastic Temporal Logic Abstractions: Challenges and Opportunities. FORMATS 2018: 3-16 - [c37]Jyotirmoy V. Deshmukh, Xiaoqing Jin, Rupak Majumdar, Vinayak S. Prabhu:
Parameter optimization in control software using statistical fault localization techniques. ICCPS 2018: 220-231 - [c36]Borzoo Bonakdarpour, Jyotirmoy V. Deshmukh, Miroslav Pajic:
Opportunities and Challenges in Monitoring Cyber-Physical Systems Security. ISoLA (4) 2018: 9-18 - [c35]Marcell Vazquez-Chanlatte, Shromona Ghosh, Jyotirmoy V. Deshmukh, Alberto L. Sangiovanni-Vincentelli, Sanjit A. Seshia:
Time-Series Learning Using Monotonic Logical Properties. RV 2018: 389-405 - [c34]Adel Dokhanchi, Heni Ben Amor, Jyotirmoy V. Deshmukh, Georgios Fainekos:
Evaluating Perception Systems for Autonomous Vehicles Using Quality Temporal Logic. RV 2018: 409-416 - [p1]Ezio Bartocci, Jyotirmoy V. Deshmukh, Alexandre Donzé, Georgios Fainekos, Oded Maler, Dejan Nickovic, Sriram Sankaranarayanan:
Specification-Based Monitoring of Cyber-Physical Systems: A Survey on Theory, Tools and Applications. Lectures on Runtime Verification 2018: 135-175 - [e1]Maria Prandini, Jyotirmoy V. Deshmukh:
Proceedings of the 21st International Conference on Hybrid Systems: Computation and Control (part of CPS Week), HSCC 2018, Porto, Portugal, April 11-13, 2018. ACM 2018 [contents] - [i10]Marcell Vazquez-Chanlatte, Shromona Ghosh, Jyotirmoy V. Deshmukh, Alberto L. Sangiovanni-Vincentelli, Sanjit A. Seshia:
Time Series Learning using Monotonic Logical Properties. CoRR abs/1802.08924 (2018) - [i9]Cumhur Erkan Tuncali, James Kapinski, Hisahiro Ito, Jyotirmoy V. Deshmukh:
Reasoning about Safety of Learning-Enabled Components in Autonomous Cyber-physical Systems. CoRR abs/1804.03973 (2018) - [i8]Xin Qin, Jyotirmoy V. Deshmukh:
Joint Probability Distribution of Prediction Errors of ARIMA. CoRR abs/1811.04685 (2018) - 2017
- [j6]Jyotirmoy V. Deshmukh, Rupak Majumdar, Vinayak S. Prabhu:
Quantifying conformance using the Skorokhod metric. Formal Methods Syst. Des. 50(2-3): 168-206 (2017) - [j5]Jyotirmoy V. Deshmukh, Alexandre Donzé, Shromona Ghosh, Xiaoqing Jin, Garvit Juniwal, Sanjit A. Seshia:
Robust online monitoring of signal temporal logic. Formal Methods Syst. Des. 51(1): 5-30 (2017) - [j4]Jyotirmoy V. Deshmukh, Marko Horvat, Xiaoqing Jin, Rupak Majumdar, Vinayak S. Prabhu:
Testing Cyber-Physical Systems through Bayesian Optimization. ACM Trans. Embed. Comput. Syst. 16(5s): 170:1-170:18 (2017) - [c33]Marcell Vazquez-Chanlatte, Jyotirmoy V. Deshmukh, Xiaoqing Jin, Sanjit A. Seshia:
Logical Clustering and Learning for Time-Series Data. CAV (1) 2017: 305-325 - [c32]Luan Viet Nguyen, James Kapinski, Xiaoqing Jin, Jyotirmoy V. Deshmukh, Ken Butts, Taylor T. Johnson:
Abnormal Data Classification Using Time-Frequency Temporal Logic. HSCC 2017: 237-242 - [c31]Luan Viet Nguyen, James Kapinski, Xiaoqing Jin, Jyotirmoy V. Deshmukh, Taylor T. Johnson:
Hyperproperties of real-valued signals. MEMOCODE 2017: 104-113 - [c30]Jyotirmoy V. Deshmukh, Wolfgang Kunz, Hans-Joachim Wunderlich, Sybille Hellebrand:
Special session on early life failures. VTS 2017: 1 - [i7]Jyotirmoy V. Deshmukh, Xiaoqing Jin, Rupak Majumdar, Vinayak S. Prabhu:
Parameter Optimization in Control Software using Statistical Fault Localization Techniques. CoRR abs/1710.02073 (2017) - 2016
- [c29]Ayca Balkan, Paulo Tabuada, Jyotirmoy V. Deshmukh, Xiaoqing Jin, James Kapinski:
Underminer: a framework for automatically identifying non-converging behaviors in black box system models. EMSOFT 2016: 7:1-7:10 - [c28]Aditya Zutshi, Sriram Sankaranarayanan, Jyotirmoy V. Deshmukh, Xiaoqing Jin:
Symbolic-Numeric Reachability Analysis of Closed-Loop Control Software. HSCC 2016: 135-144 - [i6]Marcell V.-Chanlatte, Jyotirmoy V. Deshmukh, Xiaoqing Jin, Sanjit A. Seshia:
Learning Auditable Features from Signals Using Unsupervised Temporal Projection. CoRR abs/1612.07823 (2016) - 2015
- [j3]